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World Leaders to meet during Davos Agenda in a crucial year to rebuild trust

Reporter: Aviva Lev-Ari, PhD, RN

 

Davos Agenda

https://www.weforum.org/events/the-davos-agenda-2021

 

Adrian Monck, Managing Director, Public Engagement, public.affairs@weforum.org

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World Leaders to Meet During Davos Agenda in a Crucial Year to Rebuild Trust

  • The Davos Agenda 2021 will convene under the theme: A Crucial Year to Rebuild Trust
  • The World Economic Forum will gather the world’s foremost leaders to address the economic, environmental, social and technological challenges following the COVID-19 pandemic 
  • More than 1,500 business, government and civil society leaders from over 70 countries will set the agenda for a critical year ahead and discuss how to catalyse impact in the rapidly advancing Fourth Industrial Revolution
  • The conclusions from the Davos Agenda week will feed into task forces working on global issues for the upcoming Special Annual Meeting in Singapore
  • For more information, please visit http://www.weforum.org; share on social media using the hashtag #DavosAgenda

Geneva, Switzerland, 18 January 2021 – The World Economic Forum Davos Agenda, taking place virtually on 25-29 January, will bring together the foremost leaders of the world to address the new global situation. Heads of state and government, chief executives and leaders from civil society will convene under the theme: A Crucial Year to Rebuild Trust.

The meeting will focus on creating impact, rebuilding trust and shaping the policies and partnerships needed in 2021.

“In the context of the COVID-19 pandemic, the need to reset priorities and the urgency to reform systems have been growing stronger around the world,” said Klaus Schwab, Founder and Executive Chairman of the World Economic Forum. “Rebuilding trust and increasing global cooperation are crucial to fostering innovative and bold solutions to stem the pandemic and drive a robust recovery. This unique meeting will be an opportunity for leaders to outline their vision and address the most important issues of our time, such as the need to accelerate job creation and to protect the environment.”

The COVID-19 pandemic has demonstrated that no institution or individual alone can address the economic, environmental, social and technological challenges of our complex, interdependent world. The pandemic has accelerated systemic changes that were apparent before its inception. The fault lines that emerged in 2020 now appear as critical crossroads in 2021. The Davos Agenda will help leaders choose innovative and bold solutions to stem the pandemic and drive a robust recovery over the next year.

The five programme themes are:

  1. Designing cohesive, sustainable, resilient economic systems (25 January)
  2. Driving responsible industry transformation and growth (26 January)
  3. Enhancing stewardship of the global commons (27 January)
  4. Harnessing the technologies of the Fourth Industrial Revolution (28 January)
  5. Advancing global and regional cooperation (29 January)

Special addresses from G20 heads of state and government and international organizations will provide crucial insights into a range of important issues in the year ahead. Participants will hear first-hand how these public figures will demonstrate leadership and drive action in areas such as the environment, jobs, and advances in innovation brought by the Fourth Industrial Revolution.

Heads of state and government include:

Xi Jinping, President of the People’s Republic of China; Narendra Modi, Prime Minister of India; Yoshihide Suga, Prime Minister of Japan; Emmanuel Macron, President of France; Angela Merkel, Federal Chancellor of Germany; Ursula von der Leyen, President of the European Commission; Giuseppe Conte, Prime Minister of Italy; Moon Jae-in, President of the Republic of Korea; Alberto Fernández, President of Argentina; Cyril Ramaphosa, President of South Africa; Pedro Sánchez, Prime Minister of Spain; Guy Parmelin, President of the Swiss Confederation and Federal Councillor for Economic Affairs, Education and Research; Ivan Duque, President of Colombia; Carlos Alvarado Quesada, President of Costa Rica; Nana Addo Dankwa Akufo-Addo, President of the Republic of Ghana; Kyriakos Mitsotakis, Prime Minister of Greece; Benjamin Netanyahu, Prime Minister of Israel; Abdullah II ibn Al Hussein, King of the Hashemite Kingdom of Jordan; Paul Kagame, President of Rwanda; Lee Hsien Loong, Prime Minister of Singapore, the host of the World Economic Forum Special Annual Meeting 2021.

Other world leaders are expected to confirm.

Leaders from international organizations, government agencies and central banks include:

António Guterres, Secretary-General, United Nations (UN); Tedros Adhanom Ghebreyesus, Director-General, World Health Organization (WHO); Kristalina Georgieva, Managing Director, International Monetary Fund (IMF); Amina Mohammed, Deputy Secretary-General, United Nations (UN); Achim Steiner, Administrator, United Nations Development Programme (UNDP); Phumzile Mlambo-Ngcuka, Undersecretary-General and Executive Director, United Nations Entity for Gender Equality and the Empowerment of Women (UN WOMEN); Dongyu Qu, Director-General, Food and Agriculture Organization of the United Nations (FAO); Inger Andersen, Executive Director, United Nations Environment Programme (UNEP); Henrietta Fore, Executive Director, United Nations Children’s Fund (UNICEF); David Beasley, Executive Director, United Nations World Food Programme (WFP); Fang Liu, Secretary-General, International Civil Aviation Organization (ICAO); Anthony Fauci, Director, National Institute of Allergy and Infectious Diseases, National Institutes of Health, USA; Angel Gurría, Secretary-General, Organisation for Economic Co-operation and Development (OECD); Mauricio Claver-Carone, President, Inter-American Development Bank (IDB); Guy Ryder, Director-General, International Labour Organization (ILO); Jürgen Stock, Secretary-General, International Criminal Police Organization (INTERPOL); Fatih Birol, Executive Director, International Energy Agency (IEA); Rebecca Fatima Sta Maria, Executive Director, APEC Secretariat (Asia-Pacific Economic Cooperation).

Christine Lagarde, President, European Central Bank; François Villeroy de Galhau, Governor of the Central Bank of France; Andrew Bailey, Governor of the Bank of England.

The private sector will be represented by more than 1,000 leaders from the Forum’s member and partner organizations. Seven of the top ten companies by market capitalization are engaged year-round with the Forum and many will participate in The Davos Agenda week. As a working meeting to advance ongoing project work, more than 500 chief executives and chairpersons will take part in sessions throughout the week.

Leaders from civil society are a critical voice in shaping the agenda. Those taking part in the meeting include:

Seth Berkley, Chief Executive Officer, Gavi, the Vaccine Alliance; Gabriela Bucher, Executive Director, Oxfam International; Sharan Burrow, General Secretary, International Trade Union Confederation (ITUC); Hindou Oumarou Ibrahim, President, Association for Indigenous Women and Peoples of Chad (AFPAT); Marco Lambertini, Director-General, WWF International; Laura Liswood, Secretary-General, Council of Women World Leaders; Delia Ferreira Rubio, Chair, Transparency International; Peter Sands, Executive Director, Global Fund to Fight AIDS, Tuberculosis and Malaria (GF). 

Drawn from over 10,000 civic-minded young leaders, members of the World Economic Forum’s Global Shapers, Young Global Leaders, Technology Pioneers and Social Entrepreneurs communities will bring unique perspectives to The Davos Agenda.

Flagship reports, initiatives, and the latest book on Stakeholder Capitalism 

On January 25, Professor Schwab will release his latest book, titled “Stakeholder Capitalism: A Global Economy that Works for Progress, People and Planet.” It explores how societies can build the future post-COVID, and builds on the Forum’s 50-year-old advocacy of the stakeholder approach.

The World Economic Forum will release its Global Risks Report 2021 on 19 January. The flagship report is an important marker for prioritizing action in public and private sectors in the year ahead.

The Davos Agenda will also mark the launch of several World Economic Forum initiatives to accelerate the race to net-zero emissions, to champion new standards for racial justice, to ensure artificial intelligence is developed ethically and in the global public interest and to close the digital divide. More details on these initiatives and others will be disclosed at the meeting.

Opening Event and Crystal Awards

The meeting will be preceded by the Opening Event, available on YouTube on Sunday 24 January at 19.00 CET, featuring a welcome from Klaus Schwab and a special address by Guy Parmelin, President of the Swiss Confederation, just before the 27th Crystal Awards hosted by Hilde Schwab, Chairperson and Co-founder, Schwab Foundation for Social Entrepreneurship, and the photographer Platon.

The awards will be followed by the world premiere of “See Me: A Global Concert.” The official programme of The Davos Agenda will begin on 25 January.

Notes to editors

Media registration and sign-up

Explore the guide on how to follow and embed sessions on your website here

Watch the livestreamed sessions here

Follow the Forum on Twitter via @wef@davos and join the conversation using #DavosAgenda | Instagram | LinkedIn | TikTok | Weibo | Podcasts

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SOURCE

From: “<Adrian Monck>”, World Economic Forum <Public.Affairs@weforum.org>

Reply-To: “<Adrian Monck>”, World Economic Forum <Public.Affairs@weforum.org>

Date: Monday, January 18, 2021 at 9:37 AM

To: “Aviva Lev-Ari, PhD, RN” <AvivaLev-Ari@alum.berkeley.edu>

Subject: World Leaders to meet during Davos Agenda in a crucial year to rebuild trust

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REUTERS NEXT (Jan 11-14) kicks off 2021 by gathering global leaders and forward thinkers to reimagine solutions to the challenges the new year brings

Reporter: Aviva Lev-Ari, PhD, RN

 

The Virtual Summit Rethinking the Future

REUTERS NEXT kicks off 2021 by gathering global leaders and forward thinkers to reimagine solutions to the challenges the new year brings.

After the extraordinary upheavals of 2020, we will come together to look ahead at opportunities for change and growth, as well as how to deal with the rifts and problems that our world and our societies face.

No country, company or community can tackle the future alone. To build a better world, thinkers and doers must come together to share ideas, collaborate and act.

REUTERS NEXT draws on Reuters global reach to host diverse voices from around the world who will examine topics from different perspectives, bringing their passion, experience and expertise to find new ways forward.

Join the conversation at REUTERS NEXT as we look ahead, together.

https://reutersevents.com/events/next/#about

https://reutersevents.app.swapcard.com/event/reuters-next

Leaders in Pharmaceutical Business Intelligence (LPBI) Group

Announcing Strategic Transition from 1.0 LPBI to 2.0 LPBI on 1/1/2021: New Management, Marketing Communication and New Scientific/Technical Opportunities

 

Aviva Lev-Ari, PhD, RN, Founder, LPBI Group: 1.0 & 2.0

will attend REUTERS NEXT on January 13 & 14, 2021 and

will cover these days in real time

AGENDA

https://reutersevents.com/events/next/conference-agenda.php

 

Day 1: January 11

 RECOVERING GROWTH
5:30am GMT
Capturing a Slice of the Boom in High-Net-Worth Banking

The private banking arm of OCBC Bank is among a handful of Asian banks that have emerged among the biggest serving the region’s growing legion of billionaires. Boasting assets under management of $116 billion, Bank of Singapore has expanded into Europe, India and Dubai as it seeks to serve the family offices of the rich. The private bank, part of Southeast Asia’s second-largest lender, is also exploring setting up an onshore presence in China, the top market for wealth creation.

 

Bahren Shaari

Bahren ShaariChief Executive OfficerBank of Singapore

 

Anshuman Daga

Anshuman DagaSenior Financial CorrespondentReuters

 POLICY & PROGRESS
6:00am GMT
Interview

 

Dr Reza Baqir

Dr Reza BaqirGovernorState Bank Pakistan

 

Simon Robinson

Simon RobinsonGlobal Managing EditorReuters

 POLICY & PROGRESS
6:30am GMT
Interview

 

Tae Yong-ho

Tae Yong-hoThe Member of the National Assembly of The Republic of Korea

 

Jack Kim

Jack KimCorrespondentReuters

 POLICY & PROGRESS
7:00am GMT
Asia’s COVID-19 journey: Swifter Response But Slower Return to Normality?

Asia has managed to control the spread of the new coronavirus more swiftly and effectively than the rest of the world, but many countries in the region are still battling with a persistent resurgence of new cases and the initial amount of vaccines Asia will receive will be limited. Is Asia likely to lag other regions in ending the pandemic and when will things go back to normal?

 

Dr. Pandu Riono

Dr. Pandu RionoEpidemiologist & Senior StaffUniversity of Indonesia, Faculty of Public Health

 

Irma Hidayana

Irma HidayanaCo-Founder & Co-LeaderLaporCovid19

 

Dale Fisher

Dale FisherProfessor of MedicineNational University of Singapore

 

Miyoung Kim

Moderator: Miyoung KimBreaking News Editor, AsiaReuters

 POLICY & PROGRESS
7:30am GMT
Interview

 

Edward Yau Tang-wah

Edward Yau Tang-wahSecretary for Commerce and Economic DevelopmentHong Kong Special Administrative Region Government

 

Anne-Marie Roantree

Anne-Marie RoantreeBureau ChiefReuters

 RADICAL REDESIGN
9:00am GMT
Recovering the Travel Bug post-Covid

 

Deep Kalra

Deep KalraFounder & Group Executive ChairmanMakeMyTrip Limited

 

Sabina Fluxa

Sabina FluxaChief Executive OfficerIberostar

 

Tony Fernandes

Tony FernandesChief Executive OfficerAirAsia

 SUSTAINABLE FUTURE
9:30am GMT
Urban Mining: Recycling on a Mass Scale

 

Steve Fisher

Steve FisherPresident and Chief Executive OfficerNovelis

 

Yash Lohia

Yash LohiaChief Sustainability OfficerIndorama Ventures

 SUSTAINABLE FUTURE
10:00am GMT
The Measurement Challenge of Carbon Accounting

How can we cut emissions if we can’t count them?

