Yongxin Chen
Yongxin Chen was born in Ganzhou, Jiangxi, China. He received his B.S. in mechanical engineering from Shanghai Jiao Tong University, China, in 2011, and a Ph.D. degree in mechanical engineering, under the supervision of Tryphon Georgiou, from University of Minnesota in 2016. He currently serves as an assistant professor in the Daniel Guggenheim School of Aerospace Engineering at Georgia Institute of Technology. Before joining Georgia Tech, he had a one-year research fellowship at Memorial Sloan Kettering Cancer Center from August 2016 to August 2017 and was an assistant professor in the Department of Electrical and Computer Engineering at Iowa State University from August 2017 to August 2018.
He has conducted researches in stochastic control, optimal transport and optimization. His current research focuses on the intersection between control, machine learning and robotics with the goal to develop theoretical foundations and algorithms for robots so that they are able to accomplish complex tasks autonomously and reliably.
Professor Chen's teaching interests encompass foundational and advanced topics in aerospace engineering, including control systems, dynamics, optimization, and machine learning at undergraduate and graduate levels. He emphasizes developing students' analytical and computational skills while fostering understanding of systems theory and control applications relevant to aerospace systems. His instruction integrates theoretical concepts with practical problem-solving to prepare students for research and industry challenges.
Professor Chen’s research interests lie at the intersection of control, machine learning and robotics. He has conducted research on diverse topics, including stochastic control, generative modeling, reinforcement learning, optimal transport, Markov chain Monte Carlo etc. His contributions span theory, algorithm development, and applications. He enjoys developing new algorithms and theoretical frameworks for real world applications.
Lab/Collaborations:
- Foundations of Learning And Intelligent Robots (FLAIR)
- Decision and Control Laboratory (DCL)
- Institute for Robotics and Intelligent Machines (IRIM)
Disciplines:
- Flight Mechanics & Controls
AE Multidisciplinary Research Areas:
- Robotics, Autonomy, and Human Interactions
B.S., Mechanical Engineering, 2011, Shanghai Jiao Tong University
Ph.D., Mechanical Engineering, 2016, University of Minnesota
- George S. Axelby Best Paper Award, IEEE Transaction on Automatic Control, 2017
- Doctoral Dissertation Fellowship, University of Minnesota, 2015-2016
- A.V. Balakrishnan Early Career Award for Excellence in Scientific Research, 2021
- Donald P. Eckman Award, American Automatic Control Council, 2022
- Z Liu, S Jafarpour, Y Chen, Probabilistic Reachability Analysis of Stochastic Control Systems, IEEE Transactions on Automatic Control, 2025
- Z Liu, S Jafarpour, Y Chen, Safety Verification of Nonlinear Stochastic Systems via Probabilistic Tube, IEEE Transactions on Automatic Control, 2025
- G Liu, J Choi, Y Chen, B Miller, R Chen, Adjoint Schrödinger Bridge Sampler, Conference on Neural Information Processing Systems, 2025
- U Mishra, D He, Y Chen, D Xu, Compositional Diffusion with Guided search for Long-Horizon Planning, International Conference on Learning Representations, 2026
- W Guo, J Choi, Y Zhu, M Tao, Y Chen, Proximal Diffusion Neural Sampler, International Conference on Learning Representations, 2026