PhD, Massachusetts Institute of Technology (2013)

BChE, University of Minnesota – Twin Cities (2007)

Bio

Dr. Stuber is a Pratt & Whitney Associate Professor in Advanced Systems Engineering with the Dept. of Chemical & Biomolecular Engineering and the Institute for Advanced Systems Engineering at the University of Connecticut. He received his PhD from the Massachusetts Institute of Technology and his BS from the University of Minnesota – Twin cities, both in chemical engineering. In his post-doctoral work, he cofounded a water-tech start-up company focusing on developing flexible high-efficiency solar-driven desalination technologies for diverse applications where membrane technologies prove inadequate. At UConn, his core research focus is on optimization theory, methods, and software for modeling and simulation, robust simulation and design, and controls and operations. His application interests lie in addressing challenging and timely applications from a spectrum of industries including food, energy, water and natural resources, chemicals, finance, and healthcare. The systems-level thinking combined with quantitative rigor enables the development of novel solutions to emerging and intractable problems across these diverse areas.

Current Research

• Process systems engineering: optimal design, design under uncertainty
• Global optimization, theory and software
• Process improvement and intensification
• Renewable energy and process integration
• Desalination and water treatment

Previous Positions

• 2012-2016 Co-founder and director, WaterFX, Inc.

Awards and Honors

• AIChE CAST Division W. David Smith Jr. Graduate Publication Award (2018)
• Journal of Global Optimization Best Paper Award (2012)

Selected Publications

1. Gottlieb, R.X. and Stuber, M.D. Automatic Generation of GPU Kernels for Evaluators of McCormick-Based Relaxations and Subgradients. Mathematical Programming Computation. (2026). DOI: 10.1007/s12532-026-00339-w
2. Alston, D., Choi, J.W., Xu, P., and Stuber, M.D. EOptInterface.jl: Equation-Oriented Optimization Interface in Julia. Industrial & Engineering Chemistry Research. 65(26), 13847-13861 (2026). DOI: 10.1021/acs.iecr.6c00186
3. Martin, J.D., Toh, K., Martin, M.R., Chen, P., Wang, C., Igarashi, K., Mpekris, F., Stylianopoulos, T., Stuber, M.D., Kataoka, K., and Cabral, H. Bone Marrow Vessels are Hyperpermeable to Macromolecules and Nanoscale Medicine in a Size-Dependent Manner. Journal of Controlled Release. 382:113669 (2025). DOI: 10.1016/j.jconrel.2025.113669
4. Gottlieb, R.X., Xu, P., and Stuber, M.D. Automatic Source Code Generation for Deterministic Global Optimization With Parallel Architectures. Optimization Methods & Software. 41(2), 308-346 (2024). DOI: 10.1080/10556788.2024.2396297
5. Nikkhah, H., Beykal, B., and Stuber, M.D. Comparative Life Cycle Assessment of Single-Use Cardiopulmonary Bypass Devices. Journal of Cleaner Production. 425, 138815 (2023). DOI: 10.1016/j.jclepro.2023.138815
6. Rastinejad, J., Putnam, S., and Stuber, M.D. Technoeconomic Assessment of Solar Technologies for the Hybridization of Industrial Process Heat Systems Using Deterministic Global Dynamic Optimization. Renewable Energy. 216, 119069 (2023). DOI: 10.1016/j.renene.2023.119069
7. Wilhelm, M.E., and Stuber, M.D. Improved Convex and Concave Relaxations of Composite Bilinear Forms. Journal of Optimization Theory and Applications. 197, 174-204 (2023). DOI: 10.1007/s10957-023-02196-2
8. Wilhelm, M.E., Wang, C., and Stuber, M.D. Convex and Concave Envelopes of Artificial Neural Network Activation Functions. Journal of Global Optimization. 85, 569-594 (2023). DOI: 10.1007/s10898-022-01228-x
9. Wang, C., Degnan-Morgenstern, S., Martin, J.D., and Stuber, M.D. Optimal Therapy Design With Tumor Microenvironment Normalization. AIChE Journal. e17747 (2022). DOI: 10.1002/aic.17747
10. Wang, C., Wilhelm, M.E., and Stuber, M.D. Semi-Infinite Optimization with Hybrid Models. Industrial & Engineering Chemistry Research. 61, 5239-5254 (2022). DOI: 10.1021/acs.iecr.2c00113