 

David Hone

David HoneChief Climate Change AdviserShell

 

Nick Stansbury

Nick StansburyHead of Commodity ResearchLegal & General Investment Management (LGIM)

 

Sean Kidney

Sean KidneyChief Executive OfficerClimate Bonds Initiative

 RECOVERING GROWTH
10:30am GMT
Powering Economic Growth in Africa

Look at different investment strategies – infrastructure, digital and trade.

 

Fola Fagbule

Fola FagbuleSenior Vice PresidentAfrica Finance Corporation

 

Juliana Rotich

Juliana RotichVenture PartnerAtlantica Ventures

 

Silver Ojakol

Silver OjakolCommissioner External TradeGhana

 POLICY & PROGRESS
11:00am GMT
Interview

 

Vera Daves de Sousa

Vera Daves de SousaFinance MinisterMinistry of Finance of Angola

 RADICAL REDESIGN
11:30am GMT
Ethnic Diversity at Work: Putting Words into Action

 

Lanaya Irvin

Lanaya IrvinPresidentCoqual

 

John Rice

John RiceFounder & Chief Executive OfficerManagement Leadership for Tomorrow

 MEDIA & FREE SPEECH
12:00pm GMT
Interview

 

Waad al-Kateab

Waad al-KateabFilmmaker, Activist & FounderAction For Sama

 RADICAL REDESIGN
12:30pm GMT
Ethnic Diversity at Work: Putting Words into Action

Companies lurched into diversity policies after Floyd’s death. Will they stick?

 

soon

Speakers TBC

 MEDIA & FREE SPEECH
1:00pm GMT
How to Rebuild Trust in Media

In a polarised world, news media need to rebuild trust. Impartiality, transparency, representation and listening all play a part. What other strategies are top media executives planning?

 

Tim Davie

Tim DavieDirector GeneralBBC

 

Michael Friedenberg

Michael FriedenbergPresidentReuters

 

Jane Barrett

Moderator: Jane BarrettGlobal Editor Media News StrategyReuters

 SUSTAINABLE FUTURE
3:00pm GMT
Interview

 

Professor Jeffrey Sachs

Professor Jeffrey SachsEconomist & DirectorCenter for Sustainable Development at Columbia University

 

soon

Ann SaphirFinancial ReporterReuters

 SUSTAINABLE FUTURE
3:20pm GMT
Nuclear Energy and its Future

 

Sama Bilbao y Leon

Sama Bilbao y LeonDirector GeneralWorld Nuclear Association

 

Dan Poneman

Dan PonemanPresident & Chief Executive OfficerCentrus Energy Corp.

 

Jay Wileman

Jay WilemanPresident & Chief Executive OfficerGE Hitachi

 

George Borovas

George BorovasHead of Nuclear and Tokyo Office Managing PartnerHunton Andrews Kurth

 

soon

Moderator: Nina ChestneyHead of EMEA Power, Gas, Coal and CarbonReuters

 RECOVERING GROWTH
4:00pm GMT
Trade, Doing Business Globally, Challenges

 

Joe Kaeser

Joe KaeserPresident & Chief Executive OfficerSiemens AG

 RADICAL REDESIGN
4:30pm GMT
Edtech: Making the Most of Online Learning Beyond Covid

 

Dwayne Matthews

Dwayne MatthewsEducation Strategist & FounderTomorrowNow Learning Labs

 SUSTAINABLE FUTURE
5:00pm GMT
The Arctic Frontier

Climate change is warming the Arctic faster than the rest of the world, opening long-frozen region to exploration, tourism, mining and shipping. Those crowds and commerce have an impact on the environment and indigenous communities.

 

Ann Daniels

Ann DanielsPolar Explorer

 

Ilarion Merculieff

Ilarion MerculieffPresidentGlobal Center for Indigenous Leadership and Lifeways

 

Neil Roberts

Neil RobertsHead of Marine and AviationLloyd’s of London Market Association

 

Clare Baldwin

Moderator: Clare BaldwinSpecial CorrespondentReuters

 SUSTAINABLE FUTURE
5:30pm GMT
Managing the Energy Transition from Within

Top players in the oil industry discuss the challenges and opportunities for their businesses in a transition away from fossil fuels.

 

Lorenzo Simonelli

Lorenzo SimonelliChief Executive OfficerBaker Hughes

 

Jennifer Hiller

Moderator: Jennifer HillerOil & Gas ReporterReuters

 RADICAL REDESIGN
6:00pm GMT
Interview

 

Salman Khan

Salman KhanFounder and CEOKhan Academy

 RADICAL REDESIGN
6:20pm GMT
Interview

 

Sheryl Sandberg

Sheryl SandbergChief Operating OfficerFacebook

Day 2: January 12

 POLICY & PROGRESS
5:30am GMT
India’s Place in a Divided World

 

Dr. S. Jaishankar

Dr. S. JaishankarExternal Affairs Minister of India

 POLICY & PROGRESS
6:00am GMT
Philippines: On the Road to Recovery?

 

Benjamin Diokno

Benjamin DioknoGovernorBangko Sentral ng Pilipinas

 

Karen Lema

Karen LemaBureau Chief PhilippinesReuters

 RECOVERING GROWTH
6:30am GMT
Where Asia’s Smart Money is Going in 2021

 

Hugh Young

Hugh YoungManaging DirectorAberdeen Standard Investments

 

Elizabeth Allen

Elizabeth AllenHead of Asian Fixed IncomeHSBC Global Asset Management

 MEDIA & FREE SPEECH
7:00am GMT
Political journalism in Asia: new media, old values

 

Steve Gan

Steve GanEditor-in-chiefMalaysiakini.com

 

Najwa Shihab

Najwa ShihabNewscaster & AnchorMetro TV Indonesia

 

Cherian George

Cherian GeorgeProfessor of Media StudiesHong Kong Baptist University

 MEDIA & FREE SPEECH
7:30am GMT
Interview

 

K Shanmugam

K ShanmugamMinister for Home Affairs & Minister for Law

 RADICAL REDESIGN
9:00am GMT
Australia vs Big Tech

The ACCC’s Sims is spearheading potential changes to Australia’s merger laws early in 2021, putting the country at the front of a global crackdown on antitrust violations from “Big Tech.” The ACCC is due to deliver a report on the app marketplace, with a focus on the market power of Apple and Google, by the end of March. The regulator has already taken legal action against Google twice – for misleading consumers about how much personal information it was tracking and for misleading consumers about its collection of personal location data.

 

Rod Sims

Rod SimsChairAustralian Competition and Consumer Commission

 RADICAL REDESIGN
10:10am GMT
Interview

 

Nguyen Thi Phuong Thao

Nguyen Thi Phuong ThaoPresident & CEOVietJet

 RECOVERING GROWTH
10:30am GMT
A New Economy: Africa’s Digital Engine

 

Jihan Abass

Jihan AbassFounder & Chief Executive OfficerLami

 

Iyinoluwa Aboyeji

Iyinoluwa AboyejiTech Entrepreneur Co-FounderAndela

 MEDIA & FREE SPEECH
11:00am GMT
Interview

 

Sir Tim Berners-Lee

Sir Tim Berners-LeeInventor of World Wide Web and CTOInrupt

 

John Bruce

John BruceChief Executive OfficerInrupt

 RADICAL REDESIGN
12:00pm GMT
Banking the Unbanked with New Technology

Digital taking barriers down and making banking more possible – but also making digital a requirement?

 

Vijay Shekar Sharma

Vijay Shekar SharmaChief Executive Officer & FounderPaytm

 POLICY & PROGRESS
12:30pm GMT
Interview

 

Olaf Scholz

Olaf ScholzFederal Minister of Finance and Vice ChancellorGerman Federal Ministry of Finance

 

Mark Bendeich

Mark BendeichEurope News EditorReuters

 SUSTAINABLE FUTURE
3:00pm GMT
Interview

 

Patricia Espinosa

Patricia EspinosaExecutive SecretaryUnited Nations Framework Convention on Climate Change

 

Matthew Green

Matthew GreenClimate Change CorrespondentReuters

 MEDIA & FREE SPEECH
3:30pm GMT
Misinformation and New Narratives

Conspiracy theories and misinformation have spewed out of social media to mainstream narratives. Where does it all come from? How do they proliferate and what can we do about it?

 

Graham Brookie

Graham BrookieDirector and Managing Editor, Digital Forensic Research Lab (DFRLab)Atlantic Council

 

Claire Wardle

Claire WardleCo-FounderFirst Draft

 

Christina Anagnostopoulos

Christina AnagnostopoulosSenior Producer, Reuters Fact CheckReuters

 SUSTAINABLE FUTURE
4:00pm GMT
Batteries – Lithium as the New Oil

 

Eric Norris

Eric NorrisPresident – Lithium GBUAlbemarle Corporation

 

Ernest Scheyder

Ernest ScheyderCorrespondentReuters

 SUSTAINABLE FUTURE
4:30pm GMT
The Future of Fossil Fuels in A Green World

Unlike Shell or BP, Chevron has been unabashed about its commitment to fossil fuels. It’s been smarter than others though, has a stronger balance sheet, and has made more calculated decisions. This has shown up in its market value, which last week surpassed Exxon Mobil for the first time ever. Wirth will have a lot to say about global economies, too, and the global rebound from the Covid-19 crisis.

 

Michael Wirth

Michael WirthChief Executive OfficerChevron

 

Lauren Silva Laughlin

Lauren Silva LaughlinGlobal Deals EditorReuters

 

Rob Cox

Rob CoxGlobal EditorReuters Breakingviews

 RECOVERING GROWTH
5:00pm GMT
Rich World, Poor World. How to Close the Gap

What are the best ways to help the poorer countries of the world and their societies? Is the age of foreign aid over? What about debt relief and keeping more tax in country?

 

Dambisa Moyo

Dambisa MoyoGlobal Economist & AuthorVersaca Investments

 SUSTAINABLE FUTURE
5:30pm GMT
Keep It In The Ground: A Radical Solution to Climate Change

Is the best way to lower emissions to keep fossil fuels in the ground? Why environmentalists believe not tapping new oil and gas deposits, and plugging abandoned wells, would benefit investors and society.

 

Janet Redman

Janet RedmanClimate Campaign DirectorGreenpeace USA

 

Kassie Siegel

Kassie SiegelSenior Counsel and DirectorThe Climate Law Institute

 

Peter Erickson

Peter EricksonSenior ScientistStockholm Environment Institute

 RECOVERING GROWTH
6:00pm GMT
Interview

 

Stephen Pagliuca

Stephen PagliucaCo-chairBain

 

Lauren Silva Laughlin

Lauren Silva LaughlinGlobal Deals EditorReuters

 RECOVERING GROWTH
6:20pm GMT
Interview

 

Calvin McDonald

Calvin McDonaldChief Executive OfficerLululemon

Day 3: January 13

 RADICAL REDESIGN
5:30am GMT
Asia Aviation in a Post-Pandemic World

The once fast-growing Asian aviation industry has been hit hard by the pandemic, with the region among the slowest to reopen international travel, though domestic travel has begun to rebound. How will the pandemic shape future travel patterns for leisure and business travel? How can airlines like Qantas adapt their product, fleet and route networks for the future passenger mix? How will they restore confidence in international travel before and after a vaccine?

 

Alan Joyce

Alan JoyceChief Executive OfficerQantas

 RECOVERING GROWTH
6:00am GMT
How to Sell Drinks in a Socially-Distanced World

Suntory, like all global drinks makers, has been hit hard by the pandemic which has dented sales of its popular beer and global whiskies. Even with the eventual arrival of vaccines, consumers are expected to remain wary of crowding together at bars and restaurants as they used to. How is Suntory riding out the slump? Are there any new growth opportunities in post-pandemic trends (drinking at home, non-alcohol beers etc.)? Has the pandemic, and the global political landscape, changed his views on globalization? Do Japanese companies including Suntory need to be more wary of large-scale, international acquisitions now?

 

Takeshi Niinami

Takeshi NiinamiChief Executive OfficerSuntory

 MEDIA & FREE SPEECH
6:30am GMT
Silencing the Messenger: The Struggle for Free Speech in Asia

Over the past three decades, more journalists have been killed in Asia Pacific than any other region on earth, with the Philippines, India, and Afghanistan consistently ranked among the deadliest places to be a journalist. Overall press freedom has worsened in more than a dozen countries across the continent since 2018, according to watchdog Reporters Without Borders, and in a time of pandemic, pervasive online misinformation, and rising authoritarianism, news organizations are facing unprecedented challenges.

