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Leaders in Pharmaceutical Business Intelligence (LPBI) Group

Funding, Deals & Partnerships: BIOLOGICS & MEDICAL DEVICES; BioMed e-Series; Medicine and Life Sciences Scientific Journal – http://PharmaceuticalIntelligence.com

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Yash Choudhary, Research Assistant 3

Roles @ LPBI

Implement Wolfram NLP on 13 articles in Cardiovascular disease the Role of Calcium in Cardiac Function. Completion of Proof-of-Concept

Areas of Interest and Selection of Research Categories

1. Artificial Intelligence Applications in Health Care

2. Artificial Intelligence in Medicine – Application for Diagnosis

3. Deep Learning in Pathology

4. Machine Learning

5. Machine learning in predicting type 2 diabetes

6. Drug Discovery Chemistry

7. Artificial intelligence applications for cardiology

8. Scientific Publishing

9. big data analytics

10. data science

11. Natural Language Processing (NLP)

12. vision

Yash Choudhary


+91 7354490145 | yashch664422@gmail.com | linkedin.com/in/yash | github.com/yash


Education

Indian Institute of  Technology Kanpur                                                                         Kanpur (U.P.), India

Bachelor of Technology in Material Science and Engineering,    

Aug. 2019 – May 2023 (expected)

Sardana public school.                                                                                                        Dewas (M.P.), India

Higher Secondary                                                                                                              

May. 2016 – March 2018


Projects

Neuromatch Academy Summer School 2020 | Human Connectome Project dataset.                             May 2020

  • Worked in a team of 3, Hypothesize that brain activity during different language task (Story comprehension and arithmetic calculation) has distinct differentiating characteristics.
  • Verified our hypothesis by using popular machine learning techniques to classify fMRI data into two categories .
  • Used t-SNE and PCA for dimensionality reduction.
  • Compared accuracy for 3 different models:- Linear regression , Linear discrimination analysis and Linear support vector classifier and achieved accuracy of 90%.
  • Analyzed the weights of successful models to understand these characteristic differences.


Relevant courses

MTH101 (Real Analysis and multivariable calculus).              MTH 102 (Linear algebra and Differential equation).

ESC101 (Fundamentals of C programming).                                              MSO203  (Partial differential equations).

ESC101 (Fundamentals of C programming).                                              MSO203  (Partial differential equations).

PHY102 (Mechanics).                                                                                               PHY103 (Electrodynamics).

ESC101 (Fundamentals of C programming).                                             MSO203  (Partial differential equations).


Technical Skills

Machine learning (basics).Deep learning (basics).PythonC language
C++HTMLCSSAutoCAD
NumpyPandasScikit-learn 


Interests

1) Deep learning in NLP and CV.

2) Bayesian Methods for probabilistic inference.

3) Competitive programming.

4) Neuroscience.

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