Arjun Nitin Bhagoji

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PhD Student
Department of Electrical Engineering
Princeton University

Email: abhagoji [at] princeton [dot] edu
Contact: F310, Engineering Quad, Princeton, NJ 08544
[CV](Last Updated: October 2019)

About me

I'm currently a fifth year graduate student in the Department of Electrical Engineering at Princeton University advised by Prateek Mittal. I mainly work on problems at the intersection of machine learning and security. I am also interested in issues of fairness, accountability and transparency in machine learning. I worked with Bo Li and Dawn Song at the University of California, Berkeley over the summer of 2017. I spent the summer of 2018 working with Supriyo Chakraborty at the IBM T.J. Watson Research Center.

Before coming to Princeton, I completed my Dual Degree (B.Tech. (Honours) & M.Tech.) in Electrical Engineering from the Indian Institute of Technology Madras. During my time there, I was fortunate to have the opportunity to work with Pradeep Sarvepalli and Andrew Thangaraj. I also spent the summer of 2013 working with Jan Sperling at the University of Rostock.


October 2019: Spotlight talk at the IAS School of Mathematics Theory of Deep Learning Workshop.
October 2019: Our work was featured on the Princeton School of Engineering and Applied Science's website.
September 2019: Received the Yan Huo *94 Graduate Fellowship in Electrical Engineering 2019 from the Department of Electrical Engineering, Princeton University
September 2019: Paper on lower bounds on adversarial robustness using optimal transport accepted to NeurIPS 2019.
August 2019: Paper exploring robustness of machine learning systems to out-of-distribution adversarial examples accepted to AISec 2019.