FOPAM 2019
Foundations Of Process Analytics and Machine learning is the new triennial series of CACHE-sponsored conferences; it aims to be the premier forum for researchers from industry and academia to discuss the current status and future directions of data analytics and machine learning in the process industries.
Topics include:
- Data analytics and high-throughput data processing for process health monitoring, estimation, and diagnosis
- Machine learning for process and control design
- Computational chemistry/materials analytics (including machine learning for molecular design)
- Reinforcement learning and deep reinforcement learning for process operations and control
- Synergies between process, materials, business, and supply chain data analytics
- Data analytics education for chemical engineers
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- Conference Organization
- Meeting Chairs
- Richard D. Braatz
- MIT
- Thomas A. Badgwell
- ExxonMobil
- Phillip Westmoreland
- North Carolina State University
- Advisory Committee
- Michael Baldea
- University of Texas at Austin
- Leo H. Chiang
- The Dow Chemical Company
- Selen Cremaschi
- Auburn University
- R. Bhushan Gopaluni
- University of British Columbia
- Martha A. Grover
- Georgia Institute of Technology
- Johannes Hachmann
- University at Buffalo
- Heather J. Kulik
- MIT
- Jay H. Lee
- KAIST
- Jonathan Moore
- The Dow Chemical Company
- S. Joe Qin
- University of Southern California
- Nikolaos V. Sahinidis
- Carnegie Mellon University
- Fengqi You
- Cornell University
- Victor Zavala
- University of Wisconsin-Madison
- Conference Information
- Robin Craven
- Conference Manager
- email: