Junning Huang
Research Interests
System Identification and Adaptive Control, Observer design, Optimal control
Affiliation
TU Darmstadt, Intelligent Autonomous Systems, Computer Science Department
Contact
junning.huang@ias.tu-darmstadt.de
Room E303, Building S2|02, TU Darmstadt, FB-Informatik, FG-IAS, Hochschulstr. 10, 64289 Darmstadt
+49-6151-16-20811
Junning joined the Intelligent Autonomous Systems Group at TU Darmstadt as a Ph.D. researcher in November 2020. He works with Davide Tateo and Jan Peters within IAS and its research group Safe and Reliable Robot Learning.
Before joining IAS, Junning received his bachelor‘s degree in Microelectronics, as well as his master’s degree in Computer Science from the Guangdong University of Technology. During his studies, he focused on two topics in reinforcement learning (RL): efficient exploration and RL applications in autonomous driving. His current research interest lays in three folds: 1. System Identification and Adaptive Control; 2. Observer Design; 2. Optimal Control, with applications on robots.
Publications
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- Siebenborn, M.; Belousov, B.; Huang, J.; Peters, J. (2022). How Crucial is Transformer in Decision Transformer?, Foundation Models for Decision Making Workshop at Neural Information Processing Systems.
Teaching Assistant
- Robot Learning Integrated Project (SS 2023)
Supervised Theses and Projects
Year | Type | Together with | Student(s) | Topic | Document |
---|---|---|---|---|---|
2023 | Project | Davide Tateo | Lu Liu | System Identification and Control for Unitree A1 | |
2023 | Project | Davide Tateo | Kilian Feess | System Identification and Control for Telemax Robot | |
2022 | Project | Davide Tateo | Kilian Feess | System Identification and Control for Telemax Robot | |
2022 | Master Thesis | Wenhua Bao | Model Based Hybrid Decision Making In Autonomous Driving | ||
2022 | Project | An Thai Le | Lu Liu, Yuheng Ouyang, Jiahui Shi | Benchmark Neural Lyapunov Control Algorithms on Pendulum | |
2022 | Project | An Thai Le | Chao Jin, Liyuan Xiang, Peng Yan | Hybrid Motion-Force Optimization |