 

Khin Omar

Khin OmarBurmese Democracy Activist

 

Nidhi Razdan

Nidhi RazdanAssociate Professor of JournalismHarvard University

 

Vergel O. Santos

Vergel O. SantosMember, Board of TrusteesCenter for Media Freedom and Responsibility

 RECOVERING GROWTH
7:00am GMT
China Private Equity: Navigating volatilities and capturing new growth post-COVID (3)

 

Dr. Fred Hu

Dr. Fred HuChairmanPrimavera Capital Group

 RECOVERING GROWTH
7:20am GMT
China Private Equity: Navigating volatilities and capturing new growth post-COVID (1)

 

Shan Weijian

Shan WeijianChairman and Chief Executive OfficerPAG

 POLICY & PROGRESS
9:00am GMT
The EU economy post-COVID, post-Brexit, in debt…

 

Christine Lagarde

Christine LagardePresidentEuropean Central Bank

 

Alessandra Galloni

Alessandra GalloniGlobal Managing EditorReuters

 MEDIA & FREE SPEECH
9:45am GMT
How and Why to Fight Threats to Press Freedom Around the World

A global panel on press freedom around the world. Is it getting generally worse?

 

Maria Ressa

Maria RessaFounder, Rapplercompany

 

Sonny Swe

Sonny SweCo-Founder & Chief Executive OfficerFrontier Myanmar

 RADICAL REDESIGN
10:30am GMT
Telling Africa Stories

How African storytellers are reshaping the way the world sees the continent.

 

Bibi Bakare-Yusuf

Bibi Bakare-YusufFounder & PublisherCassava Republic Press

 

Mo Abudu

Mo AbuduChief Executive OfficerEbonylife Media & Ebonylife Place

 RADICAL REDESIGN
12:00pm GMT
Managing the Masses and Politicians through the Fog of Covid

 

Dr. Anders Tegnell

Dr. Anders TegnellState EpidemiologistSweden

 

Dr. Chikwe Ihekweazu

Dr. Chikwe IhekweazuDirector GeneralNigeria Centre for Disease Control (NCDC)

 RADICAL REDESIGN
1:00pm GMT
Precious Cargo: Transporting Vaccines and Looking for Recovery

 

John Pearson

John PearsonChief Executive OfficerDHL Express

 RECOVERING GROWTH
1:30pm GMT
Interview

 

Alan Jope

Alan JopeChief Executive OfficerUnilever

 RECOVERING GROWTH
3:00pm GMT
Pets and the pandemic: The future of animal science

 

Kristin Peck

Kristin PeckChief Executive OfficerZoetis

 POLICY & PROGRESS
3:30pm GMT
Public Health Lessons from COVID and Vaccinations

COVID-19 has laid bare many failings in the public health system. What lessons are there to learn around the world and what are the biggest challenges beyond COVID?

 

Heidi J Larson

Heidi J LarsonProfessor of AnthropologyRisk and Decision Science Vaccine Confidence Project

 

Professor Michelle Williams

Professor Michelle WilliamsDean of the FacultyHarvard T.H. Chan School of Public Health

4:00pm GMT
Interview

 

soon

Speaker TBC

 RADICAL REDESIGN
4:30pm GMT
Interview

 

Sandeep Mathrani

Sandeep MathraniChief Executive OfficerWeWork

 MEDIA & FREE SPEECH
5:00pm GMT
The Edelman Trust Barometer 2021

Richard Edelman discusses the new Trust Barometer for 2021. To discuss trust in journalism, politicians, tech companies etc.

 

Richard Edelman

Richard EdelmanChief Executive OfficerEdelman

 SUSTAINABLE FUTURE
5:30pm GMT
Climate and Environmental Justice

What do we do about the unequal impact of climate change?

 

Dr Friederike Otto

Dr Friederike OttoAssociate Director, Environmental Change InstituteUniversity of Oxford

 

Osprey Orielle Lake

Osprey Orielle LakeFounder and Executive DirectorWomen’s Earth and Climate Action Network (WECAN) International

 

Mohamed Adow

Mohamed AdowDirectorPower Shift Africa

 

Valerie Volcovici

Valerie VolcoviciCorrespondentReuters

 MEDIA & FREE SPEECH
6:00pm GMT
The Changing Nature of Philanthropy in the 2020s

 

Darren Walker

Darren WalkerPresidentFord Foundation

 RADICAL REDESIGN
6:30pm GMT
Interview

 

Sundar Pichai

Sundar PichaiChief Executive OfficerGoogle and Alphabet

Day 4: January 14

 POLICY & PROGRESS
5:30am GMT
Interview

Mahathir bin Mohamad served twice as Malaysia’s prime minister, from July 1981 to October 2003 and from May 2018 to March 2020. Forming the new Homeland Fighters Party, Mahathir remains a prominent voice in the Southeast Asian nation’s politics.

 

Mahathir Mohamad

Mahathir MohamadFormer Prime Minister of Malaysia

 POLICY & PROGRESS
6:00am GMT
Interview

 

soon

Speaker TBC

 SUSTAINABLE FUTURE
6:30am GMT
Palm Oil Production in Asia: Looking For a Sustainable Future

Global sales of palm oil, used in everything from cookies to soap, reached $43 billion last year, with Southeast Asia responsible for the bulk of production. The industry has come under fire in recent years, including consumer boycotts, for clearing biodiversity-rich tropical rainforests in the region. Yet it also provides hundreds of thousands of jobs as well as substantial foreign income. The major players, Indonesia and Malaysia, are looking at ways to expand coveted green credentials, even as they push for consumer companies to step up purchases of the more expensive sustainable palm oil.

 

Ravi Muthayah

Ravi MuthayahSecretary-GeneralMalaysia Plantation & Commodities Ministry

 

Olivier Tichit

Olivier TichitLeader of SustainabilityMusim Mas

 

Mohd Haris Mohd Arshad

Mohd Haris Mohd ArshadManaging DirectorSime Darby Oils

 RADICAL REDESIGN
7:10am GMT
Tech Innovation in China

Nowhere else in the world has seen more rapid digitization in the past decade than in China, where technological innovation driven by the private sector has transformed all aspects of society, from the way people socialize to how business is done. The commercial outlook for innovators in China is positive, with a ready market of 1.4 billion people, but any new technological offerings and innovation remain beholden to sudden shifts in the mood in Beijing.

 

Ma Baoli

Ma BaoliFounder, Chairman & Chief Executive OfficerBlueCity

 POLICY & PROGRESS
7:30am GMT
Interview

 

Taro Kono

Taro KonoJapan Minister of State for Special Missions

 RECOVERING GROWTH
9:00am GMT
The business of vaccinating the world against COVID-19

India’s Serum Institute is one of the biggest vaccine makers by volume in the world. CEO Poonawalla’s early bet on the AstraZeneca-University of Oxford COVID-19 vaccine candidate during first phase trials appears to have paid off. The institute plans to prioritize distribution in India before providing doses to the COVAX facility, an international initiative aimed at ensuring almost 100 low and middle income economies have access to a vaccine.

 

Adar Poonawalla

Adar PoonawallaChief Executive OfficerIndia’s Serum Institute

 RECOVERING GROWTH
10:00am GMT
Interview

 

N Chandrasekaran

N ChandrasekaranChairmanTata Group

 RADICAL REDESIGN
10:30am GMT
The Future of Further Education post-Covid

How has Covid changed universities and which changes will stick.

 

Sebastian Thrun

Sebastian ThrunFounder, President & Executive ChairmanUdacity

 

Louise Richardson

Louise RichardsonVice-ChancellorUniversity of Oxford

 SUSTAINABLE FUTURE
11:30am GMT
The Amazon and Business. A Delicate Coexistence

The Amazon rainforest is being destroyed for business but are the two incompatible? Can we save the Amazon and profit from it?

 

João Paulo Ferreira

João Paulo FerreiraChief Executive OfficerNatura & Co Latin America

 RECOVERING GROWTH
12:00pm GMT
Interview

 

Peter Wennink

Peter WenninkPresident & Chief Executive OfficerASML

 RADICAL REDESIGN
1:00pm GMT
Break the Mould: Diversity in Tech and Finance

 

soon

Speaker TBC

 SUSTAINABLE FUTURE
3:00pm GMT
ESG: Should We Really Divest Energy Stocks?

If big investors dump stocks, there may be less accountability. What to do?

 

John Flint

John FlintFormer Group Chief ExecutiveHSBC

 

Adam Matthews

Adam MatthewsDirector of Ethics and EngagementChurch of England Pensions Board

 MEDIA & FREE SPEECH
4:00pm GMT
Interview

 

soon

Speaker TBC

 RADICAL REDESIGN
5:00pm GMT
Diversity in Law

How the US legal profession is pushing greater diversity and where the blockers still are.

 

Justice Goodwin Liu

Justice Goodwin LiuAssociate JusticeCalifornia Supreme Court

 

Anne Robinson

Anne RobinsonManaging Director, General Counsel and Corporate SecretaryVanguard

 

Dev Stahlkopf

Dev StahlkopfCorporate Vice President and General Counsel, Legal AffairsMicrosoft

 RADICAL REDESIGN
5:30pm GMT
Equality in Law and the Push for Diversity

 

Jitse Groen

Jitse GroenChief Executive OfficerJustEat

 

Brian Niccol

Brian NiccolChairman & Chief Executive OfficerChipotle

 RADICAL REDESIGN
6:00pm GMT
The Future of Travel – How Airbnb is Changing Post-COVID

Off the back of its successful IPO, Airbnb’s CEO Brian Chesky shares lessons from the pandemic and how he sees travel returning in 2021.

 

Brian Chesky

Brian CheskyChief Executive OfficerAirbnb

 RECOVERING GROWTH
6:30pm GMT
The Next Frontiers of Venture Capitalism

Interview with Y Combinator on where they are putting their trend-setting bets in 2021.

 

Michael Seibel

Michael SeibelGroup Partner and Managing DirectorY-Combinator

 

Jared Friedman

Jared FriedmanGroup PartnerY-Combinator

 

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Virtual Discover Brigham, November 12, 11AM EST – 3:45PM EST

 

2020 AGENDA

http://www.discoverbrigham.org/

11:00 – 11:45 AM EST

Poster Session & Demos

11:45 AM – 12:15 PM EST

Rock the Mic: Postdoc Fast Pitch

12:30 – 1:05 PM EST

What We Know About COVID-19

1:10 – 1:40 PM EST

Hey Briggie: The Use of Artificial Intelligence to Improve Patient Safety and Experience

1:45 – 2:15 PM EST

Committing to Diversity, Inclusion, and Equity in Clinical Research: The Time is Now

2:25 – 2:55 PM EST

Getting Ahead: Advances in Food and Drug Allergy

3:00 – 3:30 PM EST

What’s Sex Got to Do with It: Risk and Management of Autoimmune Disease

3:35 – 3:45 PM EST

Closing Remarks

“Kicking off with a keynote, the day-long event featured seven interactive demos, eight scientific sessions, 99 poster presentations, 37 speakers and the announcement of the winner of the $100,000 BRIght Futures Prize.”READ MORE

SESSION
SPOTLIGHTS

Read Full Post »


Open Data Science Conference, Virtual and In-Person | October 27th – 30th, 2020, Natural Language Processing Track

Virtual and In-Person | October 27th – 30th, 2020

Natural Language Processing Track

Learn the latest models, advancements, and trends from the top practitioners and researchers behind NLP

Conference Website

AGENDA

https://live.odsc.com/

Thursday – 10/29/2020

09:00 AM – 10:30 AM – ODSC Keynotes

10:30 AM – 5:30 PM – ODSC Hands-on Trainings and Workshops

10:00 AM – 4:30 PM – Partner Demo Talks

10:30 AM – 5:00 PM – Breakout Talk Sessions

09:30 AM – 4:30 PM – Applied AI Free Virtual Event

12:00 PM – 2:00 PM – Woman Ignite Session

1:00 PM – 1:45 PM – Virtual Networking Event

4:00 PM – 5:30 PM         – AI Investors Reverse Pitch

3:30 PM – 4:30 PM – Meet the Expert

 

Friday – 10/30/2020 

09:00 AM – 10:30 AM – ODSC Keynotes

10:30 AM – 5:30 PM – ODSC Hands-on Trainings and Workshops

10:30 AM – 5:00 PM – Breakout Talk Sessions

10:30 AM – 5:00 PM – Career Mentor Talks

11:30 AM – 12:00 PM – Meet the Speaker

4:00 PM – 5:30 PM –  Learning from Failure

Are We Ready for the Era of Analytics Heterogeneity? Maybe… but the Data Says No

 

Wed, October 28, 9:00 AM
(PDT)

Marinela Profi | Global Strategist AI & Model Management | Data Science Evangelist | SAS | WOMEN TECH NETWORK

 

Type: Keynote

 

Session Details & Prerequisites Q&A Slack Channel

Keynote Session – Suchi Saria

 

