Publications
Group highlights
(For a full list see below or go to Google Scholar, ResearchGate.
One of the primary barriers to deploying optimization or machine learning models in practice is the challenge of helping practitioners understand and interpret such models. We propose a first-of-its-kind system that enables natural language-based diagnosis and troubleshooting for infeasible optimization models using LLM.
Chen, H., Constante-Flores, G. E., & Li, C.
INFOR: Information Systems and Operational Research, 62(4), 573-587(2024)
Physics-informed neural network (PINN) leverages known physical constraints present in the data, but it cannot strictly satisfy them in the predictions. We propose an architecture to rigorously guarantee hard linear equality constraints through projection layers derived from KKT conditions.
Chen, H., Constante-Flores, G., & Li, C.
Computers & Chemical Engineering, 189, 108764(2024)
Electrification is a potential solution to alleviate the greenhouse gas emissions of chemical industries. However, spatial and temporal variations complicate the adoption of renewable energy. We propose a multi-scale MILP model for locating modular electrified plants, renewable-based generating units, and power lines in a microgrid.
Ramanujam, A., Constante-Flores, G., & Li, C.
AIChE Journal, 69(12), e18265.(2023)
Full List
scChat: A Large Language Model-Powered Co-Pilot for Contextualized Single-Cell RNA Sequencing Analysis
Chiu, H.-H., Varghese, A., Shao, K., Lu, Y.-C., Nahar, R., Chen, H., Deng, Q., Bao, X., & Li, C.
AIChE Journal, 72(6), e70285(2026)
Paper
Solving Max-Cut to Global Optimality via Feasibility-Preserving Graph Neural Networks
Chen, H., Qian, C., Morris, C., Lodi, A., & Li, C.
arXiv(2026)
Paper
A Tutorial on Multi-time Scale Optimization Models and Algorithms
Ramanujam, A., & Li, C.
Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties(2026)
Paper
SafeOR-Gym: A Benchmark Suite for Safe Reinforcement Learning Algorithms on Practical Operations Research Problems
Ramanujam, A., El Youmi, A., Chen, H., Kompalli, S. M., Ahluwalia, A. S., Pal, S., Papageorgiou, D. J., & Li, C.
Transactions on Machine Learning Research(2026)
Paper
TalkToAgent: A Multi-Agent LLM Framework for Natural Language Explanation of Reinforcement Learning Policies
Kim, H., Chen, H., Li, C., & Lee, J. M.
Computers & Chemical Engineering, 211, 109672(2026)
Paper
Model-Free Reinforcement Learning for Optimal Control of Switched Systems
Zhang, C., Li, C., & Mou, S.
IEEE Transactions on Automation Science and Engineering, 23, 8022-8033(2026)
Paper
A Quadratically-Constrained Convex Approximation for the AC Optimal Power Flow
Constante-Flores, G., & Li, C.
Optimization and Engineering(2026)
Paper
Self-Supervised Learning of Parametric Approximation for Security-Constrained DC-OPF
Anrrango, A., Quisaguano, A., Constante-Flores, G. E., & Li, C.
arXiv(2026)
Paper
DisjunctiveNet: Neural Symbolic Learning via Differentiable Convexified Optimization Layers
Pal, S., & Li, C.
Proceedings of the 43rd International Conference on Machine Learning (ICML 2026)(2026)
Preprint
Conformalized prediction of post-fault voltage trajectories using pre-trained and finetuned attention-driven neural operators
Mollaali, A., Zufferey, G., Constante-Flores, G., Moya, C., Li, C., Yue, M., & Lin, G.
Neural Networks, 192, 107809(2025)
Paper
OptiChat: Bridging Optimization Models and Practitioners with Large Language Models
Chen, H., Constante-Flores, G. E., Mantri, K. S. I., Kompalli, S. M., Ahluwalia, A. S., & Li, C.
INFORMS Journal on Data Science(2025)
Paper
Enforcing Hard Linear Constraints in Deep Learning Models with Decision Rules
Constante-Flores, G. E., Chen, H., & Li, C.
NeurIPS 2025(2025)
Paper
PAMSO: Parametric Autotuning Multi-time Scale Optimization Algorithm
Ramanujam, A., & Li, C.
Computers & Chemical Engineering, 200, 109160(2025)
Paper
FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis
Khan, A., Nahar, R., Chen, H., Constante-Flores, G. E., & Li, C.
Computers & Chemical Engineering, 199, 109152(2025)
Paper
Breaking Data Silos in Drug Discovery with Federated Learning
Li, C.
Nature Chemical Engineering, 2(5), 288-289(2025)
Paper
Solution Polishing via Path Relinking for Continuous Black-Box Optimization
Papageorgiou, D. J., Kronqvist, J., Ramanujam, A., Kor, J., Kim, Y., & Li, C.
Optimization Letters, 19(3), 463-504(2025)
Paper
Enhanced Outer-Approximation Methods for MINLP via Convexification and Bound Tightening
Peng, Z., Cao, K., Furman, K. C., Li, C., Grossmann, I. E., & Bernal Neira, D. E.
Submitted for publication(2025)
Paper
AC-Network-Informed DC Optimal Power Flow for Electricity Markets
Constante-Flores, G. E., Quisaguano, A. H., Conejo, A. J., & Li, C.
Proceedings of the 58th Hawaii International Conference on System Sciences(2025)
Paper
Diagnosing Infeasible Optimization Problems Using Large Language Models
Chen, H., Constante-Flores, G. E., & Li, C.
