2024 AIChE Annual Meeting

Session: Data science and analytics for process applications

Papers are sought on the topic of analysis of large data sets and information management for improving process design or operations. Submissions from industry or collaborations between academia and industry are highly encouraged. Topics can cover both methods for data-analysis and information management, as well as applications.

Chair

Zheyu Jiang, Oklahoma State University

Co-Chairs

Ravendra Singh, Rutgers, The State University of New Jer
Jonggeol Na, Carnegie Mellon University
Yingjie Chen, Takeda

Presentations

08:00 AM

(632a) Crystalformer: Integrating Transformer-Based Language Models in a Hybrid Approach to Relate Molecular Structure with Crystal Size Distribution
Silabrata Pahari, Joseph Kwon

08:20 AM

(632b) Improved State-of-Health Estimation for Batteries with Domain-Adaptive Deep Learning
Gift Modekwe, Qiugang (Jay) Lu

08:40 AM

(632c) Determining Polymer Size from Raman Spectroscopy
Luise Kaven, Eleni Koronaki, Johannes M.M. Faust, Ioannis G. Kevrekidis, Alexander Mitsos

09:00 AM

(632d) Multivariable Run-to-Run Control for an Atomic Layer Etching Process Using a Transformer Model
Henrik Wang, Feiyang Ou, Julius Suherman, Gerassimos Orkoulas, Panagiotis Christofides

09:20 AM

(632e) Causal Discovery in Chemical Processes: Dealing with Cycles and Latent Confounders
Harman Dewantoro, Alexander Smith, Prodromos Daoutidis

09:40 AM

(632f) Automated Characterization and Monitoring of Material Shape Using Riemannian Geometry
Alexander Smith, Steven Schilling, Prodromos Daoutidis

10:00 AM

(632g) Multi-Source Transfer Learning for Accelerating Modeling of Chemical Processes
Ming Xiao, Keerthana Vellayappan, P S Pravin, Krishna Gudena, Zhe Wu