Wed, October 28, 9:30 AM
(PDT)

Suchi Saria, PhD | Director, Machine Learning & Healthcare Lab | Johns Hopkins University

 

Type: Keynote

 

Q&A Slack Channel

A Secure Collaborative Learning Platform

 

Wed, October 28, 10:00 AM

Raluca Ada Popa, PhD | Assistant Professor | Co-Founder | Berkeley | PreVeil

 

Type: Keynote

 

Session Details & Prerequisites Q&A Slack Channel

OCTOBER 29TH

Data for Good: Ensuring the Responsible Use of Data to Benefit Society

 

Thu, October 29, 9:00 AM
(PDT)

Jeannette M. Wing, PhD | Avanessians Director of the Data Science Institute and Professor of Computer Science | Columbia University

  • Causal INFERENCE Effects – estimate effects
  • Over and under estimation of instrumental variables
  • Confounders: Model assigned causes – Over and under estimation
  • De-Confounder: Estimate substitute confounders – Over and under estimation
  • Convolutional Neuro-networks model
  • Economics: Monopsony, Robo-Advising
  • History: Topic modeling with NLP,
  • Trustworthy Computing vs Trustworthy AI: Safety, Fairness, Robustness
  • Classifiers: Fair/Unfair make then more robust to a class of distributions
  • Image recognition system: DeepXplore: Semantic perturbation
  • DP and ML: PixelDP – STOP sign vs Yield sign
  • HealthCare @Columbia University: 600 Million EHR
  1. The Medical De-confounder: Treatment Effects on A1c DM2

Type: Keynote, Level: All Levels, Focus Area: AI for Good, Machine Learning

Session Details & Prerequisites Q&A Slack Channel

Keynote Session – Ben Taylor

Thu, October 29, 9:30 AM
(PDT)

Ben Taylor, PhD | Chief AI Evangelist | DataRobot

  • Convolution NN – Clustering of Countries: Latin America, Asia
  • Story telling
  • Acceleration:
  1. GPT-3 from OpenAI – Q&A, Translation, grammar
  2. Image GPT
  • Can AI Predict

Type: Keynote, Level: All Levels, Focus Area: Data Science Track

Q&A Slack Channel

Applying AI to Real World Use Cases

Thu, October 29, 10:00 AM
(PDT)

John Montgomery | Corporate Vice President, Program Management, AI Platform | Microsoft

Type: Keynote

  • Machine comprehension
  • Massive ML Models: Vision Model – Reznet
  • Alternative to Azure, OpenAI (Partner of Microsoft) released –>>>>> GPT-3 1758
  • AZURE ML: create models, operationalize models, build models responsibly
  • Model interpretability – Data Science, gov’t regulation: Features importance dashdourd
  • USE CASES
  • Building accurate models
  1. Little Ceasar’s Pizza: “Hot N-Ready” – Demand forecasting of Pizza Supply by combination of ingredients

Predict: X Quantity by Auto ML

  • Deploy and Manage Many Models: MMM Accelerator: Ten Models at AGL – Australia renewal energy

Model for Responsible ML: Fairness & Interpretability

  • EY – Bank denies a LOAN
  • Mitigation of Bias detection for Men and Women in Loan Applications

Loan Approval

  • Explanation dashboard – Aggregate model: Top feature in loan approval: Education Level
  • Fairness – Hazard performance for Accuracy: Disparity in prediction by Gender

ML is part of AZURE Platform

Bonsai – is Reinforcement Learning: Simulation Scenarios

AutoML – do know standard algorithms vs when you do not know

Session Details & Prerequisites Q&A Slack Channel

TALKS on 10/29/2020

NLP

Thu, October 29, 10:30 AM
(PDT)

Join

Tian Zheng, PhD | Chair, Department of Statistics | Associate Director | Columbia University | Data Science Institute

Type: Track Keynote, Level: Intermediate, Focus Area: NLP

  • Stochastic variability inference
  • Case-control likelihood approximation
  • Sampling node system

TEXT

  • LDA – Latent Distribution Modeling Dirichlet

Probability distribution over the vocabulary of words: Topic assignment

LINKS

  • MMSB – Mixed Membership

Detect communities in networks

blockmodel – profile of social interaction in different nodes

  • LMV – Pairwise-Link-LDA – same topic proportions have equal % for citing

Pair-wise-Link-LDA

  1. Draw topic
  2. Draw Beta
  3. For each document
  4. For each document pair

Variational Inference – fully factored model

  • article visibility

Stochastic Variation Inference

  • local (specific to each node) & global (across nodes)
  • At each iteration minibatch of nodes

Sampling Document pairs

  • Stratified sampling scheme – shorter link
  • Informative set sampling [informative vs non-imformative sets]
  • these scheme – Mean estimation problem: Inclusion probability: All links are included
  • Stochastic gradient updates for global parameters
  • Comparison with alternative Approaches
  1. LDA + Regression
  2. Relational topic model
  3. Pairwise-Link-LDA combine LDA and MMB [Same priors]
  • Predictive ranks (random guessing) and Runtimes (compact id distinct no overalp)
  1. evaluate model fit: average predictive rank of held-out documents – Top articles

Cora dataset

LMVS – better predictive performance than

KDD Dataset

Citation trends in HEP: Relevance of Topics vs Visibility

Article recommendation by Rank Topic Proportions

Visibility as a topic-adjusted measure

More recent are more visible

CItation is not a strong indicator for visibility

Visibility as a topic-adjusted measure

Making Deep Learning Efficient

Thu, October 29, 11:20 AM
(PDT)

Join

Kurt Keutzer, PhD | Professor, Co-founder, Investor | UC Berkeley, DeepScale

Type: Track Keynote

  • ML – SubSets
  1. Deep Learning – TRAINING for Clssification – Neuralnets – LeNet vs AlexNet – 7 layers 140x flops – using parallelism
  2. Shallow learning – deterministic and linear classifier used
  3. ML algorithms: Core ML, Audio analysis (Speech and audio recognition) , Multimedia
  4. NLP: translation,
  5. McKinsey & Co. – AI as a Service (AIasS)

PROBLEMS to Solve

Image Classification

  • Object Detection
  • Semantic Segmentation
  • Convolutional NN

Audio Enhancement at BabbleLabs 

Video Sentiment Analysis – Recommendations to Watch or to search

Natural Language Processing & Speech

  • Translation
  • Document understanding
  • Question answering
  • general language understanding evaluation (GLUE)

BerkeleyDeepDrive (BDD)

BERT – Transformer – 7 seconds per sentence

  • BERT-base
  • Q-BERT
  • Transformer

Computational Patterns of Deep NN (DNN) – TRAINING required for DNN

PLATFORMS OF CLOUD

  • GRADIANT DESCENT (GD)
  • Stochastic GRADIANT DESCENT (SGD)

Recommendation Models – DNN – Parallelism

  • Facebook – 80% is recommendation = Advertisement
  • No sharing of data by Collector: Alibaba, Facebook, twitter

 Considerations

  • Latency – NETWORK WIFI
  • Energy
  • Computation power
  • Privacy
  • Quantization: Fewer Memory Accesses
  • Lower Precision implies higher
  • Flat Loss Landscape – Precision Layer by Layer
  • Move computation to the EDGE

 

Language Complexity and Volatility in Financial Markets: Using NLP to Further our Understanding of Information Processing

Thu, October 29, 12:10 PM
(PDT)

Join

Ahmet K. Karagozoglu, Ph.D. | C.V. Starr Distinguished Professor of Finance | Visiting Scholar, Volatility and Risk Institute | Hofstra University | New York University Stern School of Business

Type: Track Keynote, Level: All Levels, Focus Area: NLP

 

Intelligibility Throughout the Machine Learning Life Cycle

Thu, October 29, 2:00 PM
(PDT)

Join

Jenn Wortman Vaughan, PhD | Senior Principal Researcher | Microsoft Research

Type: Talk, Level: Beginner-Intermediate, Focus Area: Machine Learning

  • A Human-centered Agenda for Intelligibility
  • Beyond the model: Data, objectives, performance metrics
  • context of relevant stakeholders
  • Properties of system design vs Properties of Human behavior

Learning with Limited Labels

Thu, October 29, 3:05 PM
(PDT)

Join

Shanghang Zhang, PhD | Postdoc Researcher | University of California, Berkeley

Type: Talk, Level: Intermediate-Advanced, Focus Area: Deep Learning, Research frontiers

 

How AI is Changing the Shopping Experience

Thu, October 29, 3:05 PM
(PDT)

Join

Sveta Kostinsky | Director of Sales Engineering | Samasource
Marcelo Benedetti | Senior Account Executive | Samasource

Type: Talk, Level: Intermediate, Focus Area: Machine Learning, Deep Learning

  • quality rubric
  • Internal QA Sampling
  • Client QA Sampling
  • Auto QA

Transfer Learning in NLP

Thu, October 29, 3:40 PM
(PDT)

00:
03:
30

Joan Xiao, PhD | Principal Data Scientist | Linc Global

Type: Talk, Level: Intermediate, Focus Area: NLP, Deep Learning

Transfer learning enables leveraging knowledge acquired from related data to improve performance on a target task. The advancement of deep learning and large amount of labelled data such as ImageNet has made high performing pre-trained computer vision models possible. Transfer learning, in particular, fine-tuning a pre-trained model on a target task, has been a far more common practice than training from scratch in computer vision.

In NLP, starting from 2018, thanks to the various large language models (ULMFiT, OpenAI GPT, BERT family, etc) pre-trained on large corpus, transfer learning has become a new paradigm and new state of the art results on many NLP tasks have been achieved.

In this session we’ll learn the different types of transfer learning, the architecture of these pre-trained language models, and how different transfer learning techniques can be used to solve various NLP tasks. In addition, we’ll also show a variety of problems that can be solved using these language models and transfer learning.

  •  Transfer learning: Computer Vision – ImageNet Classification
  •  ResNet, GoogleNet, ILSVRC – VGG, ILSVRC’12 – AlexNet
  •   Feature Extrator vs Fine-tune
  •  Transfer learning: NLP
  • Transfer Transformer: Text-to-Text Transfer Transformer 
  1. Word embeddings: No context is taken into account – Word2vec, Glove
  2. ELMo – embedding from language models: Contextual,
  3. BERT – Bi-directional Encoder Representations fro Transformers
  4. MLM – Masked Language Model: Forward, Backward, Masked
  5. Next Sentence Prediction
  6. Achieved SOTA – 11 tasks: GLUE, SQuAD 1.0
  • Predisction models;
  • Input
  • Label – IsNext vs NotNext

 GLUE Test score

BERT BASE vs BERT LARGE

  • Featured-based approach

BERT Variants – TinyBert, Albert, RoBETa, DistilBert

Multi-lingual BERT, BERT other languages

A Primer in BERTology: How BERT Works

 OpenAI built a text generator – too dangerous to release

OpenAI GPT-3 – Trained on 300B tokens – THREE models:

  1. Zero-shot – English to French – no training
  2. one-shots
  3. Few-shot – the GOAL – GPT-3
  4. GRT-3 is large scale NLP

Examples – Feature extraction

  • English to SQL
  • English to CSS
  • English to LaTex

Semantic textual similarity

NL inference 

ULMFiT – Fine tuning – the larger the # of Training examples – the better the performance 

  1. LM pre-training – start from scratch: BART, Big Bird, ELECTRA, Longformer
  2. LM fine-tuning
  3. Classifier fine-tuning

Data augmentation

Contextual Augmentation

  1. Original sentence
  2. masked
  3. augmented

Test generation

  1. boolean questions
  2. from structured data, i.e.,  RDF – Resource Description Framework

OCTOBER 30TH

Generalized Deep Reinforcement Learning for Solving Combinatorial Optimization Problems

 

Fri, October 30, 9:00 AM
(PDT)

Azalia Mirhoseini, PhD | Senior Research Scientist | Google Brain

Type: Keynote

Abstract: 

Many problems in systems and chip design are in the form of combinatorial optimization on graph structured data. In this talk, I will motivate taking a learning based approach to combinatorial optimization problems with a focus on deep reinforcement learning (RL) agents that generalize. I will discuss our work on a new domain-transferable reinforcement learning methodology for optimizing chip placement, a long pole in hardware design. Our approach is capable of learning from past experience and improving over time, resulting in more optimized placements on unseen chip blocks as the RL agent is exposed to a larger volume of data. Our objective is to minimize PPA (power, performance, and area), and we show that, in under 6 hours, our method can generate placements that are superhuman or comparable on modern accelerator chips, whereas existing baselines require human experts in the loop and can take several weeks.

Bio: 

Azalia Mirhoseini is a Senior Research Scientist at Google Brain. She is the co-founder/tech-lead of the Machine Learning for Systems Team in Google Brain where they focus on deep reinforcement learning based approaches to solve problems in computer systems and metal earning. She has a Ph.D. in Electrical and Computer Engineering from Rice University. She has received a number of awards, including the MIT Technology Review 35 under 35 award, the Best Ph.D. Thesis Award at Rice and a Gold Medal in the National Math Olympiad in Iran. Her work has been covered in various media outlets including MIT Technology Review, IEEE Spectrum, and Wired.

