Andreas Sochopoulos
PhD in Robot Learning | University of Edinburgh | Honda Research Institute Europe
Hello! My name is Andreas, and I am currently a PhD student at the University of Edinburgh (UoE), supported by Honda Research Institute Europe (HRI-EU), and advised by Sethu Vijayakumar (UoE), Michael Gienger (HRI-EU).
My research focuses on imitation learning using continuous-time generative models, such as diffusion and flow models. So far, I have worked on accelerating the inference of flow models for action generation without additional training overhead, as well as on guaranteeing constrained solutions for neural ODEs. I am particularly interested in ways to make diffusion/flow-based policies force-aware, fast, and robust when training with limited demonstrations.
I am currently exploring adaptive compliance-based VLA post-training using offline RL. If you are interested in my research or would like to discuss related topics, feel free to reach out!
News
| Aug 01, 2025 | Our paper, Fast Flow-based Visuomotor Policies via Conditional Optimal Transport Couplings, has been accepted at the Conference on Robot Learning (CoRL), 2025! |
|---|---|
| Jul 01, 2025 | Thrilled to announce that I will be spending this July as a visiting PhD in the University of Tokyo. Feel free to reach out if you’re in Tokyo. |
| Jun 01, 2024 | Our paper, Learning Deep Dynamical Systems using Stable Neural ODEs, has been accepted at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024! |
Selected Publications
-
Learning deep dynamical systems using stable neural ODEsIn 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024