I am a Computational Mathematician in Laboratory for Applied Mathematics, Numerical Software, and Statistics, Mathematics and Computer Science Division at Argonne National Laboratory, and a Senior Scientist at-Large at the University of Chicago Consortium for Advanced Science and Engineering. My primary research focus is on optimization modeling and solutions for large-scale optimization (in particular, stochastic optimization and distributed optimization) capable of running on high performance computing systems, in applications to complex energy systems and distributed learning. Before joining Argonne, I obtained a Ph.D. degree in Industrial Engineering and Management Sciences from Northwestern University (my academic tree). I am a recipient of DOE Early Career Research Program award. I serve as associate editors in Mathematical Programming Computation and Naval Research Logistics and board members for COIN-OR Foundation and IISE Energy Systems.
My research in a few words (Last update: November, 2023):
Active Projects
- Scalable and Resilient Modeling for Federated-Learning-Based Complex Workflows
- Privacy-Preserving Federated Learning on Multimodal Data
- Randomized Algorithms for Solving Massive Discrete Optimization Problems
- PALISADE-X: Privacy Preserving Analysis and Learning in Secure and Distributed Enclaves and Exascale Systems
- Data-Driven Optimization under Uncertainty: Parallel Algorithms and Solver
- ExaSGD: Optimizing Stochastic Grid Dynamics at Exascale
- Advanced Grid Modeling
Awards and Honors
- IEEE Senior Member, 2022
- IMPACT Argonne Award (Computing, Environment and Life Sciences directorate), September 2021
- IMPACT Argonne Award (Energy and Global Security directorate), August 2021
- Early Career Research Program, US Department of Energy, 2019
- George L. Nemhauser Best Student Paper, Northwestern University, 2014
- Best Poster Award (selected among nearly 2,000 posters), American College of Cardiology’s 61st Annual Scientific Session & Expo, 2012
Media
- SIAG/OPT Views and News, Dec 2021
- Banishing blackouts, Oct 2020
- How does AI improve grid performance? No one fully understands and that’s limiting its use, Nov 2019
- New funding awarded to two early career scientists, Aug 2019
- Artificial Intelligence Can Make the U.S. Electric Grid Smarter, Jun 2019
Advisees
Postdoctoral Appointees
- Yijiang Li (2023–present)
- Charikleia Iakovidou (2022–present)
- Hideaki Nakao (2021–present)
- Minseok Ryu (2020–2023)
- Geunyeong Byeon (2020)
- Bowen Li (2019–2023; with Sven Leyffer)
- Anirudh Subramanyam (2018–2022; with Mihai Anitescu)
- Brian Dandurand (2017–2020)
Predoctoral Appointees
- Miao Li (2022–2023; with Mihai Anitescu)
- Yuxuan Ren (2021–2022; with Mihai Anitescu)
- Jisung Hwang (2020–2021; with Mihai Anitescu)
Ph.D. Interns
- Shourya Bose (UC Santa Clara, 2023) ; Weiqi Zhang (University of Wisconsin-Madison, 2022) ; Rachael Alfant (Rice University, 2022) ; Nick Dodd (Arizona State University, 2022) ; Jiaze Ma (University of Wisconsin-Madison, 2022) ; Ashutosh Shukla (University of Texas-Austin, 2022) ; Sayed A. Sadat (University of Utah, 2021) ; Sihan Zeng (Georgia Tech, 2021) ; Haoming Shen (University of Michigan, 2021) ; Can Li (Carnegie Mellon University, 2020) ; Sayed A. Sadat (University of Utah, 2020) ; Weiqi Zhang (University of Wisconsin, 2020) ; Hideaki Nakao (University of Michigan, 2020) ; Yingqiu Zhang (Virginia Tech, 2020) ; Junyi Tu (University of South Florida, 2019; with Michel Schanen) ; Jie Zhang (Virginia Tech, 2019) ; Mohamed El Tonbari (Georgia Tech, 2019, 2018) ; Cheolmin Kim (Northwestern University, 2018) ; Rui Ray Liu (Georgia Tech, 2018; with Mihai Anitescu) ; Liu Su (University of South Florida, 2018) ; Youngkyu Cho (Pohang University of Science and Technology, Korea, 2018) ; Gokce Kahvecioglu (Northwestern University, 2016) ; Jordan Jalving (University of Wisconsin-Madison, 2016) ; Christian Tjandraatmadja (Carnegie Mellon University, 2015)