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 ]

Alina Haverty

[ haverty@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.

Shaohui Liu

[ shaohuil@mit.edu ]

Shaohui Liu 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 at Stony Brook University and obtained his master’s degree in Computational Applied Math. He received his B.Sc. in applied mathematics with honors 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.

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.

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.

Byeongchan Ahn

[ abc42779@mit.edu ]

Byeongchan Ahn is a Ph.D. student in Chemical and Biological Engineering at Korea University (advisor: Wangyun Won). He received his bachelor's degree in Chemical Engineering from Kyung Hee University. His previous research has focused on sustainable process development and comprehensive evaluation methods, including techno-economic analysis and life cycle assessment. He has applied these approaches to various fields such as liquid organic hydrogen carriers (LOHC), CO₂ capture using dry sorbents, microalgae-based systems, and waste plastic upcycling. He is currently conducting research on the optimization of hydrogen supply chains based on LOHC, utilizing mixed-integer linear programming (MILP) models.

Archim Jhunjhunwala

[ archimj@mit.edu ]

Archim is a high school student who joined the group as a HIP-SAT intern in summer 2025, and is continuing his research since the end of the internship program. Archim is broadly interested in computer science, especially mathematical optimization and compilers. Outside of lab, Archim enjoys rock climbing, Rubik's cubes, and chess.

Jeongdong Kim

[ jdong96@mit.edu ]

Jeongdong's current research focuses on applying mathematical programming and machine learning to tackle stochastic optimization challenges in the co-optimization of renewable power management systems. His work particularly emphasizes the role of reinforcement learning for energy storage sizing and the dynamic operation of power-to-fuel systems under region-specific renewable uncertainty. He received his Ph.D. in Chemical and Biomolecular Engineering from Yonsei University (advised by Prof. Il Moon) and received his B.Sc. in Chemical Engineering from Sungkyunkwan University.

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.