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Jongseok Lee

DLR German Aerospace Center
Institute of Robotics and Mechatronics
Perception and Cognition
Muenchener Str. 20
82234 Wessling

telephone: +49 8153 28-4225
email: Jongseok Lee

I am a research scientist at the Institute of Robotics and Mechatronics, the German Aerospace Center (DLR) since 11.2017. In 12.2020, I started an external PhD at the Karlsruhe Institute of Technology (KIT). My advisors are Prof. Tamim Asfour (KIT) and Prof. Rudolph Triebel (DLR & TU Munich). Previously, I completed my MSc in robotics, systems and control at ETH Zurich and BSc in aerospace engineering at TU Delft. I was born in South Korea, but I also grew up in Hyderabad, India and Dublin, Ireland. I made my media debut by fishing drones.

My research aims to create robots with introspective capabilities, i.e., an intrinsic understanding of their own limitations, failures and shortcomings. Once equipped with an awareness about their own failures and limitations, robots will be able to avoid catastrophic effects by modifying their own behavior towards safety. This will lead to more explainable Artificial Intelligence and more reliable robotic systems for wider industrial deployments.

Research Interests: Field Robotics / Probabilistic Robotics / Bayesian Deep Learning.

Do not hesitate to contact me (email: This email address is being protected from spambots. You need JavaScript enabled to view it.).

Google Scholar / Linkedin / Twitter


Recent News!

[08.2023] Our work on SPIRIT was featured on IEEE video friday. Check out these links: Link 1 & Link 2.

[06.2023] We got KUKA Innovation Award Finalist 2023. Check out these links: Link 1 & Link 2.

[05.2023] Our RA-L2023 paper was on Helmholtz AI news-feed. Check out this link: Link.

[04.2023] We were interviewed by the EU RIMA. Check out these links: Link 1 & Link 2.

[11.2022] Our research on aerial manipulation was featured at the ProRobots channel. Check out this Link.

[10.2022] We are organizing an IROS 2022 workshop "Probabilistic Robotics in the Age of Deep Learning".



For a complete list of my publications, check out my google scholar profile.

Learning Fluid Flow Visualizations from In-Flight Images with Tufts

Jongseok Lee*, Jurrien Olsman* and Rudolph Triebel. RAL 2023. *equal contributions


Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks

Dominik Schnaus*, Jongseok Lee*, Daniel Cremers and Rudolph Triebel. ICML 2023. *equal contributions


Virtual Reality via Object Poses and Active Learning: Realizing Telepresence Robots with Aerial Manipulation Capabiltiies

Jongseok Lee, Ribin Balachandran, Konstantin Kondak, Andre Coelho, Marco De Stefano, Matthias Humt, Jianxiang Feng, Tamim Asfour and Rudolph Triebel. Field Robotics 2023.

Paper Video PosterSlides

Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes

Jongseok Lee, Jianxiang Feng, Matthias Humt, Marcus G. Müller and Rudolph Triebel. CoRL 2021.

Paper Video Code Slides Poster

Estimating Model Uncertainty of Neural Networks in Sparse Information Form

Jongseok Lee, Matthias Humt, Jianxiang Feng and Rudolph Triebel. ICML 2020.

Paper Code PosterSlides

Visual-Inertial Telepresence for Aerial Manipulation

Jongseok Lee, Ribin Balachandran, Yuri S. Sarkisov, Marco De Stefano, Andre Coelho, Kashmira Shinde, Min Jun Kim, Rudolph Triebel and Konstantin Kondak. ICRA 2020.

Paper Video Slides

Towards Autonomous Stratospheric Flight: A Generic Global System Identification Framework for Fixed-Wing Platforms

Jongseok Lee, Tin Muskardin, Cristina Ruiz Paez, Philipp Oettershagen, Thomas Stastny, Inkyu Sa, Roland Siegwart and Konstantin Kondak. IROS 2018.

Paper Poster Slides



  • Slides I created for introduction to Bayesian Neural Networks.
  • Blog posts from 2015 about building a smart phone controlled drone with an OpenCM board. Link


Last updated on Sunday, 15 October 2023 by Jongseok Lee