Karthikeyan Shanmugam
I am a Research Scientist at Google Deepmind India (Bengaluru). I am part of the Machine Learning Foundations and Optimization Team.
Previously, I was a Research Staff Member with the IBM Research AI, NY during the period 2017-2022 and a Herman Goldstine Postdoctoral Fellow at IBM Research, NY in the period 2016-2017. I obtained my Ph.D. in ECE from UT Austin in 2016. My advisor at UT was Alex Dimakis. I obtained my MS degree in Electrical Engineering (2010-2012) from the University of Southern California, B.Tech and M.Tech degrees in Electrical Engineering from IIT Madras in 2010.
My research interests broadly lie in Graph algorithms, Machine learning, Optimization, Coding Theory and Information Theory. Specifically in machine learning, my recent focus is on Causal Inference, Bandits/RL and Explainable AI. Please visit my personal webpage for more details.
Authored Publications
Sort By
Online Bidding under RoS Constraints without Knowing the Value
Sushant Vijayan
Swati Padmanabhan
The Web Conference (2025)
Fairness under Covariate Shift: Improving Fairness-Accuracy tradeoff with few Unlabeled Test Samples
Shreyas Havaldar
Jatin Chauhan
Jay Nandy
The 38th Annual AAAI Conference on Artificial Intelligence (2024)
Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation
Shreyas Havaldar
The Twelfth International Conference on Learning Representations (ICLR) (2024)
General Identifiability and Achievability for Causal Representation Learning
Burak Varici
Emre Acarturk
Ali Tajer
AISTATS 2024 (Oral), Oral Talk at NeurIPS Causal Representation Learning Workshop 2023. (2024)
Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge
Abhin Shah
Murat Kocaoglu
Neural Information Processing Systems 2023 (NeurIPS 2023) (2023) (to appear)
Causal Bandits for Linear Structural Equation Models
Ali Tajer
Burak Varici
Prasanna Sattigeri
Journal of Machine Learning Research (2023) (to appear)
