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Joel Paulson

Joel Paulson

Gerald and Louise Battist Associate Professor

Dr. Joel Paulson is the Gerald and Louise Battist Associate Professor in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison. Prior to joining UW-Madison, he was a faculty member in the William G. Lowrie Department of Chemical and Biomolecular Engineering at The Ohio State University (OSU) from 2019 to 2025, where he held the H.C. Slip “Slider” Professorship. He holds a B.S. degree (with Highest Honors) from the University of Texas at Austin, and M.S.CEP. and Ph.D. degrees from the Massachusetts Institute of Technology (MIT), all in Chemical Engineering. After graduating from MIT, he completed a postdoctoral research appointment at the University of California, Berkeley, working in the area of systems and control theory. His current research interests are mainly in the areas of Bayesian optimization, scientific machine learning, sustainable process systems engineering, and model predictive control. He has received several awards, including the NSF CAREER Award, the AIChE 35 Under 35 Award, the Best Application Paper Prize from the 2020 IFAC World Congress, the Lumley Research Award, and the David C. McCarthy Engineering Teaching Award. Dr. Paulson is also an active member of the AIChE CAST Division and IEEE. He served as the 10d Program Coordinator for CAST and founded the “Process Control, Optimization, and Data Analytics Online Seminar Series” for the IEEE Technical Committee on Process Control.

Department

Chemical & Biological Engineering

Contact

Engineering Hall
1415 Engineering Dr
Madison, WI

Featured news

Focus on new faculty: Joel Paulson is using machine learning to make everything better

September 2, 2025

  • PhD 2016, Massachusetts Institute of Technology
  • MS CEP 2013, Massachusetts Institute of Technology
  • BS 2011, University of Texas, Austin

  • Bayesian optimization and active learning
  • Scientific machine learning and surrogate modeling
  • Uncertainty quantification
  • AI-driven molecular and materials discovery
  • Data-driven and model-based control
  • Decision-making under uncertainty
  • Sustainable systems engineering

  • 2025 Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Gerald and Louise Battist Associate Professorship
  • 2025 The Ohio State University (OSU), David C. McCarthy Engineering Teaching Award
  • 2023 The Ohio State Univeristy, H.C. “Slip” Slider Young Professorship
  • 2023 AIChE, 35 Under 35 Award
  • 2023 National Science Foundation, NSF CAREER Award
  • 2022 College of Engineering, The Ohio State University, Winner, College of Engineering Lumley Research Award
  • 2020 IFAC, Winner, Application Paper Prize at IFAC World Congress
  • 2017 IFAC, Finalist for Young Author Prize at IFAC World Congress (Nominated)
  • 2016 AIChE CAST division, Director’s Student Presentation Award Finalist
  • 2015 Massachusetts Institute of Technology, Goodwin Medal Nominee (Nominated)
  • 2015 Chemical Engineering, Massachusetts Institute of Technology, Outstanding Graduate Teaching Assistant Award
  • 2015 Massachusetts Institute of Technology, Robert T. Haslam Fellowship
  • 2015 School of Engineering, Massachusetts Institute of Technology, School of Engineering Graduate Student Award for Extraordinary Teaching and Mentoring
  • 2011 National Science Foundation, NSF Graduate Research Fellowship
  • 2008 National Merit Scholarship
  • 2007 Siemens, Semifinalist, Siemens Research Competition (Nominated)

  • Zhang, Q., & Paulson, J. (2025). Applied Artificial Intelligence, Big Data, and Data Analytics Methods for Next-Gen Manufacturing Efficiency. In 2025 AIChE Annual Meeting.
  • Jawdekar, T., Gun, S., Lu, C., Joshi, A., Kumar, S., Paulson, J., & Fan, L. (2025). Innovative Design, Performance Assessment, and Deployment Strategies of a Novel Modular Reactor for One-Step Liquid Fuel Production from Stranded Natural Gas. In 2025 AIChE Annual Meeting.
  • Aimiuwu, G., Khan, F., Mualen, D., Tang, W., Brunelli, N., Paulson, J., Winter, J., & Wyslouzil, B. E. (2025). Millifluidic Jet Mixing Reactor for High-Throughput Nanoparticle Manufacturing: A Combined Experimental and Computational Study. In 2025 AIChE Annual Meeting.
  • Kudva, A., Tang, W., & Paulson, J. (2025). Mobons: A Multi-Objective Bayesian Optimization Framework for Graph-Structured Networks of Black-Box Systems. In 2025 AIChE Annual Meeting.
  • Zhang, Q., Avraamidou, S., Paulson, J., Thakkar, V., Wang, Z., Chiang, L., Braun, B., Rathi, T., Chakrabarty, A., Sorouifar, F., & others, (2025). Navigating the Trade-offs and Synergies of Economic and Environmental Sustainability Using Process Systems Engineering. In 2025 American Control Conference (ACC) (p. 1725-1742). IEEE.
  • Muthyala, M., Sorourifar, F., Tan, T., Peng, Y., & Paulson, J. (2025). Semi-Supervised Chemical Language Models for Efficient and Accurate Multi-Objective Generative Design of Organic Battery Materials. In 2025 AIChE Annual Meeting.
  • Chakrabarty, A., Vanfretti, L., Wang, Y., Zhan, S., Mineyuki, T., Tang, W., Paulson, J., Deshpande, V., Bortoff, S. A., & Laughman, C. R. (2025). Time-series generative networks for synthesizing realistic scenarios in occupant-centric building simulation. In Building Simulation (p. 1-19).
  • Paulson, J., & Tsay, C. (2025). Bayesian optimization as a flexible and efficient design framework for sustainable process systems. Current Opinion in Green and Sustainable Chemistry, 51, 100983.
  • Lu, Y., Hu, W., Paulson, J., & Zhang, Q. (2025). BO4IO: A Bayesian optimization approach to inverse optimization with uncertainty quantification. Computers & Chemical Engineering, 192, 108859.
  • Aimiuwu, G., Khan, F., Mualen, D., Tang, W., Brunelli, N. A., Paulson, J., Winter, J. O., & Wyslouzil, B. (2025). Experimental and computational investigation of mixing dynamics in millifluidic jet mixing reactors. Chemical Engineering Journal, 164078.

  • CBE 890 - Pre-Dissertator's Research (Fall 2025)