Led the development of MOMENT, a family of multi-task time series foundation models, which have been downloaded over 2.2 million times on HuggingFace, and attracted over USD 2.5 million in government and industrial funding. His thesis on pragmatic time series intelligence is available online. Published several papers such as 'MOMENT: A Family Of Open Time-series Foundation Models', some of which won best student abstract awards and best paper honorable mentions.
Research Experience
Worked as a Student Researcher within Athena at Google Research; interned as an Applied Scientist Intern at Amazon Web Services (AWS) AI Labs for two summers.
Education
Ph.D. in Robotics from the School of Computer Science at Carnegie Mellon University, advised by Prof. Artur Dubrawski; B.Tech. in computer engineering from Delhi Technological University (formerly Delhi College of Engineering). The second year of his Ph.D. was supported by the Center for Machine Learning and Health (CMLH) Fellowship 2021.
Background
Research interests: building and evaluating capable and useful software engineering agents. Specialization: Robotics. Brief introduction: Currently an Applied Scientist at Amazon, dedicated to making foundation models useful, efficient, and safe, particularly in high-stakes domains.
Miscellany
Can be reached out via email for collaboration or interest in his research.