Kuan FangEmail: kuanfang [at] berkeley [dot] edu |
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I will start as an Assistant Professor of Computer Science at Cornell University in Fall 2024. Currently, I am a Postdoc at the Berkeley Artificial Intelligence Research and a Researcher at Boston Dynamics AI Institute. I received my Ph.D. from Stanford University, advised by Fei-Fei Li and Silvio Savarese. I received my B.E. degree from Tsinghua University. I have spent time at Google Brain, Google [x] Robotics, and Microsoft Research Asia. My research is supported by a Computing Innovation Fellowship.
Prospective students: I am actively looking for motivated students with a strong background in robotics, computer vision, and machine learning. If you are interested in working with me, please apply to the Cornell CS PhD Program and mention my name in your statement of purpose. Google Scholar | GitHub | LinkedIn | Twitter |
MOKA: Open-Vocabulary Robotic Manipulation through Mark-Based Visual Prompting
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Stabilizing Contrastive RL: Techniques for Offline Goal Reaching
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Multi-Stage Cable Routing Through Hierarchical Imitation Learning
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Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
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BridgeData V2: A Dataset for Robot Learning at Scale
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Active Task Randomization: Learning Robust Skills Via Unsupervised Generation of Diverse and Feasible Tasks
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Generalization with Lossy Affordances: Leveraging Broad Offline Data for Learning Visuomotor Tasks
CoRL 2022 (Oral Presentation) PDF | Website | Code | BibTex |
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Planning to Practice: Efficient Online Fine-Tuning by Composing Goals in Latent Space
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Discovering Generalizable Skills via Automated Generation of Diverse Tasks
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Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations
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Adaptive Procedural Task Generation for Hard-Exploration Problems
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KETO: Learning Keypoint Representations for Tool Manipulation
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Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation
CoRL 2019 (Oral Presentation) PDF | Website | Blog | Environment | Code | BibTex |
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Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks
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Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision
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Multi-Task Domain Adaptation for Deep Learning of Instance Grasping from Simulation
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Demo2Vec: Reasoning Object Affordances from Online Videos
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Recurrent Autoregressive Networks for Online Multi-Object Tracking
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DeLay: Robust Spatial Layout Estimation for Cluttered Indoor Scenes
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