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Welcome to the Shin Group website! We are excited to announce our official launch in the Fall 2024 at the Chemical Engineering Department of the Massachusetts Institute of Technology.
Research Overview
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.
Read more about our research >>
Recent News
- Joushua Pulsipher received the best presentation prize at JuMP-dev 2024 for the talk "InfiniteExaModels.jl: Accelerating Infinite-Dimensional Optimization Problems on CPU & GPU", which is based on the collaborative work with Sungho Shin, François Pacaud and Mihai Anitescu. [ Link ]
- Our paper "A graph-based modeling abstraction for optimization: Concepts and implementation in Plasmo.jl" has received the 2022 Outstanding Paper Award of the Mathematical Programming Computation. [ Link ]
- Our paper "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 accepted for publication in PSCC 2024.
- Our paper "Parallel interior-point solver for block-structured nonlinear programs on SIMD/GPU architectures" with F. Pacaud, M. Schanen, D. A. Maldonado, and M. Anitescu has been accepted for publication in Optimization Methods and Software.
- MadNLP and ExaModels team has awarded the COIN-OR Cup! This award recognizes outstanding contributions to open-source operations research software development. [ Link ]
Selected Publications
- 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 ]