Session Details & Prerequisites Q&A Slack Channel
  • Learning Based Approaches vs branch & Bound, Hill climbing, ILP
  • scale on distributed platforms
  • Device Placement – too big to fit – PARTITION among multiple devices – evaluate run time per alternative placements
  • Learn Placement on NMT – Profiling Placement on NMT
  • CPU + layers encoder and decoders – overhead tradeoffs – parallelization for work balancing
  • RL-based placement vs Expert placement
  • Memory copying task
  • Generalization to be achieved forr Device Placement Architecture
  • Embeddings that transfer knowledge across graphs
  • Graph Partitioning: Normalized cuts objective: Volume , Cuts,
  • Learning based approach Train NN on nodes of graph assign Probability of node belonging to a given partition
  • Continuous relaxation of Normalized cuts
  • Optimize expected normalized Cuts
  • Generalized Graph Partitioning Framework
Chip Placement Problem (Floor planning) – Chip Design – resource optimization, canonical reimforcement learning
  • Placement Optimmization using AGENTS to place the nodes
  • Train Policy to be using for placement of ALL chips
  • Compiling a Dataset of Chip Placements
  • Policy/Value Model Architecture to save wire length used
  • RISC-V: Placement Visualization: Training from Scratch (Human) 6-8 weeks vs Pre-Trained 24 hours

Keynote Session – Zoubin Ghahramani

Fri, October 30, 9:30 AM
(PDT)

Zoubin Ghahramani, PhD | Distinguished Scientist and Sr Research Director | Professor of Information Engineering | ex-Chief Scientist and VP of AI | Google | University of Cambridge | Uber

Type: Keynote

Q&A Slack Channel

  • Data- models predictiona decisions Understanding
  • AI & Games
  • AI + ML
  • Deep Learning! (DL)
  1. NN  – tunable nonlinear functions with many parameters
  2. Parameters are weights of NN
  3. Optimization + Statistics
  4. DL – New-branding of NN
  5. Many layers – ReLUs attention
  6. Cloud resources
  7. SW – TensorFloe, JAX
  8. Industry investment in DL

DL – very successful

  • non-parametric statistics
  • use huge data – simulated data
  • automatic differentiation
  • stay close to identity – makes models deeps ReLU, LSTMs GRUs, ResNets
  • Symmentry parameter tieying

Limitations of DL

  • data hungry
  • adversarial examples
  • black-boxes – difficult to trust
  • uncertainty – not easily incorporated

Beyond DL

  • ML as Probabilistic Modeling: Data observed from a system
  • uncertainty
  • inverse probability
  • Bayes rule Priors from measured quantities inference for posterior
  • learning and predicting can be seen as forms of inference – likelihood
  • approximations from estimation of Likelihoods
  1. Learning
  2. Prediction
  3. Model Comparison
  4. Sum rule: Product rule

Why do probabilities matter in AI and DS?

  • COmplexity control and structure learning
  • exploration-exlpoitations trade-offs
  • Building prior knowledge algorithms for small and large data sets
  • BDP – Bayesian DL
  • Gaussian Processes – Linear and logistics regressions SVMs
  • BDL – Baysian NN/ GP Hybrids
  • Deep Sum=Product Networks – deescrimitive programming

Probabilistic Programming Languagues

Languages: Tensors, Turing,

Automatic Statistician –

  • model discovery from data and explain the results

Probabilistic ML

  • Learn from Data  decision theory Prob AI BDL, Prob Prog,

Zoubin Ghahramani, 2015, Probabilistic machine learning and AI, Nature 521; 452-459

 

The Future of Computing is Distributed

Fri, October 30, 10:00 AM

(PDT)
Ion Stoica, PhD | Professor of Computer Science Division | Co-Founder | Berkeley | Anyscale | Databricks | Conviva Networks
  • 1970 – ARPA net 1970 – distributed
  • 1980 – High performance computing – HPC 1980s
  • 1990 – WEB – Amazon
  • 2000 – Big data – Google

Distributed computing – Few courses at universities

  • Rise of deep learning (DL)
  • Application becomes AI centered: Healthcare, FIN, Manufacturing
  • Morse law – is dead: Memory and Processors
  • Specialized hardware: CPU, GPU, TPU
  • Memory dwarfed by demand
  • Memory: Tutring Project 17B
  • GPT-2 8.3B
  • GPT-1
  • Micro-services: Clusters of clouds – integrating with distributed workloads
  • AI is overlapping with HPC
  • AI and Big Data

AI Applications

  • MPI,
  • Stitching several existing systems

RAY riselab @Berkeley – Universal framework for distributed computing (Python and JAVA) across different Libraries

  • Asynchronous execution enable parallelism
  • Function -> Task (API)
  • Object ID – every task scheduled
  • Library Ecosystem – Native Libraries 3rd Party Libraries
  • Amazon and AZURE SPARK, MARS (Tensor)

ADOPTIONS

  • Number of contributors increase fast N=300

 

TALKS on 10/30/2020

 

Advances and Frontiers in Auto AI & Machine Learning – Lisa Amini



Lisa Amini, Director | IBM Research – Cambridge
  • Auto AI – holistic approach
  • Auto ML – Models: Feature creation, modeling, training & testing

AI AUTOmation for Enterprise

  • Feature Preprocessor ->>Feature Transformer Feature selector Estimator
  • Joint-optimization problem
  1. Method selection
  2. Hyper-parameter Optimization
  3. Black-box constraints
  • Bias Mitigation Algorithms
  1. Pre-processing algo
  2. In-processing Algo
  3. Post-processing algo
  • Automation for Data – READINESS for ML
  • relational data –
  • knowledge augmentation
  • Data readiness reporting
  • Labeling Automation: Enhance

Knowledge augmentation – Federated Learning

  • External data sources
  • existing data
  • documents containing domain knowledge
  • Automating Augmenting Data with knowledge: feature-concept mapping

Modeling

  • Time Series Forecasting

AI to decision Optimization

  • Demand forecasting from Standard AutoAI by ADDING Historical Decisions and Historical Business Impact__>> reinforced learning – Automatically created model from past and Auto AI

Validation

  • Meta-learning for performance prediction
  • Train the META data
  • Score production data with AI

Deployment

  • staged deployment with contextual bandits

Monitoring

  • Performance prediction meta model applied over windows of production traffic

INNOVATIONS;

  • End-to-end AI life cycle
  • expanding scope of automation; Domain knowledge and decision optimization

 

The State of Serverless and Applications to AI

 

Fri, October 30, 11:20 AM
(PDT)

Joe Hellerstein, PhD | Chief Strategy Officer, Professor of Computer Science | Trifacta, Berkeley

The Cloud and practical AI have evolved hand-in-hand over the last decade. Looking forward to the next decade, both of these technologies are moving toward increased democratization, enabling the broad majority of developers to gain access to the technology.

Serverless computing is a relatively new abstraction for democratizing the task of programming the cloud at scale. In this talk I will discuss the limitations of first-generation serverless computing from the major cloud vendors, and ongoing research at Berkeley’s RISELab to push forward toward “”””stateful”””” serverless computing. In addition to system infrastructure, I will discuss and demonstrate applications including data science, model serving for machine learning, and cloud-bursted computing for robotics.

Bio: 

Joseph M. Hellerstein is the Jim Gray Professor of Computer Science at the University of California, Berkeley, whose work focuses on data-centric systems and the way they drive computing. He is an ACM Fellow, an Alfred P. Sloan Research Fellow and the recipient of three ACM-SIGMOD “Test of Time” awards for his research. Fortune Magazine has included him in their list of 50 smartest people in technology , and MIT’s Technology Review magazine included his work on their TR10 list of the 10 technologies “most likely to change our world”. Hellerstein is the co-founder and Chief Strategy Officer of Trifacta, a software vendor providing intelligent interactive solutions to the messy problem of wrangling data. He has served on the technical advisory boards of a number of computing and Internet companies including Dell EMC, SurveyMonkey, Captricity, and Datometry, and previously served as the Director of Intel Research, Berkeley.

Type: Talk, Level: Intermediate, Focus Area: AI for Good, Machine Learning

Session Details & Prerequisites Q&A Slack Channel
  • What happened with the Cloud – no app
  • Parallelism – distributed computers – scale up or down, consistency and partial failure
  • Serverless Computing: Functions-as-a-Service (FaaS)
  • Developers OUTSIDE AWS, AZURE< Google to program the CLoud
  • Python for the Cloud
  • AutoScaling – yes
  • Limitations of FaaS: AWS Lambda: I/O Bottlenecks, lifetine 15 min, No Inbound Network COmmunication
  • Program State: local data – managed across invocations
  • Data Gravity – expensive to move

Distributed consistency – data replication: Agree on data  value mutable variable x [undate took place]

  • Two-Phase commit [ Consensus – Paxos]
  • coordination avoidance: waiting for control TALL LATENCY- DISTRIBUTION OF PERFORMANCE
  • Slowdown cascades: I/O
  • Application semantics: Programs requires coordination
  • Program must have property of Monotonic
  • MONOTONICITY: Input grows/output grows – wait on information not on Coordination

CALM – infinitely-scalable systems – no coordination ->> parallelism and smooth scalability

Monotonicity syntactically in a logic language

Hydro: a Platform for Programming the Cloud

Anna Serverless KVS – Hydro Project

  • shared-nothing at all scales (even across Threads)
  • Fast under contention: 90% request handling

Cloudburst: A stateful Serverless Platform: CACHE close to compute: Cache consistency

Latency Python, Cloudburst, AWS, AWS Lambda:

  • AWS Lambda is SLOW for AI vs Python, Cloudburst

Scalable AWS Lambda simultaneously

  • Motion planning compute
  • Cloudburst + Anna requirement

@joe_hellerstein

Bloom Lab

RiseLab

Hydro

 

Just Machine Learning

Fri, October 30, 1:10 PM
(PDT)

Join

Tina Eliassi-Rad, PhD | Professor | Core Faculty | Northeastern University | Network Science Institute

Type: Talk, Level: All Levels, Focus Area: Machine Learning

In 1997, Tom Mitchell defined the well-posed learning problem as follows: “A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.” In this talk, I will discuss current tasks, experiences, and performance measures as they pertain to fairness in machine learning. The most popular task thus far has been risk assessment. We know this task comes with impossibility results (e.g., see Kleinberg et al. 2016, Chouldechova 2016). I will highlight new findings in terms of these impossibility results. In addition, most human decision-makers seem to use risk estimates for efficiency purposes and not to make fairer decisions. I will present an alternative task definition whose goal is to provide more context to the human decision-maker. The problems surrounding experience have received the most attention. Joy Buolamwini (MIT Media Lab) refers to these as the “under-sampled majority” problem. The majority of the population is non-white, non-male; however, white males are overrepresented in the training data. Not being properly represented in the training data comes at a cost to the under-sampled majority when machine learning algorithms are used to aid human decision-makers. In terms of performance measures, a variety of definitions exist from group- to individual- to procedural-fairness. I will discuss our null model for fairness and demonstrate how to use deviations from this null model to measure favoritism and prejudice in the data.

Tasks:

  • Assessing risk
  • Ranking
  • Statistical parity: among classifier

PARITY vs imperfect classifier – can’t satisfy all the three conditions

  • Precision
  • Tru positive
  • False parity

All classifier do not consider context or allow for uncertainty

  • Learning to Place within existing cases
  • Incentives/values of Human decision maker which incorporate in the decision external factors
  • Game-theoretical framework
  • How human exemplars make decision
  • Are algorithms value free?

Computational Ethics

  • Logically consistent principle
  • Camouflage – machine did not learn on the task but on the cloudiness of the sky
  • Model Cards for Model Reporting
  • The “undersampled majority”
  • Experience: Demonstration: Should we learn from demonstrations or from simulations?
  • Complex networks: guilt by association vs privilege and prejudice, individual fairness
  • Datasheets for Datasets
  • Algorithms are like prescription drug: Adverse events

Human vs Machine judgement

  • Performance measure – FAIRNESS: Group, individual
  • Normativity throughout the entire well-posed learning problem
  • Incentive/values
  • Human or machines to make decisions?
  • Laws are needed if algorithms are used as expert witness

 

Machine Learning for Biology and Medicine

Fri, October 30, 2:00 PM

Sriram Sankararaman, PhD | Professor, Computer Science | University of California – Los Angeles

Type: Talk, Focus Area: Machine Learning

Abstract: 

Biology and medicine are deluged with data so that techniques from machine learning and statistics will increasingly play a key role in extracting insights from the vast quantities of data being generated. I will provide an overview of the modeling and inferential challenges that arise in these domains.

