People

Sungho Shin

Assistant Professor
Department of Chemical Engineering
Massachusetts Institute of Technology
77 Massachusetts Avenue, Room 66-554
Cambridge, MA 02139, USA
[ sushin@mit.edu | 617-715-5740 ]
[ Google Scholar | GitHub | LinkedIn | CV ]

Layla Gonzalez

[ lglez@mit.edu | 617-253-4533 | Room 66-542]

Dirk Lauinger

[ lauinger@mit.edu | Website ]

Dirk Lauinger 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.

David Yang Shu

[ davidshu@mit.edu | Website ]

David Yang Shu is a postdoctoral associate in the Shin Group working on the nonlinear optimal design of carbon capture units under uncertainty. David’s work spans environmental life-cycle assessment, process optimization, and sustainable system design, with applications in carbon capture and storage technologies and the broader energy transition. During his doctoral studies at ETH Zurich (advisor: André Bardow, Department of Mechanical and Process Engineering), David studied the design and operation of net-zero energy systems employing multi-criterial optimization to evaluate trade-offs between economic and environmental objectives. Further, he applied bilevel optimization to model market interactions during the transition to net-zero energy systems. David contributed to the Horizon 2020 project DMX™ Demonstration in Dunkirk (3D) by performing life-cycle assessments for full-scale CCUS supply chains. He also worked on the Swiss demonstration project DemoUpCARMA, focusing on carbon dioxide transportation. David earned his M.S. in Energy Engineering at RWTH Aachen University in 2018 with a thesis on the operational optimization of industrial energy systems and his B.S. in Mechanical Engineering at RWTH Aachen University in 2016.

Yurim Kim

[ yurimkim@mit.edu ]

Yurim focuses on formulating and solving mixed-integer nonlinear optimization problems to support operating decisions in hydrogen production systems under uncertainty. Her research project aims to develop cost-effective and low-carbon hydrogen production strategies that are adaptable to various system conditions.

Jiachen Qian

Jiachen Qian is a postdoc researching data center modeling and operations, with an additional focus on modeling and predicting power demand during LLM training, fine-tuning, and inference. Prior to joining the Shin Group, Jiachen was a postdoctoral researcher with Yang Zheng at UC San Diego, where he worked on the theory of model-free prediction for stochastic dynamical systems with partial observations. Together with Yang’s group, he developed regularization methods to mitigate overfitting in online prediction and established theoretical foundations for regret analysis in multi-step-ahead prediction, with applications to data-driven predictive control. Jiachen received his Ph.D. and B.Sc. from Peking University, under the supervision of Zhisheng Duan. His doctoral work focused on distributed state estimation for large-scale systems, including developing a theoretical framework based on coupled Riccati equations to characterize covariance evolution in distributed filtering.

David Jin

[ jindavid@mit.edu | Website ]

David Jin is a PhD student in Computational Science and Engineering (CSE) whose research focuses on GPU-accelerated and distributed methods for large-scale optimization in AI-driven decision-making systems, with applications to robotics and energy. He is supported by the Amazon AI Innovation Fellowship and is broadly interested in how algorithm design and modern hardware can push the frontiers of scalable computation. David completed his undergraduate studies at Caltech in Information and Data Science and Physics. Outside of research, he enjoys playing percussion in symphony and wind ensembles.

Wallace Tan

[ wtgy@mit.edu ]

Wallace Tan is a graduate student who joined the group in 2024. He graduated from the National University of Singapore with a BEng in Chemical Engineering and a 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 is supported by NSF as a Graduate Research Fellow. 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

[ xiaomian@mit.edu ]

Xiaomian is a Ph.D. candidate in Chemical Engineering and the Program in Polymers and Soft Matter (PPSM), who joined the Shin group in January 2025. Her research interests combine control and optimization theory with physics modeling, with applications in batteries and soft matter systems. She is also interested in advancing computational method development and is currently focusing on subspace identification and sample complexity analysis. Prior to joining MIT, Xiaomian earned her B.S. from Stanford University in materials science and engineering and a minor in computer science. Outside of research, you can find her playing the flute, reading science fiction, 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.

Anne Gvozdjak

[ annegv@mit.edu ]

Anne Gvozdjak is a MEng student in Electrical Engineering and Computer Science (EECS) whose research focuses on applying machine learning and physics modeling tools to the grid impacts of large data center loads, with broader interests in grid optimization and decarbonization. Anne received her B.S. from MIT in EECS and Business Analytics. Outside of research, she enjoys reading and writing fiction, watching hockey, and baking sweets.

Joseph Choi

[ jsphchoi@mit.edu ]

Joseph is a Ph.D. student in Chemical Engineering whose research interests include developing scalable modeling frameworks and improving GPU-accelerated nonlinear optimization for multi-scale systems. He joined the Shin Group in January 2026 after graduating from the University of Connecticut with a B.S.E. in Chemical Engineering. In his free time, he enjoys various physical activities including going to the gym, running, and bouldering.

Elliott Slaughter

[ erslaugh@mit.edu ]

Elliott (Ellie) is an undergraduate at MIT, double majoring in computer science and chemical engineering, with broad interests in AI infrastructure, large-scale optimization, and entrepreneurship. Her research is in GPU computing, with a focus on designing efficient algorithms for solving large problems on modern parallel architecture. Ellie is a Goldwater Scholar and active member of MIT’s Sloan Business Club and AI Alignment Club. When she's not working, you can find her cooking fusion dishes, going on runs, and playing an arguably unhealthy amount of NYT puzzles and card games.

Jonggeol Na

[ jgna@ewha.ac.kr ]

Jonggeol Na is an Associate Professor and Ewha Young Fellow in the Department of Chemical Engineering and Materials Science at Ewha Womans University. His research integrates process systems engineering, machine learning, and multiscale simulation to optimize advanced process systems. Currently, his work focuses on solving national-scale supply chain optimization problems linking power and chemical industries. He also heads a Self-Driving Lab in Institute for Multiscale Matter and Systems (IMMS) where he develops an operating system (OS) for autonomous experimental design and optimization. Prior to his current position, he was a postdoctoral fellow at Carnegie Mellon University (advisor: Nick Sahinidis) and a visiting researcher at MIT (advisor: Richard D. Braatz). He received his Ph.D. from Seoul National University (advisor: Won Bo Lee).