B. Wayne Bequette

Professor and Technology Manager, CESMII Northern Regional Manufacturing Center, Chemical and Biological Engineering

B. Wayne Bequette is a Professor of Chemical and Biological Engineering and the Technology Manager for the Northern Regional Center of the Clean Energy Smart Manufacturing Innovation Institute (CESMII) at Rensselaer Polytechnic Institute. His research efforts are focused on the modeling and control of biomedical and chemical process systems. Professor Bequette is the author of over 100 refereed journal publications and two textbooks published by Prentice Hall – (i) Process Control: Modeling, Design and Simulation (2003), and (ii) Process Dynamics: Modeling, Analysis and Simulation (1998).

He serves as Board Secretary for the American Automatic Control Council and is a Trustee of the Computer Aids for Chemical Engineering (CACHE) Corporation. Dr. Bequette is a founding member of the Editorial Board of the Journal of Diabetes Science and Technology, and serves on the Editorial Board of Industrial & Engineering Chemistry Research. He is a Fellow of IEEE, AIChE and the American Institute of Medical and Biological Engineers, and was inducted into the Arkansas Academy of Chemical Engineers. He is an avid bicyclist (commuting to campus in upstate NY throughout the entire year) and pole-vaulter (Master’s level competition refers more to age than skill level).


1980 B.S. Ch.E. University of Arkansas, Fayetteville 1985 M.S.E. University of Texas, Austin 1986 Ph.D. University of Texas, Austin

Research Focus
  • Deep learning and AI applications in healthcare
  • Deep learning and AI applications in smart manufacturing
  • Diabetes technology
  • Process systems automation and control
  • Human-in-the-Loop
  • Safety
Select Works
  • Diamond T, Cameron F, Bequette BW. A New Meal Model for Artificial Pancreas Systems. J. Diabetes. Sci. Technol. 2021. DOI: 10.1177/1932296821990111
  • Shu Y, Bequette BW. Optimization-based Control using Input Convex Neural Networks. Comp. Chem. Engng. 2021;144; 107143. https://doi.org/10.1016/j.compchemeng.2020.107143
  • Yang S, Rebmann A, Tang M, Moravec R, Behrmann D, Baird M, Bequette BW. Process Monitoring using Causal Graphical Models, with Application to Clogging Detection in Steel Continuous Casting. J. Process Control, 2021;105:259-266.
  • Shu Y, Navarathna P, Ghosh S, Bequette BW. Hybrid modeling in the era of smart manufacturing. Comp. Chem. Engng. 2020;140; 106784 https://doi.org/10.1016/j.compchemeng.2020.106874
  • Ghosh S, Yang S, Bequette BW. Inferential Modeling and Smart Sensors. Chapter 12 in Smart Manufacturing: Concepts and Methods (eds: M. Soroush, M. Baldea, T.F. Edgar). Elsevier. 2020. pp. 323-351.
  • Bequette BW. Process Control Education and Practice: Past, Present and Future. Comp. Chem. Engng. 2019;28:538-556. https://doi.org/10.1016/j.compchemeng.2019.06.011
  • Forlenza GP, Cameron FM, Ly TT, Lam D, Howsmon DP, Baysal N, Kulina G, Messer L, Clinton P, Levister C, Patek SD, Levy CJ, Wadwa RP, Maahs DM, Bequette BW, Buckingham BA. Fully Closed-loop Multiple Model Predictive Controller (MMPPC) Artificial Pancreas (AP) Performance in Adolescents and Adults in a Supervised Hotel Setting. Diabetes Technol. Ther. 2018;20(5):335-343.
  • DP Howsmon, N Baysal, BA Buckingham, GP Forlenza, TT Ly, DM Maahs, T Marcal, Lindsey Towers, Eric Mauritzen, Sunil Deshpande, Lauren M. Huyett, Jordan E. Pinsker, Ravi Gondhalekar, Francis J. Doyle III, Eyal Dassau, Juergen Hahn, B. Wayne Bequette. Real-time Detection of Infusion Site Failures in a Closed-Loop Artificial Pancreas. J. Diabetes Sci. Technol. 2018;12(3):599-607. https://doi.org/10.1177/19322968187551