About Me
I am a faculty member at the Kahlert School of Computing at the University of Utah. I am also part of the Theory Group, and the Utah Center for Data Science. Prior to Utah, I spent a few years as a Postdoc at the Algorithms Group in Google Research NYC (2013-15), and at EPFL in Switzerland (2012-13). Going back further in time, I spent several years as a PhD student at Princeton University, and as an undergrad at IIT Bombay.
The best way to contact me is via email, at: bhaskaraaditya AT gmail DOT com.
For students with questions on grades, etc., please use: a.bhaskara AT utah DOT edu.
Office Address: WEB 2692 (Warnock Engineering Building, Second Floor)
Research Interests
- Algorithms & Optimization
- Machine Learning, with a focus on Robustness and Efficiency
- (More Broadly) Foundations of AI, Theoretical Computer Science
Selected Publications
For a list of publications, please see my DBLP page. Here are a few recent(-ish) publications, just as a taste of my interests.- Descent with Misaligned Gradients and Applications to Hidden Convexity
(A. Bhaskara, A. Cutkosky, R. Kumar, M. Purohit)
International Conference on Learning Representations (ICLR) 2025 - Convergence Guarantees for the DeepWalk Embedding on Block Models
(C. Harker, A. Bhaskara)
International Conference on Machine Learning (ICML) 2024 - New Tools for Smoothed Analysis: Least Singular Value Bounds for Random Matrices with Dependent Entries
(A. Bhaskara, E. Evert, V. Srinivas, A. Vijayaraghavan)
ACM Symposium on Theory of Computing (STOC) 2024 - Online Learning and Bandits with Queried Hints
(A. Bhaskara, S. Gollapudi, S. Im, K. Kollias, K. Munagala)
Innovations in Theoretical Computer Science (ITCS) 2023 - Additive Error Guarantees for Weighted Low Rank Approximation
(A. Bhaskara, A.K. Ruwanpathirana, M. Wijewardena)
International Conference on Machine Learning (ICML), 2021
Teaching
Here are some courses I have taught in the recent past:
- (Spring 2026) CS 3130: Probability and Statistics for Engineers (Canvas Link)
- (Fall 2025) CS 4150: Algorithms (Canvas Link)
- (Spring 2025) CS 6960: Theory of Machine Learning (Course Webpage) Course material should be publicly accessible. This course is intended for early graduate students and mathematically inclined UGs.
- (Spring 2024) CS 6966: Algorithms, Geometry, and Optimization (Course Webpage) The course is intended for senior UGs and early year graduate students. It covers several topics essential for algorithms research, including probabilistic analysis, LPs and SDPs, spectral graph theory, and online algorithms
Contact Information
Email: a.bhaskara@utah.edu
Office: WEB 2692, Warnock Engineering Building, University of Utah
Phone: (801) 581-8224 (School of Computing)