Multimodal and Tensor Data Analytics for Industrial Systems Improvement

Chapter 1: Introduction to multimodal and tensor data analytics.- Chapter 2: Functional Methods for Multimodal Data Analysis.- Chapter 3: Advanced Data Analytical Techniques for Profile Monitoring.- Chapter 4: Statistical process monitoring methods based on functional data analysis.- Chapter 5: Tensor and multimodal data analysis.- Chapter 6: Tensor Data Analytics in Advanced Manufacturing Processes.- Chapter 7: Spatiotemporal Data Analysis - A Review of Techniques, Applications, and Emerging Challenges.- Chapter 8: Offshore Wind Energy Prediction Using Machine Learning with Multi-Resolution Inputs.- Chapter 9: Sparse Decomposition Methods for Spatio-temporal Anomaly Detection.- Chapter 10: Multimodal Deep Learning.- Chapter 11: Multimodal Deep Learning for Manufacturing Systems: Recent Progress and Future Trends.- Chapter 12: Synergy of Engineering and Statistics: Multimodal data Fusion for Quality Improvement.- Chapter 13: Manufacturing data fusion: a case study with steel rollingprocesses.- Chapter 14: AI-enhanced Fault Detection using Multi-structured Data in Semiconductor Manufacturing.- Chapter 15: A Survey of Advances in Multimodal Federated Learning with Applications.- Chapter 16: Bayesian Multimodal Data Analytics: An introduction.- Chapter 17: Bayesian approach to multimodal data in human factors engineering.- Chapter 18: Bayesian Multimodal Models for Risk Analyses of Low-Probability High-Consequence Events.

Nathan Gaw is an Assistant Professor of Data Science in the Department of Operational Sciences at Air Force Institute of Technology, Wright-Patterson AFB, Ohio, USA. His research develops new statistical machine learning algorithms to optimally fuse high-dimensional, multi-modal data sources to support decision making in military, healthcare and remote sensing. He received his B.S.E. and M.S. in biomedical engineering and a Ph.D. in industrial engineering from Arizona State University (ASU), Tempe, AZ, USA, in 2013, 2014, and 2019, respectively. Dr. Gaw was a Postdoctoral Research Fellow at the ASU-Mayo Clinic Center for Innovative Imaging (AMCII), Tempe, AZ, USA, from 2019-2020, and a Postdoctoral Research Fellow in the School of Industrial and Systems Engineering (ISyE) at Georgia Institute of Technology, Atlanta, GA, USA, from 2020-2021. He has also served as chair of the INFORMS Data Mining Society, and a member of IISE and IEEE.Panos M. Pardalos is Distinguished Professor Emeritus of Industrial and Systems Engineering at the University of Florida. Additionally, he is the Paul and Heidi Brown Preeminent Professor in Industrial & Systems Engineering. He is also an affiliated faculty member of the Computer and Information Science Department, the Hellenic Studies Center, and the Biomedical Engineering Program. He is also the Director of the Center for Applied Optimization. Dr. Pardalos is a world leading expert in global and combinatorial optimization. His recent research interests include network design problems, optimization in telecommunications, e-commerce, data mining, biomedical applications, and massive computing. He has co-authored and co-edited more than 30 books, as well as publishing more than 600 journal articles and conference proceedings. Prof. Pardalos is a Fellow of AAAS (American Association for the Advancement of Science), Fellow of American Institute for Medical and Biological Engineering (AIMBE), andEUROPT. He is a