Research

Devendra Singh Chaplot is a Ph.D. student in the Machine Learning Department at Carnegie Mellon University working with Prof. Ruslan Salakhutdinov. His research interests lie at the intersection of machine learning, computer vision, and robotics. He has led the design of several AI systems, which won the CVPR-2019 Habitat Navigation Challenge and the Visual-Doom AI Competition 2017 and received Best Paper and Best Demo awards at leading AI conferences. His research has also been featured in several popular media outlets such as MIT Technology Review, TechCrunch, Engadget, Popular Science, Kotaku, and Daily Mail. Before joining CMU, Chaplot received his bachelor’s degree in Computer Science from IIT Bombay.

Research Summary:

Advances in machine learning in the last decade have led to “digital intelligence,” i.e. machine learning models capable of learning from vast amounts of labeled data to perform several digital tasks such as speech recognition, face recognition, machine translation, and so on. Chaplot’s research goal is to design algorithms capable of “physical intelligence,” i.e. building intelligent embodied autonomous agents capable of learning to perform complex tasks in the physical world involving perception, natural language understanding, reasoning, planning, and sequential decision making. His research has provided several key advances towards building intelligent embodied navigation agents capable of spatial and semantic understanding. Specifically, he has worked on training autonomous agents capable of active localization, active mapping, pose estimation, path planning, visual navigation, following natural language instructions and answering questions. These embodied navigation agents do not assume any prior perceptual or linguistic knowledge and learn to perform complex tasks from raw-pixel based first-person view of the environment and language queries.

For more information, please visit his website.