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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Feb 07, 2024 I have been selected as finalist for the George Girault Ph.D. award!! Europe’s highest honor for a robotics dissertation :heart:
Dec 18, 2023 I succesfully defended my Ph.D with Suma Cum Laude :blush:
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

  1. se3dif.gif
    SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion
    J. Urain ,  N. Funk ,  G. Chalvatzaki , and 1 more author
    ICRA, 2023
  2. msvf_2022.gif
    Learning Stable Vector Fields on Lie Groups
    J. Urain ,  D. Tateo ,  and  J. Peters
    RA-L / ICRA, 2022
  3. rss_2021.gif
    Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning
    J. Urain ,  A. Li ,  P. Liu , and 2 more authors
    R:SS / IJRR, 2021
  4. ral_2021.gif
    Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation
    N. Funk ,  C. Schaff ,  R. Madan , and 8 more authors
    RA-L, 2021