Satyaki Mukherjee

Satyaki Mukherjee Sat-toki Moo-kher-jee

Researcher in Theory of AI

National University of Singapore

Biography

Satyaki Mukherjee is currently a postdoctoral researcher in the theory of machine learning. He is interested in a variety of problems involving some mix of probability, statistics, computer science, graph theory and combinatorics.

Interests
  • Statistical theory of Machine Learning.
  • Autoencoders, Projection pursuit and unsupervised compression theories.
  • Computational Linear Algebra.
Education
  • PhD in Mathematics, 2021

    University of California, Berkeley

  • Masters in Mathematics, 2015

    Indian Statistical Institute

  • Bachelors in Mathematics, 2013

    Indian Statistical Institute

Skills

Technical
Probability
Learning Theory
Python
Hobbies
Systems Theory
Video Games and Media
Cooking

Experience

 
 
 
 
 
Research fellow at NUS
June 2024 – Present Singapore
Researching in the Probability and Statistics.
 
 
 
 
 
Postdoctoral Researcher in TFAI
January 2022 – December 2023 Munich
Researching in the theory of Artificial Intelligence. Taught Seminar and practical courses on emerging trends and reproducibility in Machine Learning.
 
 
 
 
 
Graduate Student Instructor/Researcher
August 2015 – May 2021 California
Taught Linear Algebra, Discrete Mathematics etc. Researched in Spectral Graph Theory.

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