Aniket Das | Stanford University

About Me

Hi! I’m a first year CS PhD student in the Theory Group at Stanford, where I’m advised by the spectacular duo of Nima Anari and Tselil Schramm.

My interests broadly lie at the intersection of probability and theoretical computer science. Less broadly, I like thinking about Markov Chains, the complexity of statistical inference, and algorithmic applications of Wasserstein Gradient Flows. Feel free to reach out if we share similar interests!

Prior to grad school, I was a Pre-Doctoral Researcher at Google DeepMind India. Even earlier, I was a dazed and confused undergrad at Indian Institute of Technology Kanpur, where I double majored in Electrical Engineering and Math.

Selected Publications

Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD
with Dheeraj Nagaraj, Soumyabrata Pal, Arun Suggala and Prateek Varshney
NeurIPS 2024 [Paper]
Provably Fast Finite-Particle Variants of SVGD via Virtual Particle Stochastic Approximation
with Dheeraj Nagaraj
Spotlight at NeurIPS 2023 [Paper]
Oral Presentation at OTML Workshop, NeurIPS 2023
Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms
with Dheeraj Nagaraj and Anant Raj
COLT 2023 [Paper]
Near Optimal Heteroscedastic Regression with Symbiotic Learning
with Dheeraj Baby, Dheeraj Nagaraj and Praneeth Netrapalli
COLT 2023 [Paper]
Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization
with Bernhard Schölkopf and Michael Muehlebach
NeurIPS 2022 [Paper]

Talks

Linear Time Streaming Algorithms for Heavy Tailed Statistics
MSR IISc Theory Seminar 2024 Slides
Sampling Through the Lens of Optimization : Recent Advances and Insights
MSR IISc Theory Seminar 2023, EPFL FLAIR Seminar 2024 Slides

Service

Reviewer : NeurIPS, ICML, AISTATS
Co-ordinator : Special Interest Group in Machine Learning, IIT Kanpur
Undergrad Mentor : Programming Club, IIT Kanpur and Stamatics (Math Club), IIT Kanpur