Zifan Wang's Homepage

Zifan Wang Doctoral Student Division of Decision and Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Email: zifanw [@] kth [DOT] se Google Scholar

About me

I am currently a fourth-year Ph.D. student affiliated with Division of Decision and Control Systems (DCS) at KTH Royal Institute of Technology. I am fortunate to jointly work with Prof. Karl H. Johansson at KTH and Prof. Michael M. Zavlanos at Duke University. Before that, I received both the master and bachelor degrees at Honors School of Harbin Institute of Technology.

Research

I am broadly interested in the intersection of control, machine learning, optimal transport, and game theory. I have worked on research topics including distributionally robust optimization, CVaR optimization, distributional reinforcement learning in LQR, decision-dependent optimization. Lately, I have been exploring generative models with a special focus on flow matching models.

News

• 06/2025: I give a talk at ECC Workshop in Thessaloniki, Greece

• 01/2025: I successfully defended Licentiate

• 12/2024: I give a talk at IEEE CDC Workshop at Milan, Italy

• 04/2024: Travel scholarship from Björns Foundation

• 12/2023: I attend IEEE CDC 2023 in Singapore.

• 11/2023: Travel grant from Karl Engvers Foundation

• 09/2023: I attend ELLIIT Symposium on Network Dynamics and Control in Linköping.

• 03/2023: I give a talk at New York University

• 12/2022: I attend IEEE CDC 2022 in Mexico.

• 06/2022: I join KTH DCS as a Doctoral student!!

Selected Publications

• Source-Guided Flow Matching

  • Z. Wang, A. Harting, M. Barreau, M. M. Zavlanos, and K. H. Johansson

• Outlier-Robust Distributionally Robust Optimization via Unbalanced Optimal Transport

  • Z. Wang, Y. Shen, M. M. Zavlanos, and K. H. Johansson

  • NeurIPS-24. Annual Conference on Neural Information Processing Systems, 2024.

• Risk-Averse No-Regret Learning in Online Convex Games

  • Z. Wang, Y. Shen, and M. M. Zavlanos

  • ICML-22. International Conference on Machine Learning, 2022.

• Constrained Optimization with Decision-Dependent Distributions

  • Z. Wang, C. Liu, T. Parisini, M. M. Zavlanos, and K. H. Johansson

  • IEEE Transactions on Automatic Control, 2025.

• Policy Evaluation in Distributional LQR (Extended Version)

  • Z. Wang, Y. Gao, S. Wang, M. M. Zavlanos, A. Abate, and K. H. Johansson

  • IEEE Transactions on Automatic Control, 2025