Selected Publications

  • Gu, S*., Shi, L*., Wen, M., Jin, M., Mazumdar, E., Chi, Y., Wierman, A., Spanos, C.. (2025). Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning. ICLR 2025.

  • Gu, S., Sel, B., Ding, Y., Wang, L., Lin, Q., Knoll, A., & Jin, M. (2025). Safe and Balanced: A Framework for Constrained Multi-Objective Reinforcement Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence.

  • Gu, S., Knoll, A., & Jin, M. (2024). TeaMs-RL: Teaching LLMs to Generate Better Instruction Datasets via Reinforcement Learning. Transactions on Machine Learning Research.

  • Gu*, S., Shi*, L., Ding, Y., Knoll, A., Spanos, C., Wierman, A., & Jin, M. (2024). Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation. NeurIPS.

  • Gu, S., Yang, L., Du, Y., Chen, G., Walter, F., Wang, J., & Knoll, A. (2024). A review of safe reinforcement learning: Methods, theory and applications. IEEE Transactions on Pattern Analysis and Machine Intelligence.

  • Zheng, Z., & Gu*, S. (2024). Safe Multi-Agent Reinforcement Learning with Bilevel Optimization in Autonomous Driving. IEEE Transactions on Artificial Intelligence.

  • Gu, S., Liu, P., Kshirsagar, A., Chen, G., Peters, J., Knoll, A. (2024). ROSCOM: Robust Safe Reinforcement Learning on a Stochastic Constraint Manifolds. IEEE Transactions on Automation Science and Engineering.

  • Gu, S., Huang, D., Wen, M., Chen, G., Knoll, A. (2024). Safe Multi-Agent Learning with Soft Constrained Policy Optimization in Real Robot Control. IEEE Transactions on Industrial Informatics.

  • Gu, S., Bilgehan S., Ding, Y., Wang, L., Lin, Q., Jin, M., Knoll, A. (2024). Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation. AAAI 2024 (Oral paper).

  • Gu, S., Kuba, J. G., Chen, Y., Du, Y., Yang, L., Knoll, A., & Yang, Y. (2023). Safe multi-agent reinforcement learning for multi-robot control. Artificial Intelligence, 319, 103905.

  • Gu, S., Kshirsagar, A., Du, Y., Chen, G., Peters, J., & Knoll, A. (2023). A human-centered safe robot reinforcement learning framework with interactive behaviors. Frontiers in Neurorobotics, 17.

  • Gu, S., Chen, G., Zhang, L., Hou, J., Hu, Y., & Knoll, A. (2022). Constrained Reinforcement Learning for Vehicle Motion Planning with Topological Reachability Analysis. Robotics, 11(4), 81. (Editor selected paper).

  • Gu, S., Zhu, M., Chen, G., Wen, Y., & Knoll, A. (2022). Computing position error margin for a USV due to wind and current with a trajectory model. Ocean Engineering, 262, 111950. (Top Journal in this area).

  • Gu, S., Zhou, C., Wen, Y., Xiao, C., & Knoll, A. (2022). Motion Planning for an Unmanned Surface Vehicle with Wind and Current Effects. Journal of Marine Science and Engineering, 10(3), 420.

  • Zhou, C., Gu*, S., Wen, Y*., Du, Z., Xiao, C., Huang, L., & Zhu, M. (2020). The review unmanned surface vehicle path planning: Based on multi-modality constraint. Ocean Engineering, 200, 107043. (Corresponding author, Top Journal in this area).

  • Zhou, C., Gu*, S., Wen, Y*., Du, Z., Xiao, C., Huang, L., & Zhu, M. (2020). Motion planning for an unmanned surface vehicle based on topological position maps. Ocean Engineering, 198, 106798. (Corresponding author, Top Journal in this area).

  • Gu, S., Zhou, C., Wen, Y., Zhong, X., Zhu, M., Xiao, C., & Du, Z. (2020). A motion planning method for unmanned surface vehicle in restricted waters. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 234(2), 332-345.

  • Gu, S., Zhou, C., Wen, Y., Xiao, C., Du, Z., & Huang, L. (2019). Path Search of Unmanned Surface Vehicle Based on Topological Location. Navigation of China, 42(02), 52-58.

For more details, please see Google Scholar.

Thesis

  • Gu, S. (2024). Safe Reinforcement Learning to Make Decisions in Robotics. (PhD Dissertation, Bosch AIoT Scholarship).

  • Gu, S. (2020). Motion Planning for an Unmanned Surface Vehicle in Complex Environments. (Master Thesis with distinction: Top 1%).

  • Gu, S. (2017). A Cooperative Model of Private Cars in Uncertain Environments. (Bachelor Thesis with distinction: Top 3%).