I am a Computer Science PhD student at the University of Wisconsin-Madison. I am grateful to have Prof. Frederic Sala and Prof. Ramya Korlakai Vinayak as my advisors. My research interests are broadly in foundations of machine learning, statistics and applications. Before coming to Madison I was at IBM Research, Bangalore for 3 years, where I worked on knowledge graphs, reasoning and information retrieval. I spent two wonderful years at the IISc, Bangalore to obtain a masters in CS, where I was fortunate to work with Prof. Chiranjib Bhattacharyya on temporal point processes and group inducing regularizers. I was a software engineer at Ittiam Systems, Bangalore for a couple of years where we built a media transcoding service. Before that I grew up playing cricket in a village in Bundelkhand, India and graduated from SGSITS, Indore with B.E. in computer science. For more details you can checkout my CV.

• I am interested in machine learning and statistics, with a focus on understanding fundamental principles and developing theoretically grounded solutions (a.k.a "practical theory"). My current interests revolve around, learning with less labeled data [auto-labeling, weak supervision], uncertainty quantification and calibration, and statistical inference/safe anytime valid inference (SAVI) [adaptive OOD detection].
• I gravitate towards efficient organization and retrieval of information and love building efficient+elegant systems in general. I have delved into reasoning and knowledge graph embeddings [quantum embeddings], and information retrieval. I am exploring Foundation models/LLMs as they provide a more unified and promising solution to these problems.
• I am also enthusiastic about optimzation and game theory [parameter markets, federated learning].

Served as a reviewer for,

• Neural Information Processing Systems (NeurIPS)
  2021, 2022, 2023.
  Top Reviewer (~ top 8%) for NeurIPS 2022.
• International Conference on Machine Learning (ICML)
  2022, 2023, 2024.
• International Conference on Learning Representations (ICLR)
  2021, 2022, 2023, 2024.
• International Conference on Artificial Intelligence and Statistics (AISTATS)
  2024.
• Transactions on Machine Learning Research Journal (TMLR) Since 2022.
  

• I was TA for,
  1. CS 761, advanced course on Mathematical Foundations of ML, Instructor Prof. Rob Nowak, [Spring, 22]. I helped with homeworks, exams, held office hours and gave a lecture on uniform convergence results for finite hypothesis class.
  2. CS 760, grad level intro to ML course, Instructor Prof. Fred Sala, [Fall, 21 ]. I helped with homeworks, exams and held office hours.
• In general, I enjoy teaching and mentoring. I have taught students at various levels in my village during my high school, partly to support my education and with the hope to inspire the otherwise disinterested kids. It has also been a yardstick to measure my own understanding. ( Feynman's quote "If you want to master something, teach it."). My biggest success has been teaching and mentoring my younger brother from the elementary school till the college, who is now a much better software engineer than me.

• I enjoy sports/athletic activities, particularly enjoy playing cricket, badminton, racquetball and biking, running.
• I like reading Indian philosophy and Hindi poetry (e.g. Kabir), it gives me useful point of views/tools and has been a source of peace and strength in tough times :).