Furong Huang

Furong Huang is an Associate Professor at the University of Maryland's Department of Computer Science, with affiliations at the Institute for Advanced Computer Studies, Center for Machine Learning, Maryland Robotics Center, and Applied Mathematics, Statistics, and Scientific Computation Program. Her research bridges trustworthy machine learning, sequential decision-making, and foundation models for robotics, emphasizing reliability, interpretability, and ethical standards.

Research Interests:

• Trustworthy AI
• Generative AI
• Reinforcement Learning
• AI Security
• Algorithmic Fairness
• Foundation Models for Robotics

Recent Publications span leading conferences (NeurIPS, ICML, ICLR, CVPR) and journals, focusing on:

• Robustness in Vision-Language Systems
• Trustworthy Generative AI
• Foundation Models for Sequential Decision-Making
• AI Security and Watermarking

Scientific Awards

• MIT TR35 Innovator Under 35 (Asia Pacific 2022)
• Best Paper Award, AdvML Frontier Workshop, NeurIPS 2024
• NSF NAIRR Pilot Awardee
• Microsoft Accelerate Foundation Models Research Award (2023)
• JP Morgan Faculty Research Awards (2019–2022)

Advising and Grants: Her lab has graduated students to roles at OpenAI, Google, Meta, and Netflix. Research funded by DARPA, NSF, ONR, AFOSR, and industry partners like Microsoft, Adobe, and Capital One.

Labs & Teams: Leads research groups focused on Trustworthy AI and Robotics at the University of Maryland, collaborating with the Maryland Robotics Center and Applied Mathematics Program.