Lab notebook
Research releases, talks, student milestones, awards, and other signals from Furong Lab.
HumanEgo learns robot manipulation policies from minutes of human egocentric video, without robot demonstrations. Congratulations to all coauthors!
μ₀: A Scalable 3D Interaction-Trace World Model learns from video to predict 3D interaction traces that transfer across embodiments. Congratulations to all coauthors!
The paper introduces SkillFormer, which combines skill-conditioned vision and touch with event memory to track progress in contact-rich robotic manipulation. Congratulations to all coauthors!
Furong presented at the ECCV 2026 tutorial “Evaluating Visual Foundation and World Models” in Malmö, Sweden. Drawing on IVE, DynaFLIP, μ₀, and Guava, the talk examined evaluation as infrastructure for a reliable digital development loop grounded in physical evidence.
Furong spoke at Math & AI Summer in Seattle at Amazon, covering controlled decoding, agentic critical training, and query-adaptive workflows for self-improving agentic systems.
UMD CS alumnus Ananth Sankaralingam (B.S. ’26), co-founder of Chromie.dev, reflects on how Furong’s graduate AI course broadened his view of what could be built with large language models.
Featured talk at the Agentic AI Summit 2026 at UC Berkeley, with slides on control across thinking, actions, and workflow.
An advanced summer-school course on agent architectures, reasoning, alignment, safety, and world models.
Auditors, actuators, and amplifiers for trustworthy AI.
Adaptive test-time compute for planning agents.
Work spanning reasoning, safety, multimodal systems, scientific prediction, and multi-agent learning.
The agentic safety benchmark is used in the released Muse Spark MSL model.
World modeling in 3D trace space for cross-embodiment robot learning.
Including MomaGraph, selected for an oral presentation.
One paper accepted and selected for an oral presentation.
Including one spotlight presentation.
Keynote at the RLC workshop on Reinforcement Learning Beyond Rewards.
Keynote at the fourth CVPR Workshop on Computer Vision in the Wild.
Keynote at the second Texas Colloquium on Distributed Learning on enhancing generative AI agents.
Keynote at the ICLR Generative AI Watermarking Workshop on stress-testing watermark robustness.
Keynote at the ICLR World Models Workshop on learning foundation models for action.
Keynote at the New York Academy of Sciences Annual Machine Learning Symposium on stress-testing and alignment.
Promotion in the University of Maryland Department of Computer Science, effective July 1, 2024.
A talk for the SEC AI Community of Practice on multimodal approaches to misinformation and content authenticity.
A public Reddit discussion about machine learning, trustworthy AI, and current research questions.
Chair and organizer of the Fairness in Artificial Intelligence principal-investigator meeting.
University of Maryland Department of Computer Science colloquium.
Research releases, invited talks, recognition, career milestones, public engagement, and academic service.