Papers
49
Total Citations
551
H-Index
12
About
Zhenzhong Jia is a versatile robotics researcher whose work spans manipulation, mobile robotics, medical robotics, and machine learning. His research addresses some of the field's most demanding challenges: enabling robots to operate intelligently in complex, uncertain physical environments. Among his most recognized contributions is his work on large-scale multi-object rearrangement, which demonstrated robotic systems capable of reorganizing up to 100 densely packed objects — a landmark achievement in manipulation planning that has garnered 70 citations. He has also made significant strides in medical robotics, developing a 3D ultrasound-guided robotic system for precise liver tumor ablation, cited 53 times and representing a meaningful bridge between robotics and clinical application. Jia's investigations into terramechanics-based wheel-terrain interaction models have advanced the reliability of off-road mobile and planetary rovers, with multiple papers in this domain accumulating over 90 citations collectively. His broader portfolio includes shared grasping strategies, robust reinforcement learning through adversarial training, and viewpoint-invariant place recognition. Across these diverse areas, Jia consistently translates rigorous theoretical modeling into practical robotic systems, making his work highly relevant to both academic researchers and engineers building next-generation autonomous machines.
Research Focus
Key Achievements
Top Papers
- 1Large-Scale Multi-Object Rearrangement70 citations · 2019
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- 4Manipulation with Shared Grasping29 citations · 2020
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- 7Robust Planar Dynamic Pivoting by Regulating Inertial and Grip Forces21 citations · 2020
- 8Adversary A3C for Robust Reinforcement Learning20 citations · 2019
- 9Fast Sequence-Matching Enhanced Viewpoint-Invariant 3-D Place Recognition19 citations · 2021
- 10Data-Driven Classification of Screwdriving Operations18 citations · 2017