Deepak Narayanan Sridharan

About

I am a PhD student at ETH Zurich, advised by David Steurer. My research lies at the intersection of theoretical computer science and statistics. I am currently working on robust and private statistical estimation.

Papers

On efficient robust regression with subquadratic samples with Deeksha Adil, Jarosław Błasiok, and Hongjie Chen COLT 2026 • arXiv • PMLR
Fast algorithms for learning a Gaussian under halfspace truncation with optimal sample complexity with Haitong Liu, David Steurer, and Manuel Wiedmer COLT 2026 • arXiv • PMLR
Outlier-robust Mean Estimation near the Breakdown Point via Sum-of-Squares with Hongjie Chen and David Steurer SODA 2025 • arXiv • SIAM • Thesis
Awarded ETH Medal for Outstanding Master's Thesis
IGLU: Efficient GCN Training via Lazy Updates with Aditya Sinha, Prateek Jain, Purushottam Kar, and Sundararajan Sellamanickam ICLR 2022 • arXiv • OpenReview

Undergraduate work

A Toolkit for Spatial Interpolation and Sensor Placement with Zeel B. Patel, Apoorv Agnihotri, and Nipun Batra SenSys 2020 poster • ACM
[Re] One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers with Varun Gohil and Atishay Jain ReScience C 2020 • ReScience C • OpenReview
Active Learning for Air Quality Station Location Recommendation with Apoorv Agnihotri and Nipun Batra CoDS-COMAD 2020 • ACM

Teaching

Served as TA for the following courses at ETH Zurich.

Algorithms and Probability (S25, S26)
Algorithms and Data Structures (F24, F25)
Algorithmic Foundations of Data Science (S23, S24)
Deep Learning (F23)
Computational Intelligence Lab (S23)