In the first part of my talk, I will focus on machine learning problems arising in the field of genomics. The cost of genome sequencing has decreased by over 100,000 fold over the last decade. Availability of genetic variation data from millions of individuals has opened up the possibility of using genetic information to identifying the cause of diseases, developing effective drugs, predicting disease risk and personalizing treatment. While genome-wide association studies offer a powerful paradigm to discovering disease-causing genes, the hidden genetic structure of human populations can confound these studies. I will describe statistical models that can infer this hidden structure and show how these inferences lead to novel insights into the genetic basis of diseases.

In the second part of my talk, I will discuss how the availability of large-scale electronic medical records is opening up the possibility of using machine learning in clinical settings. These electronic medical records are designed to capture a wide range of data associated with a patient including demographic information, laboratory tests, images, medications and clinical notes. Using electronic records from around 60,000 surgeries over five years in the UCLA hospital, I will describe efforts to use machine learning algorithms to predict mortality after surgery. Our results reveal that these algorithms can accurately predict mortality from information available prior to surgery indicating that automated predictive systems have great potential to augment clinical care.

Bio: 

Sriram Sankararaman is an assistant professor in the Departments of Computer Science, Human Genetics, and Computational Medicine at UCLA where he leads the machine learning and genomic lab. His research interests lie at the interface of computer science, statistics and biology and is interested in developing statistical machine learning algorithms to make sense of large-scale biomedical data and in using these tools to understand the interplay between evolution, our genomes and traits. He received a B.Tech. in Computer Science from the Indian Institute of Technology, Madras, a Ph.D. in Computer Science from UC Berkeley and was a post-doctoral fellow in Harvard Medical School before joining UCLA. He is a recipient of the Alfred P. Sloan Foundation fellowship (2017), Okawa Foundation grant (2017), the UCLA Hellman fellowship (2017), the NIH Pathway to Independence Award (2014), a Simons Research fellowship (2014), and a Harvard Science of the Human Past fellowship (2012) as well as the Northrop-Grumman Excellence in Teaching Award at UCLA (2019).

  • ML & BioMedicine

BioMedical data: high D, heterogeneous, noisy data

  1. Clinical Data & DL
  • Predict death after surgery – 1000 dealth complication, sepsis acout kidney injury
  • Mortality during and after surgery
  • collaboration: Anesthesiology, PeriOps, UCLA Health
  • Data warehouse – EMR 4/2013 – 12/2018
  • 60,000 patients in data: Age, height, weight, gender,ASA Status- input from physician

Pre-operative mortality risk prediction – False positive, missing data: Lab data was collected, what were the values

2% of admission associate with mortality

SMOTE: over-sampling of associate with risk

Learning setup: Temporal training-testing split, hyper parameter

Models: Logistics, Random forest, gradient-boosted trees

Feature sets: ASA status, surrugate-ASA

  • ASA Status – did not contribute  with it and without it the same
  • Lab values and timing of lab – is the most important festure.
  • RANDOM FOREST model was selected
  • Precision/recall curve
  • The model reduced number of patients flagged by around 20x

Open problemsL Interoperability, Learning over private data

2. Epidemiological dat and ML – Social distancing in COVID-19 Pandemic

  • Effectiveness of social distancing
  • SEIR
  • Average duration of infection
  • Susceptible-Exposed-Infectious-Removed (SEIR) model
  • R-naught applied to social distancing the ratio of Susceptible /Exposed is compared to Infectious/Removed the lowe the better
  • Social distancing-relaxation – Relaxation in 2022
  • COVID spread – estimate when SOcial distabcing need to END
  • UK, NY, Spain, France, Germany, Denmark
  • Hierarchical Bayesian model: Shared Global parameters, Location-specific, Observations
  • Hierarchical Bayesian model SEIR Model: Data generation process
  • Empirical Bayes: Maximize likelihood of the global parameters
  • Trajectory based on Model Fit
  • Estimation of uncertainty
  • End of Social distancing – time distribution around a mean
  • No seasonality, no infinite immunity, No vaccine
  • Quantify Uncertainty
  • Work with domain knowledge experts is great

The Bayesians are Coming! The Bayesians are Coming, to Time Series – Aric LaBarr


Fri, Oct 30, 2020 5:50 PM – 6:35 PM EDT


Aric LaBarr, Associate Professor of Analytics | Institute for Advanced Analytics at NC State University
With the computational advances over the past few decades, Bayesian analysis approaches are starting to be fully appreciated. Forecasting and time series also have Bayesian approaches and techniques, but most people are unfamiliar with them due to the immense popularity of Exponential Smoothing and autoregressive integrated moving average (ARIMA) classes of models. However, Bayesian modeling and time series analysis have a lot in common! Both are based on using historical information to help inform future modeling and decisions. Using past information is key to any time series analysis because the data typically evolves over time in a correlated way. Bayesian techniques rely on new data updating their models from previous instances for better estimates of posterior distributions. This talk will briefly introduce the differences between classical frequentist approaches of statistics to their Bayesian counterparts as well as the difference between time series data made for forecasting compared to traditional cross-sectional data. From there, it will compare the classical Exponential Smoothing and ARIMA class models of time series to Bayesian models with autoregressive components. Comparing the results of these models across the same data set allows the audience to see the potential benefits and disadvantages of using each of the techniques. This talk aims to allow people to update their own skill set in forecasting with these potentially Bayesian techniques. At the end, the talk explores the technique of model ensembling in a time series context. From these ensembles, the benefits of all types of models are potentially blended together. These models and their respective outputs will be displayed in R
  • Single Exponential Smoothing
  • ARIMA – long-memory models – Autoregressive AR
  • Moving Average (MA) model – short memory
  • Intergrated AR+MA = ARIMA

Learning Intended Reward Functions: Extracting all the Right Information from All the Right Places

Fri, October 30, 3:45 PM

(PDT)

00:04:42
Anca Dragan, PhD | Assistant Professor, EECS | Head | UC Berkeley | InterACT lab

Type: Talk, Focus Area: Deep Learning

Learning Intended Reward Functions: Extracting all the Right Information from All the Right Places

Abstract: 

Content: AI work tends to focus on how to optimize a specified reward function, but rewards that lead to the desired behavior consistently are not so easy to specify. Rather than optimizing specified reward, which is already hard, robots have the much harder job of optimizing intended reward. While the specified reward does not have as much information as we make our robots pretend, the good news is that humans constantly leak information about what the robot should optimize. In this talk, we will explore how to read the right amount of information from different types of human behavior — and even the lack thereof.
Learning outcomes: After participating, you should be able to articulate the common pitfalls we face in defining an AI reward, loos, or objective function. You should also develop a basic understanding of the main algorithmic tools we have for avoiding these pitfalls.

Target audience: Participants with some AI experience, be in supervised or reinforcement learning.

Bio: 

Anca Dragan is an Assistant Professor in EECS at UC Berkeley, where she runs the InterACT lab. Her goal is to enable robots to work with, around, and in support of people. She works on algorithms that enable robots to a) coordinate with people in shared spaces, and b) learn what people want them to do. Anca did her PhD in the Robotics Institute at Carnegie Mellon University on legible motion planning. At Berkeley, she helped found the Berkeley AI Research Lab, is a co-PI for the Center for Human-Compatible AI, and has been honored by the Presidential Early Career Award for Scientists and Engineers (PECASE), the Sloan fellowship, the NSF CAREER award, the Okawa award, MIT’s TR35, and an IJCAI Early Career Spotlight.

  • Sequential decision making
  • defining what robots goal is
  • Autonomous car
  • AI = optimize intended rewards vs specified reward
  • parametrization of the reward function
  • Agent over-learn from specified rewards but under-learn from other sources
  • observing feedback and express the human feedback in observation (human) model
  • How can we model reward design/specification as a noisy and suboptiman process
  • Development vs deployment environment
  • Robot trust the development environment
  • good behavior incentivized reward
  • maximize winning, maximizing score, minimize winning, minimize score
  • model the demo as a reward-rational implicit
  • Human feedback as a reward-rational implicit choice
  • The state of the environment as a reward-rational implicit choice
  • task specification –>> reward

 

KEYNOTE SPEAKERS

ODSC West Keynotes

Suchi Saria, PhD
Suchi Saria, PhD

Director Of The Machine Learning And Healthcare Lab, John C. Malone Endowed Chair, Founder Of Bayesian Health, MIT Technology Review’s 35 Innovators Under 35, And A World Economic Forum Young Global Leader

Johns Hopkins University

Jeannette M. Wing, PhD
Jeannette M. Wing, PhD

Avanessians Director Of The Data Science Institute, Professor Of Computer Science Columbia University, Former Corporate Vice President Microsoft, Former Assistant Director, National Science Foundation

Columbia University

Ion Stoica, PhD
Ion Stoica, PhD

Professor Of Computer Science, Head Of RISELab. Co-Founder Of Anyscale, Databricks, And Conviva Networks, ACM Fellow, SIGOPS Hall Of Fame Award (2015), SIGCOMM Test Of Time Award (2011)

UC Berkeley

Raluca Ada Popa, PhD
Raluca Ada Popa, PhD

Cybersecurity & Applied Cryptography Professor, MIT Technology Review’s 35 Under 35, Recipient Of Intel Early Career Faculty Honor Award, George M. Sprowls Award For Best MIT CS Doctoral Thesis, Co-Founder Of PreVeil

UC Berkeley

Zoubin Ghahramani, PhD
Zoubin Ghahramani, PhD

Chief Scientist, Founding Director Of The AlanTuring Institute, Prof. Of Information Engineering & Deputy Director Of The Leverhulme Centre For The Future Of Intelligence, Fellow Of St John’s College Cambridge And Of The Royal Society

Uber | The University of Cambridge

Azalia Mirhoseini, PhD
Azalia Mirhoseini, PhD

Senior Research Scientist At Google Brain. Advisor At Cmorq. Co-Founder Machine Learning For Systems Moonshot At Brain Focusing On Deep RL. MIT Technology Review 35 Under 35 Award

Google Brain

Marinela Profi
Marinela Profi

Global Strategist For AI, Global Ambassador For The Women Tech Network, Author Of “Mastering Model Lifecycle Orchestration: An Interactive Guide”

SAS

John Montgomery
John Montgomery

Corporate Vice President, Visual Studio, Microsoft Azure AI Lead, Former Chief Information Office At Imagine Publishing, Author At Visual Studio

Microsoft

Ben Taylor,PhD
Ben Taylor,PhD

Chief AI Evangelist, Deep Learning & HPC Expert, Co-Founder & Chief Scientist At Zeff.Ai, Former Chief Scientist At HireVue, ProductCraft Contributor

DataRobot

SCHEDULE

Open Data Science

TUESDAY, OCTOBER 27TH

Pre-conference Day

ODSC BootCamp

BOOTCAMP KICKOFF WEST VIRTUAL
10:00 am

Fundamentals | Morning Sessions

 – 

Choose from 6 foundation sessions in Programming, Mathematics for Data Science, and Statistics

Virtual break

 – 

11:00 am
12:00 pm
1:00 pm
2:00 pm

Fundamentals | Afternoon Sessions

 – 

Choose from 6 foundation sessions in Programming, Mathematics for Data Science, and Statistics

3:00 pm
4:00 pm
5:00 pm

 

Open Data Science

WEDNESDAY, OCTOBER 28TH

Day 1

ODSC Trainings, Workshops & AI Expo, Ai x and Ai x Keynotes

VIRTUAL HANDS-ON TRAINING WEST VIRTUAL VIRTUAL AI X EXPO & DEMO HALL WEST VIRTUAL EVENTS WEST VIRTUAL
10:00 am

Hands-on Training and Workshops

 – 

Choose from Five 3.5 hours Training Sessions and Six 90 minute Workshop Sessions

Networking break

 – 

Morning Partners Demo Talks

 – 

Choose from 12 Partners Sessions

11:00 am

Virtual Exhibitor Showcase

 – 

Visit 30+ Virtual Partners booth

12:00 pm
1:00 pm

Networking break

 – 

2:00 pm

Hands-on Training and Workshops

 – 

Choose from Five 3.5 hours Training Sessions and Six 90 minute Workshop Sessions

Afternoon Partners Demo Talks

 – 

Choose from 12 Partners Sessions

3:00 pm
4:00 pm
5:00 pm

 

Open Data Science

THURSDAY, OCTOBER 29TH

Day 2

ODSC Keynotes, Talks, Trainings, Workshops, AI Expo & Events

VIRTUAL HANDS-ON TRAINING WEST VIRTUAL VIRTUAL AI X EXPO & DEMO HALL WEST VIRTUAL VIRTUAL PRESENTATIONS WEST VIRTUAL
9:00 am

ODSC Keynote

 – 

10:00 am

Morning Hands-on Training and Workshops

 – 

Choose from Five 3.5 hours Training Sessions and Six 90 minute Workshop Sessions

Networking break

 – 

Virtual Exhibitor Showcase & Partners Demo Talks

 – 

Choose from 12 Morning Partners Sessions & Visit 25+ Virtual Partners booth

11:00 am

Breakout Talk Sessions

 – 

Choose from 7 talk presentations

12:00 pm
1:00 pm

Networking break

 – 

2:00 pm

Afternoon Hands-on Training and Workshops

 – 

Choose from Five 3.5 hours Training Sessions and Six 90 minute Workshop Sessions

Virtual Exhibitor Showcase & Partners Demo Talks

 – 

Choose from 12 Afternoon Partners Sessions & Visit 25+ Virtual Partners booth

Breakout Talk Sessions

 – 

Choose from 7 talk presentations

3:00 pm
4:00 pm
5:00 pm

 

