2025 AIChE Annual Meeting

Session: Data-driven approaches, ML/AI and model uncertainty to better process understanding

Chair

Yuriy Abramov, Porton USA

Co-Chair

Presentations

03:30 PM

(42a) Fast-Tracking Process Optimization with Small Data and Machine Learning
Daniela Blanco, Ethan Tenison, Giselle Lu

03:55 PM

(42b) Reducing Model Size and Improving Model Identifiability Using Model Based Design of Experiments
Shivam Barodiya, Nikola Malinov, Marianthi Ierapetritou, Eleftherios Terry Papoutsakis

04:20 PM

(42c) Mechanistic Exploration and Kinetic Modeling through in-Silico Data Generation and Probabilistic Machine Learning Analysis
Xiao Li, Yasser Jangjou, Colton Davis, Sven Jager, Indu Muthancheri, Andreas R. Rötheli, Antoine de Gombert, Reza Amirmoshiri

04:45 PM

(42d) Exploring Synergies between SMEs and AI-Powered Tools in Reaction Optimization
Rudi Oliveira, Pedro Valente

05:10 PM

(42e) Data-Driven Design Space Identification in Data Limited Scenarios Using Transfer Learning
Andrea Galeazzi, Elizabeth Edwards, David Hilton, Maria Papathanasiou

05:35 PM

(42f) Model- and Data-Enabled Process Scale-up for High Shear Wet Granulation
Kanishka Ghosh, Faiz Khan, Hemlata Patil, Dale E. Greenwood, Maitraye Sen