Karthikeyan Shanmugam

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
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    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)
    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)
    InfoNCE Loss Provably Learns Cluster-Preserving Representations
    Advait Parulekar
    Aryan Mokhtari
    Liam Collins
    Sanjay Shakkottai
    COLT 2023