Currently, I am a Research Scientist at Adobe Research, Bangalore (India). Prior to this, I spent two years as a postdoc at Google Research, India working with Dr. Prateek Jain and Dr. Karthikeyan Shanmugam . Before that, I completed my Ph.D in the Computer Science Department (CICS) at the University of Massachusetts Amherst advised by Dr. Arya Mazumdar. During that time, I was a Visiting Graduate Student at the University of California San Diego from May – November 2021. I had also spent the summer of 2019 as a Research Intern at Ernst & Young AI Lab at Palo Alto and Spring 2020 as an Applied Scientist Intern at Amazon Search (Berkeley). Even earlier, I graduated from Indian Institute of Technology, Kharagpur in August 2016 with a Bachelor’s degree in Electronics and Electrical Communication Engineering.
Research Interests
My research interests are LLM Efficiency and Theoretical Machine Learning focused on Non-convex Optimization and Online Learning. More concisely, I love Statistical recovery/reconstruction problems under different reasonable structural assumptions on the data generating mechanism such as sparsity, low-rank, presence of latent clusters among others. Nowadays, I am working on designing algorithms in offline/online/hybrid systems aimed at incorporating personalization efficiently at scale. Most of my work so far can be categorized into five topics namely 1) Scalable Personalization via Low Rank and Sparse Decomposition 2) Multi-agent Online Learning via Collaborative Filtering 3) Latent Variable models – Mixtures of Linear Regression, Linear Classifiers and Distributions 4) Generative models for Graph Clustering – Geometric Block Model and 5) Active learning for Semi-supervised clustering – Disjoint Clusters, Overlapping Clusters and Fuzzy Clusters
Personal Webpage (see for Detailed Publication list) – https://soumyabratap.github.io/