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Hi, I'm Progyan!

I’m intrigued by Theoretical Deep Learning, Probabilistic Machine Learning and Differential Equations (especially in Operator Learning). My research is aligned along those fields.

Over the past four years, I’ve been lucky to be a part of the Google Summer of Code, I’ve been awarded the Cargill Global Scholarship, and I spent a wonderful summer in sunny California as a Caltech SURF fellow in the summer of 2023, where I worked with JPL, NASA on Machine Learning for (literally) astronomically large datasets. Interspersed between these were fortunate opportunities to work on research problems with scientists from DRDO, ISRO, TCS Research, as well as a wonderful winter at Bangalore as a Quantitative Researcher at Mudrex Capital.

In 2024, I will be interning with MIT CSAIL as part of their SGI programme, in problems related to Computational Geometry. I’ve also collaborated with University of Maryland on mathematical questions that arise in Kernel-based Learning. After that, I’m headed to Microsoft Bing, Bangalore as an Applied Scientist!

As a sidequest, I’ve also led a team of 120 students for a year and brought my institute’s cultural fest back offline in 2021, coordinated 400+ internships across 50+ companies with the Industrial Relations Cell at IIT Gandhinagar, and was elected as the institute’s Technical Secretary, where I had the great fortune of leading an incredible team of smart and driven individuals to bring positive, driven change in how students approached technology at IIT Gandhinagar. Check out the MetaIITGN Initiative to check out some of our work!

I was brought up in a family of theatre artistes, in quaint and beautiful Agartala, Tripura, where my interests ranged from good literature (from Tagore to Dostoevsky), to great music (from Vivaldi to Dhanji!) I also enjoy good beer, and the occasional whiskey, so hit me up if you’re in Bangalore and in the mood to hit a pub!

Progyan's Projects

arrgh icon arrgh

A small python utility to pretty-print a table summarizing arrays & scalars from numpy, pytorch, etc.

bishop icon bishop

Bishop is a work-in-progress neural operator library in C++.

black-scholes icon black-scholes

Part of the MA 201 project on the Black-Scholes equation, by Progyan Das, Vedang Chavan, Rahul Chembakasseril, Yash Kokane, and Shaandili Vajpai

cerebruh icon cerebruh

A Windows-based python application aimed at putting Wikipedia at the tip of your finger. One finger.

codemixedtexttoolkit icon codemixedtexttoolkit

Constructing an open-source library like NLTK and spaCy for efficient processing of code-mixed text, models, and datasets under Prof. Mayank Singh.

coinframe icon coinframe

Library for analysing, backtesting, and presenting cryptocurrency portfolios reliably, and with very little code.

commentator icon commentator

A code-mixed annotation tool aimed at increasing the annotation quality whilst reducing the annotation time and various overheads associated with code-mixed data.

competitivecoding icon competitivecoding

My first foray into competitive coding. The commit structure journals my daily improvement!

cs229 icon cs229

Assignments done as part of auditing the CS229 course offered by Stanford in 2018, by Professor Andrew Ng. An abridged version of the course is available on Coursera.

gossip icon gossip

Gossip is a beautiful tree-walk interpreter (that now also supports bytecode!) that allows for beautiful visualizations for abstract syntax trees, and is built to support beginners starting a course on Compiler Design.

gp-zoo icon gp-zoo

A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably including Stochastic Variational Gaussian Processes.

gpjax icon gpjax

A didactic Gaussian process package for researchers in Jax.

insiit icon insiit

Official Students App for IITGN!

learn-z3 icon learn-z3

Some challenge solutions solved using z3

life_code icon life_code

A simple program to simulate attraction/reuplsion forces between many particles

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