Mohit Bansal

Mohit Bansal is the John R. & Louise S. Parker Distinguished Professor and Director of Graduate Admissions in the Computer Science Department at the University of North Carolina Chapel Hill. He leads the MURGe-Lab (UNC-AI Group) and serves as Lead (Core AI) for the ENGAGE NSF-AI Institute. Previously, he was a Research Assistant Professor at TTI-Chicago.

Dr. Bansal earned his Ph.D. from UC Berkeley in 2013 under Dan Klein and his B.Tech. from IIT Kanpur in 2008. His research spans Natural Language Processing and Multimodal Machine Learning, with specific expertise in multimodal generative models, grounded and embodied semantics (language with vision/speech for robotics), faithful language generation, reasoning and planning agents, and interpretable deep learning. He employs techniques from structured prediction, reinforcement learning, and model editing to address challenges in compositional generalization and robustness.

His recent work focuses on multimodal understanding, vision-language navigation, model merging, and evaluating/factuality in generative models. Trends show increasing emphasis on trustworthy AI, with projects addressing hallucination reduction, cultural bias diagnosis, and safe generation. His publications span top venues including ACL, CVPR, NeurIPS, and ICML, with significant contributions to multimodal foundation models and parameter-efficient learning.

• AAAI Fellow (2025)
• Presidential Early Career Award for Scientists and Engineers (PECASE) (2025)
• IIT Kanpur Young Alumnus Award (2023)
• DARPA Director's Fellowship (2019)
• NSF CAREER Award (2019)
• Microsoft Investigator Fellowship (2019)
• Outstanding Paper Awards at ACL, CVPR, EACL, COLING, and CoNLL

Dr. Bansal has advised numerous PhD students who now hold positions at top institutions including UT Austin, NTU Singapore, JHU, Meta, and Adobe. His lab secures substantial funding from NSF, DARPA, NIH, and ONR, including the $20M NSF-AI Institute on Engaged Learning where he serves as Core AI Lead. Current projects include DARPA's Environment-driven Conceptual Learning (ECOLE) and ONR's Science of Artificial Intelligence program.

The MURGe-Lab (Multimodal Understanding, Reasoning, and Generation) develops foundational models for multimodal tasks, with recent work on VideoTree for long video reasoning, SELMA for skill-specific text-to-image experts, and LASeR for adaptive reward model selection. The lab collaborates extensively with industry partners including Google, Meta, and Microsoft.