INFOR: Information Systems and Operational Research, 62(4), 573-587(2024)
Paper
Preprint
Physics-Informed Neural Networks with Hard Linear Equality Constraints
Chen, H., Constante-Flores, G., & Li, C.
Computers & Chemical Engineering, 189, 108764(2024)
Paper
A Convexication-Based Outer-Approximation Method for Convex and Nonconvex MINLP
Peng, Z., Cao, K., Furman, K. C., Li, C., Grossmann, I. E., & Bernal Neira, D. E.
Computer Aided Chemical Engineering, 53, 3211-3216(2024)
Paper
Distributed manufacturing for electrified chemical processes in a microgrid
Ramanujam, A., Constante-Flores, G., & Li, C.
AIChE Journal, 69(12), e18265.(2023)
Paper
Preprint
Recent Advances and Challenges in Optimization Models for Expansion Planning of Power Systems and Reliability Optimization
Cho, S., Li, C., & Grossmann, I. E.
Computers & Chemical Engineering, 165, 107924(2022)
Paper
Preprint
Engineering Chimeric Antigen Receptor Neutrophils from Human Pluripotent Stem Cells for Targeted Cancer Immunotherapy
Chang, Y., Syahirah, R., Wang, X., Jin, G., Torregrosa-Allen, S., Elzey, B. D., Hummel, S. N., Wang, T., Li, C., Lian, X., Deng, Q., Broxmeyer, H. E., & Bao, X.
Cell Reports, 40(3), 111128(2022)
Paper
On Representative Day Selection for Capacity Expansion Planning of Power Systems Under Extreme Operating Conditions
Li, C., Conejo, A. J., Siirola, J. D., & Grossmann, I. E.
International Journal of Electrical Power & Energy Systems, 137, 107697(2022)
Paper
Preprint
Slides
A Review on the Performance of Linear and Mixed Integer Two-Stage Stochastic Programming Software
Torres, J. J., Li, C., Apap, R. M., & Grossmann, I. E.
Algorithms, 15(4), 103(2022)
Paper
Mixed-Integer Linear Programming Models and Algorithms for Generation and Transmission Expansion Planning of Power Systems
Li, C., Conejo, A. J., Liu, P., Omell, B. P., Siirola, J. D., & Grossmann, I. E.
European Journal of Operational Research, 297(3), 1071-1082(2022)
Paper
Preprint
Slides
Shale Gas Field Development Planning Under Production Profile Uncertainty
Peng, Z., Li, C., Grossmann, I. E., Kwon, K., Ko, S., Shin, J., & Feng, Y.
AIChE Journal, 68(1), e17439(2022)
Paper
Sample Average Approximation for Stochastic Nonconvex Mixed Integer Nonlinear Programming via Outer-Approximation
Li, C., Bernal, D. E., Furman, K. C., Duran, M. A., & Grossmann, I. E.
Optimization and Engineering, 22(3), 1245-1273(2021)
Paper
Multi-Period Design and Planning Model of Shale Gas Field Development
Peng, Z., Li, C., Grossmann, I. E., Kwon, K., Ko, S., Shin, J., & Feng, Y.
AIChE Journal, 67(8), e17195(2021)
Paper
Algorithmic Approaches to Inventory Management Optimization
Perez, H. D., Hubbs, C. D., Li, C., & Grossmann, I. E.
Processes, 9(1), 102(2021)
Paper
A Review of Stochastic Programming Methods for Optimization of Process Systems Under Uncertainty
Li, C., & Grossmann, I. E.
Frontiers in Chemical Engineering, 2, 34(2021)
Paper
Preprint
A deep reinforcement learning approach for chemical production scheduling
Hubbs, C. D., Li, C., Sahinidis, N. V., Grossmann, I. E., & Wassick, J. M.
Computers & Chemical Engineering, 141, 106982(2020)
Paper
Shale gas pad development planning under price uncertainty
Li, C., Eason, J. P., Drouven, M. G., & Grossmann, I. E.
AIChE Journal, 66(6), e16933(2020)
Paper
Preprint
Slides
A generalized Benders decomposition-based branch and cut algorithm for two-stage stochastic programs with nonconvex constraints and mixed-binary first and second stage variables
Li, C., & Grossmann, I. E.
Journal of Global Optimization, 75, 247–272(2019)
Paper
Preprint
Slides
A finite ϵ-convergence algorithm for two-stage stochastic convex nonlinear programs with mixed-binary first and second-stage variables
Li, C., & Grossmann, I. E.
Journal of Global Optimization, 75(4), 921-947(2019)
Paper
Preprint
Slides
Global Optimization Algorithm for Multi-period Design and Planning of Centralized and Distributed Manufacturing Networks
Lara, C. L., Bernal, D. E., Li, C., & Grossmann, I. E.
Computers & Chemical Engineering, 127, 295-310(2019)
Paper
Preprint
An improved L-shaped method for two-stage convex 0–1 mixed integer nonlinear stochastic programs
Li, C., & Grossmann, I. E.
Computers & Chemical Engineering, 112, 165-179(2018)
Paper
Preprint
Sequence-Based Prediction of Cysteine Reactivity Using Machine Learning
Wang, H., Chen, X., Li, C., Liu, Y., Yang, F., & Wang, C.
Biochemistry, 57(4), 451-460(2018)
Paper