Vedant Nanda

I am a PhD student in the Computer Science Department at the University of Maryland, College Park and the Max Planck Institute for Software Systems (MPI-SWS), where I am part of the Maryland-Max Planck joint program. I am fortunate to have the guidance of Krishna P. Gummadi (MPI-SWS) and John P. Dickerson (University of Maryland) as my advisors, and I also collaborate closely with Adrian Weller at the University of Cambridge. My research focuses on Trustworthy Machine Learning, and I have published on topics such as the fairness implications of counterfactual explanations (ICML2019), fairness in image classification models due to disparate robustness of subgroups (FAccT2021), and fairness issues in two-sided markets such as rideshare platforms (AAAI2020 & AAAI2023). More recently, I have been exploring the nature of learned invariances in deep neural networks (ICML2022 & AAAI2023). I had the pleasure of interning twice at Amazon where I first worked on counterfactual explanations with AWS Clarify and then on fairness aspects of generative AI with AWS Bedrock.

I obtained my undergrad from IIIT Delhi (2015 - 2019) majoring in Computer Science and Engineering, where I was associated to Precog. During my undergrad I worked on topics related to Social Computing, Computational Social Science and ICT4D.

I am fortunate to have worked with some amazing mentors (in alphabetical order): Muhammad Bilal Zafar (Amazon), Hoda Heidari (ETH Zürich), Ponnurangam Kumaraguru (IIIT Delhi), Rijurekha Sen (IIT Delhi) and Pushpendra Singh (IIIT Delhi). I spent the wonderful summer of 2018 interning at MPI-SWS where I was advised by Krishna P. Gummadi.

For more, check out my CV.

  vnanda [at] mpi-sws [dot] org   vedant [at] cs [dot] umd [dot] edu



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