I'm a Senior Research Scientist at NVIDIA, NYC. Prior to NVIDIA, I was a Research Scientist at FAIR, Meta AI. I received my Ph.D. in Computer Science from TTI Chicago working with Kevin Gimpel and Karen Livescu. Before TTIC, I was at IBM Research India working on IBM Watson related research. I received my B.Tech. in Computer Science and Engineering from IIT Kanpur.

My research focuses primarily on natural language processing (NLP). Some of the key topics which drive my research are:

• Reasoning with Language Models: Performing reasoning with LLMs; Generating synthetic data with LLMs; Impact of pretraining data on emergence of LLM capabilities. [1][2][3]
• Entity Tracking with Language Models: Understanding text requires that the models are building an implicit/explit representation of the underlying world. Are language models trained on mere surface form capable of representing the underlying world? [3][4][5]

• Oct 2024 - Released OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data. Links - [Code][Models and Dataset]
• Sep 2024 - Major Entity Identification: A Generalizable Alternative to Coreference Resolution has been accepted to EMNLP 2024 and CRAC 2024!
• Sep 2024 - OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset has been accepted to NeurIPS Datasets and Benchmarks Track as an oral. See you in Vancouver!
• June 2024 - Nemotron-4 340B is out!
• May 2024 - Arxiv report of our ongoing work on effect of code pretraining on entity tracking.