People

Principal Investigator

Sungho Shin

Affiliations

Education and Training

Postdoc, Mathematics and Computer Science Division, Argonne National Laboratory
Ph. D. in Chemical Engineering, University of Wisconsin-Madison
B.S. in Mathematics and Chemical Engineering, Seoul National University

Bio

Sungho Shin is a Texaco-Mangelsdorf Career Development Chair Assistant Professor of the Chemical Engineering Department at Massachusetts Institute of Technology. Prior to joining MIT, he was a postdoctoral researcher at the Mathematics and Computer Science Division at Argonne National Laboratory (supervisor: Mihai Anitescu). He received his Ph.D. from the University of Wisconsin-Madison (advisor: Victor M. Zavala). He was a Summer intern at Los Alamos National Laboratory (2020; worked with Carleton Coffrin and Kaarthik Sundar) and Argonne National Laboratory (2018; worked with Mihai Anitescu). He was an undergraduate researcher at Jong Min Lee's group at Seoul National University. His research interests include model predictive control, optimization algorithms, and their applications to large-scale energy infrastructures (such as natural gas and power networks). He is the main developer of the nonlinear optimization solver MadNLP.jl and the automatic differentiation/algebraic modeling tool ExaModels.jl. He was the winner of the W. David Smith, Jr. Graduate Publication Award, AIChE Annual Meeting CAST Directors’ Student Presentation Award, IFAC ADCHEM Young Author Award, IFAC NMPC Young Author Award. He was a recipient of the Korea Presidential Science Fellowship, Kwanjeong Fellowship, and Grainger Wisconsin Distinguished Graduate Fellowship.

Postdoctoral Associates

Dirk Lauinger

[ lauinger@mit.edu | Website ]

Dirk is a postdoc researching mathematical optimization techniques for the planning and operation of sustainable and reliable energy and mobility systems. Spanning the disciplines of operations research, energy engineering, and industrial ecology, his research finds applications in renewable energy integration, energy storage, electric transportation, energy and material supply security, global material cycles, resource economics, and policy analysis. Prior to joining the Shin group, Dirk was a postdoc with Andy Sun at MIT Sloan and MITEI. Together with Andy's group, he developed decomposition procedures for large-scale AC optimal power flow problems with unit commitment and ranked second in terms of overall prize money in the third edition of the Grid Optimization challenge organized by the US DOE. He obtained his PhD, MSc, and BSc from EPFL.

Flemming Holtorf

holtorf@mit.edu

Flemming is a postdoctoral associate in the Shin group working on advanced decision-support tools for the operation of battery systems. Flemming’s research interest lies in control and optimization theory, applied statistics, as well as stochastic processes and modeling. A core theme of his work is to leverage theory to devise numerical methods and build computational tools to support decision-making under uncertainty and at scale. His research has found applications in domains as diverse as quantum information science, space weather forecasting, stochastic chemical modeling, and now predominantly energy and process systems engineering. Prior to joining the Shin group, Flemming received a PhD from MIT (advisor: Alan Edelman, MIT Math/CSAIL), an MS degree from RWTH Aachen University (advisors: Alexander Mitsos, RWTH MechE and Lorenz Biegler, CMU ChemE), and a BS degree from RWTH, where he also served as an undergraduate researcher (advisor: Alexander Mitsos, RWTH MechE). His MS thesis research conducted as a visiting researcher in the Biegler group at Carnegie Mellon University was awarded the Friedrich-Wilhelm Prize.

Shaohui Liu

(co-advised with Pablo Duenas-Martinez)

shaohuil@mit.edu

Shaohui is a postdoctoral associate in the Shin group working on demand response in decarbonized utility-scale energy systems. Shaohui’s current research focuses on using computational mathematics and machine learning tools to tackle challenging optimization and control problems in electric power grids. Prior to joining the Shin group at MIT, he received his Ph.D. in Electrical and Computer Engineering from the University of Texas at Austin (advisor: Hao Zhu). Before joining UT, he spent 2 years as a PhD student in Stony Brook University and got his master’s degree in Computational Applied Math. He received his B.Sc. in applied mathematics with honor from Sichuan University (advisor: Hao Wang). Shaohui was a summer intern with Los Alamos National Lab (mentors: Misha Chertkov and Deepjyoti Deka), Argonne National Lab (mentor: Emil Constantinescu), and Amazon AWS.

Graduate Students

David Jin

jindavid@mit.edu

David is a graduate student focused on designing GPU solvers for nonlinear optimization and using learning techniques to improve these optimizations. His broader research interest is in accelerating calculations using specific algorithms tailored for particular hardware, such as GPUs. He is particularly interested in sum-of-squares programming and semidefinite programming, with applications in robotics. David holds a B.S. in Information and Data Science from Caltech and a B.A. in Physics from Grinnell College. In his spare time, he enjoys playing percussion in both a symphony orchestra and a wind ensemble.

Wallace Tan

(co-advised with Richard Braatz)

wtgy@mit.edu

Wallace Tan is a graduate student who joined the group in 2024. He graduated from the National University of Singapore with BEng in Chemical Engineering and BSc in Mathematics. He is broadly interested in applied and computational mathematics, with a particular focus on stochastic systems and control. Outside of the lab, his hobbies include hitting the gym, competitive bowling, and Chinese chess (xiangqi).

Sanjay Johnson

sanjayjo@mit.edu

Sanjay is a graduate student researching grid-level energy systems and how optimization can allow new and existing technologies to provide further improvements to the power grid. His broader research interests include modeling for decarbonization and the intersection of public policy with engineering and technology. Sanjay received his B.S. from Carnegie Mellon in Chemical Engineering and Engineering & Public Policy. Outside of the lab, Sanjay enjoys reading, scuba diving, and playing soccer and ultimate frisbee.

Xiaomian Yang

yang@mit.edu

Xiaomian is a Ph.D. student who joined the Shin group in January, 2025. Her research interests combine control and optimization theory with physics modeling for applications in battery energy storage systems. She is also interested in theory and is excited to begin her work on subspace identification and sample complexity methods. Xiaomian graduated from Stanford University with a degree in materials science and engineering and a minor in computer science. Outside of research, you can find her playing the flute, reading science fictions, and learning new board games.

Boxun Huang

boxun667@mit.edu

Boxun is a graduate student working on carbon capture modeling and optimization, with an additional focus on kinetic parameter estimation in reaction systems. He is broadly interested in process system engineering and numerical computation. Prior to joining the group, he obtained a B.S. in Chemical Engineering from the University of Minnesota. Outside of research, Boxun enjoys playing badminton and making cocktails for his friends.

Undergraduate Students

Natalie Chung

chungn05@mit.edu

Natalie is an undergraduate student pursuing a bachelor's degree in Electrical Engineering and Computer Science at MIT. She has an interest in control systems, particularly their applications in energy grid management and optimization. To unwind, she enjoys sketching and crocheting in her free time.

Visiting Students

Geunseo Song

song650@mit.edu

Geunseo Song is a graduate student in the integrated Master's and Ph.D. program in Chemical Engineering at Ewha Womans University (advisor: Jonggeol Na). She received her bachelor's degree in Chemical Engineering at Ewha Womans University. Her previous research focused on optimizing hydrogen supply chain operations using hierarchical multi-agent reinforcement learning. Her research interests include optimization algorithms, machine learning, and their applications to energy systems