People

Professor

My passion lies in the future of robots coexist with human-beings
where I enjoy developing machine learning methods for this.

I am an assistant professor at the Department of Artificial Intelligence in Korea University. Before joining Korea University, I was a postdoctoral researcher at Disney Research, Los Angeles, from 2018-2020 and a research scientist at Kakao Brain, Korea in 2018. My research interests include, but not limited to, the following areas: Reinforcement Learning, Uncertainty Modeling, Human-Robot-Interaction, and Motion Generation for Animatronics.

I previously received my Ph.D. degree in Electrical Computer Engineering at Seoul National University in Seoul, Korea, advised by Songhwai Oh. Before that, I received my Bachelor’s degree in Electrical Engineering and Computer Sciences at Seoul National University. During my undergraduate years, I worked in Hanool Robotics in Bucheon, Korea, as a software engineer for three years developing robot cleaners.

Perosnal Website

Publications

International Journal

  • Sungjoon Choi and Joohyung Kim, “Cross-Domain Motion Transfer Via Safety-Aware Shared Latent Space Modeling,” IEEE Robotics and Automation Letters (R-AL), 2020

  • Sungjoon Choi, Kyungjae Lee, and Songhwai Oh, “Robust Learning From Demonstrations With Mixed Qualities Using Leveraged Gaussian Processes,” IEEE Transaction on Robotics (T-RO), 2019

  • Kyungjae Lee, Sungjoon Choi, and Songhwai Oh, “Sparse Markov Decision Processes With Causal Sparse Tsallis Entropy Regularization for Reinforcement Learning,” IEEE Robotics and Automation Letters (R-AL), 2018

  • Eunwoo Kim, Sungjoon Choi, Songhwai Oh, “Structured Kernel Subspace Learning for Autonomous Robot Navigation,” SENSORS, 2018

  • Hyemin Ahn, Sungjoon Choi, Nuri Kim, Geonho Cha, and Songhwai Oh, “Interactive Text2Pickup Networks for Natural Language Based Human-Robot Collaboration,” IEEE Robotics and Automation Letters (R-AL), 2018

  • Hyemin Ahn, Yoonseon Oh, Sungjoon Choi, Claire J. Tomlin, and Songhwai Oh, “Online Learning to Approach a Person with No-Regret,” IEEE Robotics and Automation Letters (R-AL), 2018.

  • Sungjoon Choi, Eunwoo Kim, Kyungjae Lee, and Songhwai Oh, “Real-Time Nonparametric Reactive Navigation of Mobile Robots in Dynamic Environments,” Robotics and Autonomous Systems, 2017

  • Sungjoon Choi, Mahdi Jadaliha, Jongeun Choi, and Songhwai Oh, “Distributed Gaussian Process Regression Under Localization Uncertainty,” ASME Journal of Dynamic Systems, Measurement, and Control, 2015.

  • Junghun Suh, Seungil You, Sungjoon Choi, and Songhwai Oh, “Vision-Based Coordinated Localization for Mobile Sensor Networks,” IEEE Transactions on Automation Science and Engineering, 2016.

International Conference

    • Sungjoon Choi, Min Jae Song, Hyemin Ahn, and Joohyung Kim, “Self-Supervised Motion Retargeting with Safety Guarantee,” in Proc. of the IEEE International Conference on Robotics and Applications (ICRA), May 2021.

    • Matthew Pan, Sungjoon Choi, James Kennedy, Kyna McIntosh, Daniel Campos Zamora, Gunter Niemeyer, Joohyung Kim, and Alexis Wieland, “Realistic and Interactive Robot Gaze,” in Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS), Nov 2020.

    • Sungjoon Choi, Matthew Pan, and Joohyung Kim, “Nonparametric Motion Retargeting for Humanoid Robots on Shared Latent Space,” in Robotics: Science and Systems (RSS), July 2020.

    • Kyungjae Lee, Sungyub Kim, Sungbin Lim, Sungjoon Choi, Mineui Hong, Jaein Kim, Yong-Lae Park, and Songhwai Oh, “Generalized Tsallis Entropy Reinforcement Learning and Its Application to Soft Mobile Robots,” in Robotics: Science and Systems (RSS), July 2020.

    • Sungjoon Choi, Sanghoon Hong, Kyungjae Lee, and Sungbin Lim, “Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Network,” in Proc. of Conference on Computer Vision and Pattern Recognition (CVPR), June 2020.

    • Sungjoon Choi and Joohyung Kim, “Cross-Domain Motion Transfer Via Safety-Aware Shared Latent Space Modeling,” in Proc. of the IEEE International Conference on Robotics and Applications (ICRA), May 2020.

    • Sungjoon Choi and Joohyung Kim, “Towards a Natural Motion Generator: a Pipeline to Control a Humanoid based on Motion Data,” in Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS), Nov 2019.

    • Sungjoon Choi and Joohyung Kim, “Trajectory-based Probabilistic Policy Gradient for Learning Locomotion Behaviors,” in Proc. of the IEEE International Conference on Robotics and Applications (ICRA), May 2019.

