About Me
Hi! I am PhD student in the Department of Electrical Engineering and Computer Science (EECS) at MIT advised by Prof. Marzyeh Ghassemi. My research broadly focuses on developing fair, interpretable, and robust models by carefully re-evaluating and surfacing assumptions in machine learning-based measurements in socially-relevant contexts.
I have held research intern positions at the Stanford RegLab (advised by Prof. Dan Ho), the Max Planck Institute for Security and Privacy (advised by Prof. Asia Biega), the Technische Universität, Dresden as a DAAD-WISE scholar, and at the Philips Innovation Campus, Bengaluru in the healthcare R&D team.
Previously, I was a Research Engineer at Winterlight Labs. I graduated from the University of Toronto with a Master’s degree in Applied Computing. My master’s project, generously supported by Winterlight Labs and a Mitacs Accelerate Scholarship, was supervised by Prof. Marzyeh Ghassemi, Prof. Frank Rudzicz, and Dr. Jekaterina Novikova. Prior to this, I graduated with honors from the Indian Institute of Technology, Guwahati.
Here is my CV.
I’m on the job market for postdoctoral and industry research positions
News
- Dec 2024: Presenting at the Women in Machine Learning, AFME, and RBFM workshops at NeurIPS in Vancouver!
- Aug 2024: Giving a spotlight talk at the Responsible AI for Health Symposium RAIHS at John Hopkins in DC!
- May 2024: Excited to be summer institute fellow at the Stanford Regulation, Evaluation, and Governance Lab!
Research Interests
I am broadly interested in developing techniques to support fair classification and ranking in healthcare contexts. In this scope, the themes of my own research are:
(1) Understanding and Improving Responsible Data Acquisition Practices, (2) Developing Algorithms and Measures for Fair Ranking, and (3) Studying Views of Interpretability to Achieve Fair Outcomes Through an HCI+AI lens.