Open Data Science

FRIDAY, OCTOBER 30TH

Day 3

ODSC Keynotes, Talks, Trainings, Workshops, Events, & Career Expo

VIRTUAL HANDS-ON TRAINING WEST VIRTUAL VIRTUAL PRESENTATIONS WEST VIRTUAL CAREER LAB AND EXPO & POSTER SESSIONS WEST VIRTUAL
9:00 am

ODSC Keynote

 – 

10:00 am

Morning Hands-on Training and Workshops

 – 

Choose from Five 3.5 hours Training Sessions and Six 90 minute Workshop Sessions

Virtual Lunch & Networking break

 – 

Virtual Career Expo

 – 

Get n touch with 30+ Hiring Partners and choose from 12 Mentor Talks

11:00 am

Breakout Talk Sessions

 – 

Choose from 7 talk presentations

12:00 pm
1:00 pm

Virtual Lunch & Networking break

 – 

2:00 pm

Afternoon Hands-on Training and Workshops

 – 

Choose from Five 3.5 hours Training Sessions and Six 90 minute Workshop Sessions

Breakout Talk Sessions

 – 

Choose from 7 talk presentations

3:00 pm
4:00 pm
5:00 pm

 


SPEAKERS

Click for
more info

Nadja Herger, PhD

DATA SCIENTISTTHOMSON REUTERS

Click for
more info

Viktoriia Samatova

HEAD OF TECHNOLOGY & INNOVATIONTHOMSON REUTERS

Click for
more info

Nina Hristozova

JUNIOR DATA SCIENTISTTHOMSON REUTERS

Click for
more info

Daniel Whitenack, PhD

INSTRUCTOR, DATA SCIENTISTDATA DAN

David Talby: NLP for healthcare
Click for
more info

David Talby, PhD

CTOPACIFIC AI, JOHN SNOW LABS

Click for
more info

Tian Zheng, PhD

CHAIR, DEPARTMENT OF STATISTICSCOLUMBIA UNIVERSITY

Click for
more info

Phoebe Liu

SENIOR DATA SCIENTISTAPPEN

Click for
more info

Frank Zhao

SENIOR DIRECTOR, QUANTAMENTAL RESEARCHS&P GLOBAL MARKET INTELLIGENCE

TOPICS – trends in NLP, including pre-trained models, with use-cases focusing on deep learning, speech-to text, and semantic search.

  • Natural Language Processing
  • NLP Transformers
  • Pre-trained Models
  • Text Analytics
  • Natural Language Understanding
  • Sentiment Analysis
  • Natural Language Generation
  • Speech Recognition
  • Named Entity Extraction

MODELS

  • BERT
  • XLNet
  • GPT-2
  • Transformers
  • Word2Vec
  • Deep Learning Models
  • RNN & LSTM
  • Machine Learning Models
  • ULMFiT
  • Transfer Learning

TOOLS

  • Tensorflow 2.0
  • Hugging Face Transformers
  • PyTorch
  • Theano
  • SpaCy
  • NLTK
  • AllenNLP
  • Stanford CoreNLP
  • Keras
  • FLAIR

Read Full Post »


Tweets & Retweets by @pharma_BI and @AVIVA1950 at #BioIT20, 19th Annual Bio-IT World 2020 Conference, October 6-8, 2020 in Boston

 

Virtual Conference coverage in Real Time: Aviva Lev-Ari, PhD, RN

 

Amazing conference ended at 2PM on October 8, 2020

e-Proceedings 19th Annual Bio-IT World 2020 Conference, October 6-8, 2020 Boston

Virtual Conference coverage in Real Time: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/03/26/19th-annual-bio-it-world-2020-conference-october-6-8-2020-in-boston/

Review Tweets and Retweets

and 2 others liked your Tweet

#BioIT20 Plenary Keynote: cutting innovative approach to #Science #Game On: How #AI, #CitizenScience #HumanComputation are facilitating the next leap forward in #Genomics and in #Biology may be in #PrecisionMedicine in the Future @pharma_BI @AVIVA1950 pic.twitter.com/L52qktkeYc

Retweeted your Tweet
#BioIT20 Plenary Keynote: cutting innovative approach to #Science #Game On: How #AI, #CitizenScience #HumanComputation are facilitating the next leap forward in #Genomics and in #Biology may be in #PrecisionMedicine in the Future @pharma_BI @AVIVA1950 pic.twitter.com/L52qktkeYc

and

liked your Tweet

#BioIT20 Plenary Keynote: cutting innovative approach to #Science #Game On: How #AI, #CitizenScience #HumanComputation are facilitating the next leap forward in #Genomics and in #Biology may be in #PrecisionMedicine in the Future @pharma_BI @AVIVA1950 pic.twitter.com/L52qktkeYc

NIH Office of Data Science Strategy
@NIHDataScience

We’ve made progress with #FAIRData, but we still have a ways to go and our future is bright. #BioIT20 #NIHData

Image

3

Aviva Lev-Ari
@AVIVA1950

#BioIT20

Driving Scientific Discovery with Data Digitization great ideas shared by moderator Timothy Gardner

#CEO Inspiration from History Total Quality Implementation is key for BioScience Data #AI won’t solve the problem #Data #Quality will

Image

Rob Lalonde
@HPC_Cloud_Rob

My #BioIT20 talk, “#Bioinformatics in the #Cloud Age,” is tomorrow at 3:30pm. I discuss cloud migration trends in life sciences and #HPC. Join us! A panel with

and

follows the talk.

1
16

Jean Marois
@JeanMarois

My team is participating in Bio-IT World Virtual 2020, October 6-8. Join me! Use discount code 20NUA to save 20%! invt.io/1tdbae9s8lp

#BioIT20

I’m going to Bio-IT World 2020, Oct 6-8, from home! Its a virtual event. Join me!
My team is participating in Bio-IT World Virtual 2020, October 6-8. Join me! Use discount code 20NUA to save 20%! @bioitworld #BioIT20
invt.io
2

NIH Office of Data Science Strategy
@NIHDataScience

One of the challenges we face today: we need an algorithm that can search across the 36+ PB of Sequence Read Archive (SRA) data now in the cloud. Imagine what we could do! #BioIT20 #NIHdata #SRAdata

Image

2

NCBI Staff
@NCBI

NCBI’s virtual #BioIT20 booth will open in 15 minutes. There, you can watch videos, grab some flyers and even speak with an expert! bio-itworld.pathable.co/organizations/ The booth will close at 4:15 PM, but we’ll be back tomorrow, Oct 7 and Thursday, Oct 8 at 9AM.
Bio-IT World
Welcome to Bio-IT World Virtual
bio-itworld.pathable.co
1
6
Show this thread

PERCAYAI
@percayai

Happening soon at #BioIT20: Join our faculty inventor Professor Rich Head’s invited talk “CompBio: An Augmented Intelligence System for Comprehensive Interpretation of Biological Data.”
4

Wendy Anne Warr
@WendyAnneWarr

This was a good discussion
Quote Tweet
Cambridge Innovation
@CIInstitute
·
RT percayai: We’ve put together what’s sure to be a thought-provoking discussion group for #BioIT20 “Why Current Approaches Using #AI in #…
1
2

Cambridge Innovation
@CIInstitute

RT VishakhaSharma_: Excited to speak and moderate a panel on Emerging #AI technologies bioitworld #BioIT20
1

Titian Software
@TitianSoftware

Meet Titian at #BioIT20 on 6-8th October and discover the latest research, science and solutions for exploring the world of precision medicine and the technologies that are powering it: bit.ly/2GjCj4B

Image

1

PERCAYAI
@percayai

Thanks for joining us, Wendy! You’ve done a great job summing up key points from the discussion. #BioIT20
1

Aviva Lev-Ari
@AVIVA1950

#NIHhealthInitiative #BioItWorld20

Out standing Plenary Keynote on #DataScience

CONNECTED DATA ECOSYSTEM FAIR Foundable, Accessible, Interoperable, reusable

Image

2

Read Full Post »


Tweet Collection by @pharma_BI and @AVIVA1950 and Re-Tweets for e-Proceedings 14th Annual BioPharma &amp; Healthcare Summit, Friday, September 4, 2020, 8 AM EST to 3-30 PM EST – Virtual Edition

Real Time Press Coverage: Aviva Lev-Ari, PhD, RN

 

e-Proceedings 14th Annual BioPharma & Healthcare Summit, Friday, September 4, 2020, 8 AM EST to 3-30 PM EST – Virtual Edition

Real Time Press Coverage: Aviva Lev-Ari, PhD, RN

Founder & Director, LPBI Group

https://pharmaceuticalintelligence.com/2020/07/28/14th-annual-biopharma-healthcare-summit-friday-september-4-2020-8-am-est-to-3-30-pm-est-virtual-edition/

 

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Hal Barron, Chief Scientific Officer and President R&D, GlaxoSmithKline GWAS not easy to find which gene drives the association  Functional Genomics gene by gene with phenotypes using machine learning significant help

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Hal Barron, Chief Scientific Officer and President R&D, GSK GWAS not easy to find which gene drives the association  Functional Genomics gene by gene with phenotypes using machine learning significant help

Srihari Gopal
@sgopal2

Enjoyed hearing enthusiasm for Neuroscience R&D by Roy Vagelos at #USAIC20. Wonderful interview by Mathai Mammen

Image

1
2
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Aviva Lev-Ari
@AVIVA1950

#USAIC20 Nina Kjellson, General Partner, Canaan Data science is a winner in Healthcare Women – Data Science is an excellent match

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Arpa Garay, President, Global Pharmaceuticals, Commercial Analytics, Merck & Co. Data on Patients and identification who will benefit fro which therapy  cultural bias risk aversion

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Najat Khan, Chief Operating Officer, Janssen R&D Data Sciences, Johnson & Johnson Data Validation  Deployment of algorithms embed data by type early on in the crisis to understand the disease

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Sastry Chilukuri, President, Acorn AI- Medidata Opportunities in Data Science in Paharma COVID-19 and Data Science

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Maya Said, Chief Executive Officer, Outcomes4Me Cancer patients taking change of their care Digital Health – consumerization of Health, patient demand to be part of the decision, part the information FDA launched a Program Project Patient Voice

USAIC
@USAIC

We’re taking a quick break at #USAIC20 before our next panel on rare diseases starts at 12:20pm EDT. USAIC would like to thank our Sponsors and Partners for supporting this year’s digital event.

Image

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Roy Vagelos, Chairman of the Board, Regeneron HIV-AIDS: reverse transcriptase converted a lethal disease to a chronic disease, tried hard to make vaccine – the science was not there

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Roy Vagelos, Chairman of the Board, Regeneron Pharmaceuticals Congratulates Big Pharma for taking the challenge on COVID-19 Vaccine, Antibody and anti-viral Government funding Merck was independent from Government – to be able to set the price

1

Dr Kapil Khambholja
@kapilmk

Christopher Viehbacher, Gurnet Point Capital touches very sensitive topic at #USAIC20 He claims that we are never going to have real innovation out of big pharma! Well this isn’t new but not entirely true either… any more thoughts?
1
1
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Aviva Lev-Ari
@AVIVA1950

#USAIC20 Daphne Zohar, Founder & CEO, PureTech Health Disease focus, best science is the decision factors

1

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Christopher Viehbacher, Managing Partner, Gurnet Point Capital Dream of every Biotech – get Big Pharma coming to acquire and pay a lot Morph and adapt

anju ghangurde
@scripanjug

Biogen’s chair Papadopoulos big co mergers is an attempt to solve problems; typically driven by patent expirations.. #usaic20

2

anju ghangurde
@scripanjug

Chris Viehbacher/Gurnet Point Capital on US election: industry will work with whoever wins; we’ll have to ‘morph & adapt’ #usaic20

1

Dr Kapil Khambholja
@kapilmk

of

talks about various philosophies and key reasons why certain projects/molecules are killed early. My counter questions- What are chances of losing hope little early? Do small #biopharma publish negative results to aid to the knowledge pool? #USAIC20

Image

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Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Laurie Glimcher, President & CEO, Dana-Farber Cancer Institute DNA repair and epignetics are the future of medicine

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Laurie Glimcher, President & CEO, Dana-Farber Cancer Institute COlonorectal cancer is increasing immuno therapy 5 drugs marketed 30% cancer patients are treated early detection key vs metastatic 10% of cancer are inherited treatment early

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Rehan Verjee, President, EMD Serono Charities funding cancer research – were impacted and resources will come later and in decreased amount New opportunities support access to Medicine improve investment across the board