    • Kyungjae Lee, Sungjoon Choi, and Songhwai Oh, “Maximum Causal Tsallis Entropy Imitation Learning,” in Neural Information Processing Systems (NeurIPS), Dec 2018.

    • Donghoon Lee, Sangdoo Yun, Sungjoon Choi, Hwiyeon Yoo, Ming-Hsuan Yang, and Songhwai Oh, “Unsupervised Holistic Image Generation from Key Local Patches,” in European Conference on Computer Vision (ECCV), Sep 2018.

    • Sungjoon Choi, Kyungjae Lee, Sungbin Lim, and Songhwai Oh, “Uncertainty-Aware Learning from Demonstration Using Mixture Density Networks with Sampling-Free Variance Modeling,” in Proc. of the IEEE International Conference on Robotics and Applications (ICRA), May 2018.

    • Sungjoon Choi, Kyungjae Lee, H. Andy Park, and Songhwai Oh, “A Nonparametric Motion Flow Model for Human Robot Cooperation,” in Proc. of the IEEE International Conference on Robotics and Applications (ICRA), May 2018.

    • Kyungjae Lee, Sungjoon Choi, and Songhwai Oh, “Sparse Markov Decision Processes with Causal Sparse Tsallis Entropy Regularization for Reinforcement Learning,” in Proc. of the IEEE International Conference on Robotics and Applications (ICRA), May 2018.

    • Sungjoon Choi, Kyungjae Lee, and Songhwai Oh, “Scalable Robust Learning from Demonstration with Leveraged Deep Neural Networks,” in Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS), Sep 2017.

    • Hyemin Ahn, Yoonseon Oh, Sungjoon Choi, Claire J. Tomlin, and Songhwai Oh, “Online Learning to Approach a Person with No-Regret,” in Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS), Sep 2017.

    • Sungjoon Choi, Kyungjae Lee, Songhwai Oh, “A Multi-Agent Coverage Algorithm with Connectivity Maintenance,” in Proc. of the IEEE International Conference On Multisensor Fusion and Integration for Intelligent Systems (MFI), Nov 2017

    • Seunggyu Chang, Sungjoon Choi, Songhwai Oh, “Self-Correcting Online Navigation via Leveraged Gaussian Processes,” In Proc. of the International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Jun 2017

    • Sungjoon Choi, Kyungjae Lee, and Songhwai Oh, “Robust Modeling and Prediction in Dynamic Environments Using Recurrent Flow Networks,” in Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS), Oct 2016.

    • Sungjoon Choi, Kyungjae Lee, and Songhwai Oh, “Gaussian Random Paths for RealTime Motion Planning,” in Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS), Oct 2016.

    • Kyungjae Lee, Sungjoon Choi, and Songhwai Oh, “Inverse Reinforcement Learning with Leveraged Gaussian Processes,” in Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS), Oct 2016.

    • Sungjoon Choi, Kyungjae Lee, and Songhwai Oh, “Robust Learning From Demonstration Using Leveraged Gaussian Processes and Sparse Constrained Optimization,” in Proc. of the IEEE International Conference on Robotics and Applications (ICRA), June 2016. (Best Conference Paper Finalist)

    • Eunwoo Kim, Sungjoon Choi, and Songhwai Oh, “Structured Low-Rank Matrix Approximation in Gaussian Process Regression for Autonomous Robot Navigation,” in Proc. of the IEEE International Conference on Robotics and Applications (ICRA), May 2015.

    • Sungjoon Choi, Eunwoo Kim, and Songhwai Oh, “Leveraged Non-Stationary Gaussian Process Regression for Autonomous Robot Navigation,” in Proc. of the IEEE International Conference on Robotics and Applications (ICRA), May 2015.

    • Yoonseon Oh, Sungjoon Choi, and Songhwai Oh, “Chance-Constrained Target Tracking for Mobile Robots,” in Proc. of the IEEE International Conference on Robotics and Applications (ICRA), May 2015.

    • Eunwoo Kim, Sungjoon Choi, and Songhwai Oh, “A Robust Autoregressive Gaussian Process Motion Model Using l 1 -Norm Based Low-Rank Kernel Matrix Approximation,” in Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS), Sep. 2014.

    • Sungjoon Choi, Eunwoo Kim, and Songhwai Oh, “Real-Time Navigation in Crowded Dynamic Environments Using Gaussian Process Motion Control,” in Proc. of the IEEE International Conference on Robotics and Applications (ICRA), May 2014.

    • Sungjoon Choi, Mahdi Jadaliha, Jongeun Choi, Songhwai Oh, “Distributed Gaussian Process Regression for Mobile Sensor Networks Under Localization Uncertainty,” in Proc. of the IEEE Conference on Decision and Control (CDC), Dec. 2013.

    • Sungjoon Choi, Eunwoo Kim, and Songhwai Oh, “Human Behavior Prediction for Smart Homes Using Deep Learning,” in Proc. of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), Aug. 2013.