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Hao Jiang | 姜昊 I am a first-year PhD student in Computer Science at the University of Southern California, advised by Prof. Daniel Seita. I completed my undergraduate studies at USC, double majoring in Computer Science and Applied & Computational Mathematics (ACMA). I'm broadly interested in robot learning and manipulation. Currently, my focus is on dexterous grasping & manipulation. |
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Selected Publications(* indicates equal contribution, † indicates equal advising) |
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Concurrent Prehensile and Nonprehensile Manipulation: A Practical Approach to Multi-Stage Dexterous Tasks
Hao Jiang, , Yue Wang, Gaurav S. Sukhatme, Daniel Seita Technical Report, 2025 project page / arXiv Sample-efficient dexterous manipulation via retrieve-align-execute over object-centric skills. Achieves 66% success on concurrent multi-stage tasks with 3–4 demos per object, outperforming diffusion policy baselines by 2–3×. |
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Learning to Singulate Objects in Packed
Environments using a Dexterous Hand
Hao Jiang, Yuhai Wang*, Hanyang Zhou*, Daniel Seita International Symposium of Robotics Research (ISRR), 2024 project page / arXiv / code / presentation / blog Multi-phase RL with a displacement-based state representation for singulating target objects in clutter using a 16-DOF Allegro Hand. Demonstrates strong sim-to-real transfer and outperforms baselines in packed-environment tasks. |
Other Publications |
Open-Source |
Award
CRA Outstanding Researcher
: Honorable Mention 2025
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Service
Journal reviewer
: IEEE Robotics and Automation Letters (RA-L)
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