Hello, I recently graduated with a Master's degree from the David R. Cheriton School of Computer Science at the University of Waterloo, where I was advised by Prof. Shai Ben-David. I am broadly interested in Theoretical Computer Science, particularly in Theoretical Machine Learning. I have recently been working on ethical issues (Fairness, Interpretability, Privacy, Robustness) in Machine Learning (and algorithms in general). I have also dabbled in some research projects related to Game Theory, Optimization, Graph Algorithms, and Clustering Theory. Overall, I am motivated by problems that are theoretically challenging, while also being practically relevant. Previously, I did my Bachelor's in Mathematics and Theoretical Computer Science from Chennai Mathematical Institute.
Fun fact: My Erdos number is 3 :)
Papers
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On Learnability with Computable Learners
Sushant Agarwal, Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, Ruth Urner
Appeared in ALT 2020. [pdf]
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Trade-offs Between Fairness, Interpretability, and Privacy in Machine Learning
Sushant Agarwal
Master's Thesis [pdf], Accepted as workshop poster in ALT 2020, in submission. [pdf]
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Trade-offs Between Fairness and Privacy in Machine Learning
Sushant Agarwal
Accepted in IJCAI 2020 Workshop on AI for Social Good. [pdf]
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Trade-offs Between Fairness and Interpretability in Machine Learning
Sushant Agarwal
Accepted in IJCAI 2020 Workshop on AI for Social Good. [pdf]
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A Different View of Fair Data Representation
Tosca Lechner, Nivasini Ananthakrishnan, Sushant Agarwal, Shai Ben-David
Workshop poster in ALT 2020, in submission. [pdf]
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A Critical Survey of Post-hoc Interpretability Tools Based on Feature Attributions
Sushant Agarwal, Shai Ben-David
Working paper. [pdf]
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Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Zhiwei Steven Wu, Himabindu Lakkaraju
In Submission. [pdf]
Projects
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Locality Sensitive Hashing for Probabilistic Clustering [pdf]
Theoretical Foundations of Clustering, 2019.
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Tractable Variants of Envy-Free Cake Cutting [pdf]
Game Theory, 2018.
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Improving Local-Search Methods Using Deep Neural Networks [pdf]
Deep Learning in Computational Discrete Optimization, 2018.
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Google is Watching You
Artificial Intelligence: Law, Ethics & Policy, 2017.
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Efficient Algorithms for Bounded Clique-Width Graphs
Topics in Graph Algorithms, 2017.