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
Researching in the Probability and Statistics.
Postdoctoral Researcher in TFAI
Researching in the theory of Artificial Intelligence. Taught Seminar and practical courses on emerging trends and reproducibility in Machine Learning.
Graduate Student Instructor/Researcher
Taught Linear Algebra, Discrete Mathematics etc. Researched in Spectral Graph Theory.
About
Lecture Notes
Geometry of Polynomials
Blog
Selected posts
Contact
- satyaki.mukhyo@gmail.com
- +65 8160 6684
- 1A Lutheran, Singapore, Singapore 267745