CV Publications Awards Projects Students Extra-currics

About Me

I am a Ph.D. candidate working in statistical machine learning with a focus on metric elicitation and optimization, fairness, ranking, and recommendation systems. I am advised by Prof. Sanmi Koyejo. Prior to joining the Ph.D. program, I worked at Adobe Research, India for two years. I have pursued integrated masters in Mathematics and Scientific Computing from IIT Kanpur, where I began my machine learning journey with Prof. Harish Karnick.

Ph.D. Research Internships

(Summers’19) I spent summers’20 at the innovative office of Google Research, Mountain View (remotely interned from Urbana due to Covid), where I was mentored by Dr. Harikrishna Narasimhan and Dr. Mahdi Milani Fard.
(Summers’19) I spent summers’19 at the dynamic office of Amazon (A9) Research, Palo Alto, where I was mentored by Dr. Nikhil Rao and Dr. Sumeet Katariya.
(Summers’18) I spent summers’18 at the wonderful office of Microsoft Research, India, where I was mentored by Dr. Prateek Jain and Dr. Ayush Choure.

Prior to Ph.D.

(June’15-July’17) I was a member of research staff at Adobe Research, India, where I mostly worked in Time Series Analysis and Recommendation systems and also explored many areas including Augmented Reality, Natural Language Processing, and Visualization (paper to be completed someday). However, all the projects had Machine Learning in action.

(Summers’13) At some point, I was really interested in Discrete Mathematics, especially, Combinatorics. For summers 2013, I got a wonderful opportunity to work with Dr. Jean-Marc Schlenker at the University of Luxembourg. Under his guidance, I published my first siginificant work in the European Journal of Combinatorics.

NEWS

(December 2020) Presented our paper on Fair Performance Metric Elicitation at the Conference on Neural Information Processing Systems.
(July 2020) Presented our paper on Optimization and Analysis of the pAp@k Metric for Recommender Systems at the International Conference on Machine Learning.
(March 2019) Awarded the prestigious C.L. and Jane W.-S. Liu Award for showing exceptional research promise. It is awarded to only one student each year across batches.
(December 2019) Presented our paper on Mutliclass Performance Metric Elicitation at the Conference on Neural Information Processing Systems.
(November 2019) Nominated by the Computer Science Department (first round) and then by the University of Illinois at Urbana-Champaign (second round) for one of the most competetive fellowships – Google PhD Fellowship.
(July 2019) Harvineet presented our paper on Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank at the Conference on Uncertainty in Artificial Intelligence.
(April 2019) Presented our paper on Performance Metric Elicitation from Pairwise Classifier Comparisons at the International Conference on Artificial Intelligence and Statistics.
(February 2019) Presented our paper on Clustered Monotone Transforms for Rating Factorization at the International Conference on Web Search and Data Mining.
(May 2018) Presented our paper on Sparse Decomposition of Time Series at the SIAM International Conference on Data Mining (SDM), 2018 held in San Diego, USA.
(October 2017) Our paper on Enhanced Digital Marketing using Augmented Reality was presented by Dr. Atanu Sinha at the International Symposium on Mixed and Augmented Reality (ISMAR), 2017 held in Nantes, France.

Teaching

Teaching Assistant for CS 446: Machine Learning, Fall 2017