FOPAM Conference Overview

FOPAM 2023, the CACHE conference on "Foundations of Process Analytics and Machine learning," will be held on July 30-August 3, 2023, at the University of California, Davis. Building on the successful FOPAM 2019, FOPAM aims to be the premier forum for researchers from industry and academia to discuss current status and future directions of data analytics and machine learning in the process industries.

Conference Format

The format of the conference is 3-1/2 days of presentations and discussions, preceded by an optional 1-1/2-day workshop. The conference begins on Monday evening, July 31, with an opening keynote by Cenk Ündey, Executive Director of Operations Advanced Analytics at Amgen. In the next three days, AM and PM sessions follow a format of two talks, then the speakers in a panel with an invited discussant for audience Q&A and serious technical discussions. Two of the afternoons are planned for poster sessions, open-mike discussions, small-group discussions, and other unstructured activities. On the last night, the conference banquet will conclude the conference with rapporteur analyses.

 

Schedule

Day Morning Afternoon Evening
Sun, Jul 30, 2023 Optional workshop by Leo Chiang (Dow), R. Bhushan Gopaluni (U British Columbia), and Joe Si Zhao Qin (City Univ of Hong Kong) Workshop (continued) Hospitality
Mon, Jul 31, 2023   Workshop (continued)

Welcoming Reception

Conference introduction/overview

Keynote: Cenk Ündey, Amgen

Tue, Aug 1, 2023

Emerging Machine-Learning Methods

Victor Zavala, University of Wisconsin Madison
Ioannis Kevrekidis, The Johns Hopkins University

Free time and Poster Session 1

Industrial Data-Science Applications I

Elif Ozkirimli, Roche (Zürich)
Detlef Hohl, Shell (Houston)

Wed, Aug 2, 2023

Machine Learning for Process and Product Chemistry

Zachary Ulissi, Carnegie Mellon
Kristen Severson, Microsoft

Free time and Poster Session 2

Industrial Data-Science Applications II

Salvador Garcia, Eli Lilly
Bea Braun, Dow Chemical

Thu, Aug 3, 2023

Data Science for Processes and Control

Rolf Findeisen, Technische Universität Darmstadt
Xiaonan Wang, Tsinghua University

Past and Future of Process/Product Analytics & Machine Learning, including Education and Workforce Development

Venkat Venkatsubramanian, Columbia University
John Hedengren, Brigham Young University

Conference Banquet with after-dinner rapporteurs

Continental breakfast and lunch will be provided Tue-Fri

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