2025 AIChE Annual Meeting

Session: 10E Interactive Session: Data and Information Systems

This session solicits posters in the broad area of Data and Information Management in the chemical engineering domain. Abstracts describing methods, applications, challenges, and tools are all welcome.

Chair

Victor M. Zavala, University of Wisconsin-Madison

Co-Chairs

Maria Papathanasiou, Imperial College London
Miguel A. Zamarripa, National Energy Technology Laboratory

Presentations

(394a) Equivalent-Circuit Thermal Aging Model for Lithium-Ion Battery Temperature Prediction with Parameter Identification
Myisha Ahmed Chowdhury, Qiugang (Jay) Lu
(394i) Optimal Selection of Nonlinear Dynamic Sparse Surrogate Models with Exact Satisfaction of Mass, Energy and Thermodynamics Constraints
Samuel Adeyemo, Benjamin Ilesanmi, Debangsu Bhattacharyya
(394ap) Cybersecurity in the Manufacturing Industry: Challenges, Strategies, and Future Directions
Seerat Bilal, Saqib Naeem
(394af) LLM-Powered Knowledge Graph Framework - the Analysis of Biochemical Networks
Nikos Trokanas, Stefanos Xenios, Konstantinos Mexis, Franjo Cecelja, Antonios Kokosis
(394g) Domain-Compliant AI Adoption Enhances the Operation Excellence of Power Systems
Waqar Ashraf, Ramit Debnath, Vivek Dua
(394h) The Composer: Lessons Learned on Developing a Data-Driven Assistant for Bioreactor Design and Optimization
Héctor Maldonado De Leon, Víctor Puig I Laborda, Johan Le Nepvou De Carfort, Jorge Carrasco, Adrie J. J. Straathof, Cornelis Haringa
(394ah) A Human-Centric Explanation of Reinforcement Learning Agents Using Large Language Models
Haechang Kim, Hao Chen, Can Li, Jong Min Lee
(394k) Bridging Computer Vision and Chemical Experimentation for Automated Observation
Rama El-khawaldeh, Jason Hein
(394am) Hard Vs Soft-Constrained Physics-Informed Neural Networks for Process Optimization: A Systematic Comparison
Tanuj Karia, Giacomo Lastrucci, Abhinav Verma, Ankit Tyagi, Stanislav Jaso, Artur M. Schweidtmann
(394b) Denoising Dynamic Composition Data from a Multi-Sample Instrument in a Pilot Unit
Apurva Raje, Robert DeJaco, Ryan Evans, Brandon Burghardt, Anthony J. Kearsley
(394ag) A Novel Bayesian Approach for Data-Driven Hierarchical Sparse Modeling of Time-Delayed Process Systems
Samuel Adeyemo, Debangsu Bhattacharyya
(394aj) Manifold Learning for Mechanism Discovery in Automated Protein Folding
Collin Szczepanski, Begum Cicekdag, Sachin Kadyan, Gonzalo Gutierrez, Venkat Venkatasubramanian
(394aa) Exploring Kolmogorov–Arnold Networks for Data-Efficient Fault Detection in Industrial Processes
Enrique Luna, Vladimir Mahalec
(394u) Improving Dynamical System Model Quality Using Symbolic Regression
Benjamin Cohen, Burcu Beykal, George M. Bollas
(394v) Toward Developing an Agent Based Digital Twin for Air Quality Management
Sathish Swaminathan, Pranav Agrawal, V. Faye McNeill, Raghunathan Rengaswamy
(394m) Nonlinear Structure-Property Space Identification with Distance-Based Uncertainty Quantification for Molecular Property Predictions
Jae Young Kim, Dionisios Vlachos
(394ak) Accelerated Reaction Discovery Via High-Throughput Reaction Pooling and Progressive Fidelity Analytics
Babak Mahjour, Runzhong Wang, Connor Coley
(394l) Enhancing Performance and Explainability of Bayesian Variational Autoencoder for Solving Partial Differential Equations Via Adaptive Fourier Decomposition