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Philip Larsen, Global Head of Research, Bayer AG Repurposing drugs as antiviral from drug screening innovating methods Cytokine storm in OCVID-19 – kinase inhibitors may be antiviral data of tested positive allows research of pathway in new ways

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Laurie Glimcher, President & CEO, Dana-Farber 3,000 Telemedicine session in the first week of the Pandemic vs 300 before – patient come back visits patient happy with Telemedicine team virtually need be reimbursed same rate working remotely

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Raju Kucherlapati, Professor of Genetics, Harvard Medical School New normal as a result of the pandemic role of personalized medicine

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Rehan Verjee, President, EMD Serono entire volume of clinical trials at Roche went down same at EMD delay of 6 month, some were to be initiated but was put on hold Charities funding cancer research were impacted and resources will come later smaller

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Laurie Glimcher, President & CEO, Dana-Farber Cancer Institute Dana Farber saw impact of COVID-19 on immunosuppressed patients coming in for Cancer Tx – switch from IV Tx to Oral 96% decrease in screenings due to Pandemic – increase with Cancer

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Kenneth Frazier, Chairman of the Board and Chief Executive Officer, Merck & Co. Pharma’s obligation for next generations requires investment in R&D vs Politicians running for 4 years Patients must come first vs shareholders vs R&D investment in 2011

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Kenneth Frazier, Chairman of the Board and Chief Executive Officer, Merck & Co. Antibiotic research at Merck – no market incentives on pricing for Merck to invest in antibiotics people will die from bacterial resistance next pandemic be bacterial

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Kenneth Frazier, Chairman of the Board and Chief Executive Officer, Merck & Co. Strategies of Merck = “Medicine is for the People not for Profit” – Ketruda in India is not reembureable in India and million are in need it Partnership are encouraged

Dr Kapil Khambholja
@kapilmk

Chairman Stelios Papadopoulos asks #KennethFrazier if wealthy nations will try to secure large proportion of #COVID19 drugs/vaccines. #KennethFrazie rightly mentions: pharma industry’s responsibility to balance the access to diff countries during pandemic. #USAIC20

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Dr Kapil Khambholja
@kapilmk

Almost 60% participants at #USAIC20 feel that MNCs are more likely to run their #clinicalTrials in #INDIA seeing changing environment here, reveals the poll. Exciting time ahead for scientific fraternity as this can substantially increase the speed of #DrugDevelopment globally

Clapping hands sign

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Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Barry Bloom, Professor & former Dean, Harvard School of Public Health Vaccine in clinical trials, public need to return for 2nd shot, hesitancy Who will get the Vaccine first in the US  most vulnerable of those causing transmission Pharma’s risk

4

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr. Barry Bloom, Professor & former Dean, Harvard School of Public Health Testing – PCR expensive does not enable quick testing is expensive result come transmission occurred Antibody testing CRISPR test based Vaccine in clinical trials

1

Aviva Lev-Ari
@AVIVA1950

#USAIC20 Dr Andrew Plump, President of R&D, Takeda Pharmaceuticals COllaboration effort around the Globe in the Pandemic therapy solutions including Vaccines

Read Full Post »


Tweets by @pharma_BI and @AVIVA1950 @ 2020 State of Possible Conference, MassBio’s VIRTUAL Annual Meeting, August 26 – 27, 2020

Real Time press coverage: Aviva Lev-Ari, PhD, RN

 

2020 State of Possible Conference, MassBio’s VIRTUAL Annual Meeting, August 26 – 27, 2020

Real Time press coverage: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/02/21/2020-state-of-possible-conference-massbios-annual-meeting-march-25-26-2020-sonesta-hotel-cambridge-ma/

 

Aviva Lev-Ari
@AVIVA1950

2020 State of Possible Conference, MassBio’s VIRTUAL Annual Meeting, August 26 – 27, 2020
2020 State of Possible Conference, MassBio’s VIRTUAL Annual Meeting, August 26 – 27, 2020 Leaders in Pharmaceutical Business Intelligence (LPBI) Group will cover this event in REAL TIME…
pharmaceuticalintelligence.com
2

Aviva Lev-Ari
@AVIVA1950

Thomas McCourt President Ironwood Pharmaceuticals, Inc. Clinical trials many are STUCK – solve problems calls for adoption of all companies to digital platforms Entrepreneurial spirit in Kendall square took away the prime position of CA Biotech

Aviva Lev-Ari
@AVIVA1950

Thomas McCourt President Ironwood Pharmaceuticals, Inc. GI disease in Patients – My Gi Health started in NIH – symptoms of GI diseases GI entrepreneurs to build a smart e-Tool to analyze the GI Symptoms  few thousand Patients

Aviva Lev-Ari
@AVIVA1950

Nick Dougherty Managing Director MassChallenge HealthTech Around the World communities, MA Biotech infrastructure  MassChallenge HealthTech: In Mexico, in Israel in Switzerland Becoming virtual instantly in MARCH 2020 More locations pick up scale up

1

Aviva Lev-Ari
@AVIVA1950

Naomi Fried Founder CEO Health Innovation Strategies MA best Hospitals: MGH-BWH, Beth Israel-Lahey Clinic, Stuart BC/BS Medical Schools Clusters in Biotech & Digital Health Counsel  Definition of Community changed in the COVID-19 Era

Aviva Lev-Ari
@AVIVA1950

Stephen Bernstein McDermott Will & Emery LLP Virtual Bench science Life sciences Products; Deploying a compound, provider responsible for the cost or how the Reimbursement will work Consumer & Patients: Specialty Pharmacy  collaborations by planning

Aviva Lev-Ari
@AVIVA1950

Stephen Bernstein McDermott Will & Emery LLP Webinars and Zooms allows communication we will see more innovations – Flatten the World Greater isolation US is expected to lead collaborate is NOW home based no travel creative  Virtual Clinical Trials

Aviva Lev-Ari
@AVIVA1950

Renée Deehan-Kenney PhD, VP, QuartzBio Precision Medicine Group Network biology modeling – helps inform chemistry models: Cell line in Mice translation to Human in pancreatic cancer cell line  Pessimistic view: Long way to go end point most time

Aviva Lev-Ari
@AVIVA1950

Rachel Hodos Senior AI Scientist BenevolentAI Panelist Pick Targets AI is a Possible dream trusted a drug in human

Aviva Lev-Ari
@AVIVA1950

Nora Khaldi Founder and CSO Nuritas AI biological data is early while relying on that knowledge identify drug safe for human is possible I believe AI – take a molecule to humans 99% working in humans AI teated and validated in vitro

Aviva Lev-Ari
@AVIVA1950

Juan Alvarez AVP, Merck High dimensional spaces sample comparison Find therapies for Humans in the absence of having Humans participating, data on human is BIASED by drugs history Drugable identify interventions translatable to Humans pathway-based

Aviva Lev-Ari
@AVIVA1950

Renée Deehan-Kenney PhD, VP, QuartzBio, Precision Medicine Group Chemistry in developing drugs is complex Network biology modeling – helps inform chemistry models: Cell line in Mice translation to Human in pancreatic cancer cell line

Aviva Lev-Ari
@AVIVA1950

Renée Deehan-Kenney PhD, VP, QuartzBio Precision Medicine Group technology enable company clinical data analysis of data clinical trials ML prior knowledge network biology drive inside MOA prioritize indications Chemistry in developing drugs complex

Aviva Lev-Ari
@AVIVA1950

Juan Alvarez AVP, Computational and Structural Chemistry Merck metabolomics evolving proteins analyzing data access to compute power data acquisition and storage – High dimensional spaces sample comparison

1

Aviva Lev-Ari
@AVIVA1950

Juan Alvarez AVP, Computational and Structural Chemistry Merck Drug Target identification Drug Discovery – ML since 1980s Identify molecules syntesis prediction physico space – physiological systems Transcriptomics, single cell biomarkers proteomics

Aviva Lev-Ari
@AVIVA1950

Renée Deehan-Kenney PhD, VP, QuartzBio Precision Medicine Group Network biology modeling – helps inform chemistry models: Cell line in Mice translation to Human in pancreatic cancer cell line  Pessimistic view: Long way to go end point most time

Aviva Lev-Ari
@AVIVA1950

Rachel Hodos Senior AI Scientist BenevolentAI Panelist Pick Targets AI is a Possible dream trusted a drug in human

Aviva Lev-Ari
@AVIVA1950

Nora Khaldi Founder and CSO Nuritas AI biological data is early while relying on that knowledge identify drug safe for human is possible I believe AI – take a molecule to humans 99% working in humans AI teated and validated in vitro

Aviva Lev-Ari
@AVIVA1950

Thomas McCourt President Ironwood Pharmaceuticals, Inc. Clinical trials many are STUCK – solve problems calls for adoption of all companies to digital platforms Entrepreneurial spirit in Kendall square took away the prime position of CA Biotech

Aviva Lev-Ari
@AVIVA1950

Thomas McCourt President Ironwood Pharmaceuticals, Inc. GI disease in Patients – My Gi Health started in NIH – symptoms of GI diseases GI entrepreneurs to build a smart e-Tool to analyze the GI Symptoms  few thousand Patients

Aviva Lev-Ari
@AVIVA1950

Nick Dougherty Managing Director MassChallenge HealthTech Around the World communities, MA Biotech infrastructure  MassChallenge HealthTech: In Mexico, in Israel in Switzerland Becoming virtual instantly in MARCH 2020 More locations pick up scale up

1

Aviva Lev-Ari
@AVIVA1950

Naomi Fried Founder CEO Health Innovation Strategies MA best Hospitals: MGH-BWH, Beth Israel-Lahey Clinic, Stuart BC/BS Medical Schools Clusters in Biotech & Digital Health Counsel  Definition of Community changed in the COVID-19 Era

Aviva Lev-Ari
@AVIVA1950

Stephen Bernstein McDermott Will & Emery LLP Virtual Bench science Life sciences Products; Deploying a compound, provider responsible for the cost or how the Reimbursement will work Consumer & Patients: Specialty Pharmacy  collaborations by planning

Aviva Lev-Ari
@AVIVA1950

Stephen Bernstein McDermott Will & Emery LLP Webinars and Zooms allows communication we will see more innovations – Flatten the World Greater isolation US is expected to lead collaborate is NOW home based no travel creative  Virtual Clinical Trials

Aviva Lev-Ari
@AVIVA1950

Kenneth Anderson Director, Multiple Myeloma Center Dana-Farber Cancer Institute Hematologic Division – African Americans  Change paradigm of clinical trials Geraldine Feraro was patient at DFCI Tom Bracow patient at DFCI  STEM for girls 6-12 grades

Aviva Lev-Ari
@AVIVA1950

Kenneth Anderson Director, Multiple Myeloma Center Dana-Farber Cancer Institute Multiple Myeloma – 23 drugs approved by FDA Dana-Farber Cancer Institute with Sanofi collaboration Foundations stepped forward to study Multiple Myeloma FDA motivated

Aviva Lev-Ari
@AVIVA1950

Juan Alvarez AVP, Merck High dimensional spaces sample comparison Find therapies for Humans in the absence of having Humans participating, data on human is BIASED by drugs history Drugable identify interventions translatable to Humans pathway-based

Aviva Lev-Ari
@AVIVA1950

Renée Deehan-Kenney PhD, VP, QuartzBio, Precision Medicine Group Chemistry in developing drugs is complex Network biology modeling – helps inform chemistry models: Cell line in Mice translation to Human in pancreatic cancer cell line

Aviva Lev-Ari
@AVIVA1950

Renée Deehan-Kenney PhD, VP, QuartzBio Precision Medicine Group technology enable company clinical data analysis of data clinical trials ML prior knowledge network biology drive inside MOA prioritize indications Chemistry in developing drugs complex

Aviva Lev-Ari
@AVIVA1950

Juan Alvarez AVP, Computational and Structural Chemistry Merck metabolomics evolving proteins analyzing data access to compute power data acquisition and storage – High dimensional spaces sample comparison

1

Aviva Lev-Ari
@AVIVA1950

Juan Alvarez AVP, Computational and Structural Chemistry Merck Drug Target identification Drug Discovery – ML since 1980s Identify molecules syntesis prediction physico space – physiological systems Transcriptomics, single cell biomarkers proteomics

Read Full Post »


14th Annual BioPharma & Healthcare Summit, Friday, September 4, 2020, 8 AM EST to 3-30 PM EST – Virtual Edition

Real Time Press Coverage: Aviva Lev-Ari, PhD, RN

Founder & Director, LPBI Group

 

Tweet Collection by @pharma_BI and @AVIVA1950 and Re-Tweets for e-Proceedings 14th Annual BioPharma &amp; Healthcare Summit, Friday, September 4, 2020, 8 AM EST to 3-30 PM EST – Virtual Edition

Real Time Press Coverage: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/09/04/tweet-collection-by-pharma_bi-and-aviva1950-and-re-tweets-for-e-proceedings-14th-annual-biopharma-healthcare-summit-friday-september-4-2020-8-am-est-to-3-30-pm-est-virtual-editio/

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