Home

photo

Welcome to the Shin Group’s website! We are a research group at the Massachusetts Institute of Technology (MIT), led by Professor Sungho Shin.


Group 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:

Read more about our research >>


Recent News

See more news >>

MadSuite: An Optimization Software Suite for GPUs

MadSuite is a suite of open-source optimization software deisgned to support GPU acceleration. The software tools within this suite encompasses modeling library, optimization solvers, linear system solvers, and additional utility tools. Shin Group is actively contributing to the development of MadSuite.

Learn more about MadSuite >>


PSE Seminar Series

Shin group and Braatz group are co-hosting the MIT Process Systems Engineering Seminar Series. This seminar series features talks by leading researchers in the field of process systems engineering, covering a wide range of topics such as process control, process design, optimization, machine learning, data analytics, and their applications in diverse areas. Open to the public, the seminar series offers a great opportunity to learn about the latest research in process systems engineering. You can receive seminar information by subscribing to our mailing list. We hope to see you at the next seminar!

Learn more about MIT PSE Seminar Series >>


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 ]
See more publications >>