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. (2024). Safe Reinforcement Learning to Make Decisions in Robotics. (PhD Dissertation)

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. (2020). Motion Planning for an Unmanned Surface Vehicle in Complex Environments. (Master Thesis with distinction)

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.

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