Five graduate students from our lab shared their research at the Foundations of Process/Product Analytics and Machine Learning (FOPAM) 2023 Conference held at UC Davis from July 30th to August 3rd, including:
Hailey Lynch: Model-Based Design of Experiments and Pyomo.DoE
Ke Wang: Optimization Of Modern Manufacturing for Thermoelectric Material Using Machine Learning And Data Science
Kyla Jones: On the Identifiability of Hybrid Models
Montana Carlozo: Bayesian Optimization for Nonlinear Model Calibration
Xinhe Chen: Multiperiod Optimization of Integrated Energy Systems with Machine-Learning Surrogates to Predict Market Impacts.
For detailed abstracts of these presentations, please visit https://fopam.cache.org/poster-sessions. You can find other recent presentations and publications from our group at Dowlinglab.com/publications.