465 Soda Hall
Berkeley, California 94709
I am a PhD student at UC Berkeley where I work in Programming Languages and Machine Learning. I am particularly interested in how machine learning techniques can be used for developer productivity tools like program analysis, synthesis, and repair (ML for PL). I am also excited about how synthesis and verification can help in designing better generalizing and explainable algorithms and also reasoning about such algorithms (PL for ML)
I recieved my undergraduate degree from IIT Bombay where I was advised by Prof. Sunita Sarawagi on understanding robustness in natural language processing. Prior to that, I also delved quite a bit into computer vision (mostly adjacent to human-pose-estimation) with Prof. Arjun Jain and Prof. Abhinav Shrivastava at UMD College Park.
After my undergraduate, I spent two amazing years as a predoctoral research fellow at Microsoft Research India where I worked on machine learning and/or program synthesis. I was part of the Project Jigsaw and worked on cool research problems like program-repair with static analysis tools, improving large language models with guarentees, and learning decision trees with bandit feedback.
|Jigsaw (combining program synthesis with large language models) has been accepted at ICSE’22
|Preprint out on learning decision trees with bandit feedback
|Joined Microsoft Research, India as a Research Fellow
|Paper on named entity robustness of BERT models accepted to RepL4NLP, ACL’20
|Visiting University of Maryland for research internship with Prof. Abhinava Shrivastava
|Paper on adversarial examples in human pose estimation accepted in VUHCS, CVPR’19
|Recieved Undergraduate Research Award (URA) from IIT Bombay
Academic AdvisorsI have been fortunate to work many great researchers
- Jigsaw: Large Language Models meet Program SynthesisICSE May 2022
- Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient DescentAug 2022