Julen Urain
Postdoctoral Researcher at the German Research Centre for Artificial Intelligence (DFKI)
I recently received my doctorate from TU Darmstadt under the supervision of Prof. Jan Peters. I am currently a postdoctoral researcher at the Intelligent Autonomous Systems lab (IAS) and the DFKI. Previously, I interned as a researcher in Nvidia’s Seattle Robotics Lab (SRL). I did my Master’s degree at UPC and my Master’s Thesis at EPFL in the Biorobotics Lab. For my research, I was honoured to be selected as an R:SS Pioneer.
My research interests lie at the intersection of robotics and machine learning. In particular I explore the combination of fields such as deep generative models, motion planning and control, imitation learning, optimisation, and reinforcement learning. During my PhD, I adapted diffusion models to the Lie group SE(3) to represent 6-DoF grasp pose distributions, explored the composability of energy-based models for reactive motion generation and exploited normalizing flows to learn nonlinear globally stable dynamical systems from demonstrations.
If you are interested in similar topics, I am always looking for collaborations or thesis supervision, so please do not hesitate to contact me.
Contact: julen [at] robot-learning [dot] de
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news
Feb 07, 2024 | I have been selected as finalist for the George Girault Ph.D. award!! Europe’s highest honor for a robotics dissertation |
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Dec 18, 2023 | I succesfully defended my Ph.D with Suma Cum Laude |
Jun 02, 2023 | We won Best Paper Award in Geometric Representations Workshop at ICRA 2023 for our work on SE(3) DiffusionFields. |
Apr 28, 2023 | I am a R:SS Pioneer! A 30 member strong-cohort of top early robotics researchers (%22 acceptance). |
Mar 06, 2023 | Accepted our IJRR paper on Composable Energy Policies. |
selected publications
- SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusionICRA, 2023
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- Composable Energy Policies for Reactive Motion Generation and Reinforcement LearningR:SS / IJRR, 2021
- Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object ManipulationRA-L, 2021