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Email:
chuang26@kent.edu
Phone:
+1 (234)-327-1330
Chao Huang is an Ph.D. candidate (Sep. 01 2019~now) at College of Aeronautics and Engineering, Kent State University, Ohio, USA. He is studying in the Cognitive Robotics and AI lab (CRAI) for Cognitive Robotics, Multi-agent Reinforcement Learning, fast and robust generalization, advised by Prof. Rui Liu.
In the Institute of Automation, Chinese Academy of Science he received Master degree in 2019 July. Chao Huang graduated and received his Bacheloe’s degree, China, at 2016 July.
Recent News
[paper acceptance] 2022.08:
my latest research “Byzantine Resilient Reinforcement Learning for Multi-Agent UAV Systems” has been accepted by 2023 AIAA SciTech.
[paper acceptance] 2022.03:
my latest research “Design Attention Awareness Among Robots for Uncertainty-Adaptive Heterogeneous Teaming” has been accepted by IEEE ARSO.
[paper acceptance] 2021.06:
my latest research of using a novel meta-learning based human preference model was developed to model human preference in the multi-robot deployment. The human preference model can fast adapt to various human preference on multi-robot behaviors. The paper has been accepted by the prestigious robotics conference IROS2021.
[paper acceptance] 2021.06:
my latest research of using a novel Synthesized Trust Learning (STL) method was developed to model human trust in the collaboration. STL explores two aspects of human trust (trust level and trust preference), meanwhile accelerates the convergence speed by integrating active learning to reduce human workload. The paper has been accepted by the prestigious robotics conference ROMAN2021.
[paper acceptance] 2021.05:
my latest research of using attention-transfer for repairing human-trust in human robot collaboration has been accepted by the 2021 17th IEEE International Conference on Automation Science and Engineering (CASE).
[paper acceptance] 2020.06:
my latest research of using attention for human-multi UAV teaming in natural disaster rescue has been accepted by the prestigious robotics conference RSS2020 as workshop papers.