Zeyuan Song, Zheyu Jiang
(394ar) Towards Sustainable Water Management: Leveraging Machine Learning for Optimizing Energy Consumption and Reducing Emissions in GOSP Facilities
Muhammad Abbas, Omar Naeem
(394f) A Benchmark Simulation Model of Green Ammonia Production for the Development of Process Safety and Monitoring Approaches
Niklas Groll, Jakob Kjøbsted Huusom, Gurkan Sin
(394ao) Modeling Nonlinear Chemical Process Networks with Spatial-Temporal Data Using a Graph Convolutional Lstm Approach
Wanlu Wu, Guoquan Wu, Zhe Wu
(394s) Domain Aware Modeling of Multi-Mode Operation of RO Water Treatment and Desalination Systems Via Graph Attention Networks
Michael Clement, Bilal Khan, Yang Zhou, Nora Marki, Yoram Cohen
(394j) Fault Detection for an Industrial Etching Process Using Transfer Learning and Data Aggregation
Feiyang Ou, Julius Suherman, Henrik Wang, Panagiotis Christofides
(394t) Generative Machine Learning Modeling with Data Aggregation Techniques in Anindustrial Manufacturing Setting
Feiyang Ou, Julius Suherman, Henrik Wang, Panagiotis Christofides
(394r) Machine Learning-Based System for Real-Time Quantification of Heavy Metals across Diverse Solution Matrices Using Spectroscopy of Plasmas in Liquids
Liang-Yu Chen
(394x) Smart Farming in Space and Extreme Environments: Applications of Machine Learning and Digital Twin Technologies
Van Duc Long Nguyen, Shu Liang, Marc Escriba-Gelonch, Volker Hessel
(394an) From Data to Differential Equations: Interpretable Modeling with Genetic Algorithm–Based Machine Learning and Embedded Domain Knowledge
Kyung Il Kim, Hannah Qi, Arijit Chakraborty, Venkat Venkatasubramanian
(394c) Multi-Dataset Feature Selection Enhances Lithium-Ion Battery End-of-Life Prediction
Yooil Son, Seongmin Heo
(394q) Machine Learning Empowered Autonomous Laboratory for Emulsifiable Concentrates Design
Yipei Zhao, Tong Liu, Robin Wesley, Joan Cordiner
(394y) A Novel Method for Improving the Robustness of Data-Driven Process Models
Hsiao-Te Liu, Jeffrey Ward, Ming-Chun Fang, Hao-Yeh Lee, Cheng-Ting Hsieh, Tzu-Chieh Hua, Shih-Chieh Lin, Chih-Lung Lee, Tzu-Hsien Huang, Wei-Ti Chou
(394ac) Gaussian Process Q-Learning for Finite-Horizon Markov Decision Processes
Maximilian Bloor, Tom Savage, Calvin Tsay, Antonio del Rio Chanona, Max Mowbray
(394p) Multi-Agent Llms for Sustainable Operational Decision Making
Emma Pajak, Abdullah Bahamdan, Klaus Hellgardt, Antonio del Rio Chanona
(394aq) Artificial Intelligence in the Petrochemical Industry: Yesterday, Today, and Tomorrow
Minghua Ye
(394ad) Learning Feasible Bioprocess Kinetics with Semi-Supervised VAEs for LCA
Stefanos Xenios, Nikos Trokanas, Antonis Kokossis, Konstantinos Mexis
(394ae) Data-Driven Discovery of Reaction Rates from Batch Time Series Data Via Kolmogorov-Arnold Networks
Aswin Chandrasekar, Prashant Mhaskar
(394d) Integrating Process Knowledge with Data-Driven Approaches for Industrial Soft Sensor Development
Fangyuan Ma, Jingde Wang, Chengyu Han, Zheyu Jiang, Wei Sun
(394e) Nonlinear Cointegration-Based Complex Feature Extraction and Monitoring for Non-Stationary Process
Jingzhi Rao, Cheng Ji, Jingde Wang, Wei Sun
(394ab) A Hybrid Framework for Early Flooding Detection in Distillation Columns: Integrating Hydraulic Modeling and Data-Driven Techniques
Amir Hossein Hamedi, Vladimir Mahalec, Prashant Mhaskar