CV
Robot learning and AI researcher focused on reinforcement learning for robotic manipulation and interpretability for RL agents. TODO: add a downloadable CV PDF under assets/pdf/ and set cv_pdf above.
Basics
| Name | Wenhao Lu |
| Label | PhD Researcher in Robot Learning and Explainable RL |
| wenhao.lu@uni-hamburg.de | |
| Url | https://LukasWill.github.io |
| Summary | Robot learning and AI researcher focused on reinforcement learning for robotic manipulation and interpretability for RL agents. My work studies how learned policies can be trained, evaluated, and explained in embodied decision-making tasks. |
Education
-
Hamburg, Germany
Skills
| Reinforcement Learning | |
| PPO | |
| reward shaping | |
| reward decomposition | |
| trajectory-level evaluation |
| Robot Learning | |
| robotic manipulation | |
| simulation-based learning | |
| obstacle-aware behavior | |
| embodied control |
| Interpretability | |
| causal state distillation | |
| high-level robotic explanations | |
| mental modeling of RL agents | |
| action coherence analysis |
| Research Engineering | |
| PyTorch | |
| robotics simulation | |
| experiment analysis |
Interests
| Research Interests | |
| reinforcement learning for robotic manipulation | |
| robot learning and robotic manipulation | |
| explainable reinforcement learning | |
| interpretability for RL agents |
Projects
- - Present
RL-Driven Robotic Manipulation
Reinforcement learning for robotic manipulation, including reward design, obstacle-aware behavior, and simulation-based evaluation.
- robot learning
- reinforcement learning
- manipulation
- - Present
Causal and Language-Based RL Interpretability
Analyses of RL agents using causal state distillation and language-model mental modeling to inspect learned behavior from trajectories.
- RL interpretability
- causal analysis
- mental modeling