We are actively seeking talents to join our research group. Positions are open for postdocs, PhD students, undergraduates, and visiting researchers, beginning in the Fall of 2024.
Our research group is dedicated to tackling the mathematical, computational, and practical challenges involved in making systematic decisions in complex systems. We strive to make contributions in the fields of mathematical optimization, control theory, machine learning, process systems engineering, and energy systems.
Here are some of our specific research interests:
- Developing scalable algorithms capable of addressing challenging decision-making problems in various engineering and society domains.
- Advancing our understanding and developing algorithms for machine learning methods in control problems.
- Building computational infrastructure for scalable and data-driven decision-making by harnessing the capabilities of modern high-performance computing, particularly through the use of GPU computing.
- Making tangible impacts in decision-making practices within the domains of process systems engineering and energy systems by introducing new modeling paradigms, algorithms, and software tools.
- MadNLP and ExaModels team has awarded the COIN-OR Cup! This award recognizes outstanding contributions to open-source operations research software development. [ Link ]
- Sungho has received the W. David Smith, Jr. Graduate Publication Award for his paper "Exponential decay of sensitivity in graph-structured nonlinear programs" coauthored with M. Anitescu and V. M. Zavala, published in SIAM Journal on Optimization. [ Link ]
- A new preprint titled "Accelerating optimal power flow with GPUs: SIMD abstraction of nonlinear programs and condensed-space interior-point methods" with F. Pacaud and M. Anitescu has been posted on arXiv [ Link ].
- Our paper "Accelerating condensed interior-point methods on SIMD/GPU architectures" with F. Pacaud, M. Schanen, D. A. Maldonado, M. Anitescu has been published in Journal of Optimization Theory and Applications. [ Link ]
- Our paper "Near-optimal distributed linear-quadratic regulator for networked systems" with Y. Lin, G. Qu, A. Wierman, and M. Anitescu has been published in SIAM Journal on Control and Optimization. [ Link ]
- S. Shin, M. Anitescu, and V. M. Zavala. Exponential decay of sensitivity in graph-structured nonlinear programs. SIAM Journal on Optimization, 32(2):1156--1183, 2022. [ DOI | arXiv ]
- S. Shin, Y. Lin, G. Qu, A. Wierman, and M. Anitescu. Near-optimal distributed linear-quadratic regulator for networked systems. SIAM Journal on Control and Optimization, 61(3):1113--1135, 2023. [ DOI | arXiv ]
- S. Shin, F. Pacaud, and M. Anitescu. Accelerating optimal power flow with GPUs: SIMD abstraction of nonlinear programs and condensed-space interior-point methods. [ arXiv ]