Art Graesser is a professor in the Department of Psychology and the Institute of Intelligent Systems at the University of Memphis, as well as Honorary Research Fellow at University of Oxford. He received his Ph.D. in psychology from the University of California at San Diego. His research interests question asking and answering, tutoring, text comprehension, inference generation, conversation, reading, problem solving, memory, emotions, artificial intelligence, computational linguistics, and human-computer interaction. He served as editor of the journal Discourse Processes (1996–2005) and Journal of Educational Psychology (2009-2014), as well as presidents of 4 societies, including Society for Text and Discourse (2007-2010), the International Society for Artificial Intelligence in Education (2007-2009), and the Federation of Associations in the Behavioral and Brain Sciences (2012-13). He and his colleagues have developed and tested software in learning, language, and discourse technologies, including those that hold a conversation in natural language and interact with multimedia (such as AutoTutor) and those that analyze text on multiple levels of language and discourse (Coh-Metrix and Question Understanding Aid -- QUAID). He has served on five panels with the National Academy of Sciences and four OECD expert panels on problem solving, namely PIAAC 2011 Problem Solving in Technology Rich Environments, PISA 2012 Complex Problem Solving, PISA 2015 Collaborative Problem Solving (chair), and PIAAC Adaptive Problem Solving 2021. He has received lifetime achievement awards from three societies (Artificial Intelligence in Education, American Psychological Association, and Society for Text and Discourse) and a McGraw Prize in Education in the area of learning sciences.

Kevin Bowyer is the Schubmehl-Prein Family Professor of Computer Science and Engineering at the University of Notre Dame. Professor Bowyer was elected as a Fellow of the American Academy for the Advancement of Science “for distinguished contributions to the field of computer vision and pattern recognition, biometrics, object recognition and data science”, a Fellow of the IEEE “for contributions to algorithms for recognizing objects in images”, and a Fellow of the IAPR “for contributions to computer vision, pattern recognition and biometrics”. He has received a Technical Achievement Award from the IEEE Computer Society “for pioneering contributions to the science and engineering of biometrics”, and IEEE Biometrics Council’s Meritorious Service Award and Leadership Award. Professor Bowyer has served as Editor-In-Chief of both the IEEE Transactions on Biometrics, Behavior, and Identity Science and the IEEE Transactions on Pattern Analysis and Machine Intelligence. Professor Bowyer has served as General Chair or Program Chair of conferences such as Computer Vision and Pattern Recognition, Winter Conference on Applications of Computer Vision, and Face and Gesture Recognition, and is one of the founding General Chairs of the International Joint Conference on Biometrics conference series.

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Haiying Shen is an Associate Professor in the Department of Computer Science at the University of Virginia. During her 2024 sabbatical, she served as a Consulting Researcher at Microsoft in Redmond, WA, where she focused on LLM systems. Her research area is distributed systems, with a focus on ML/LLM systems, cloud computing, edge computing, and cyber-physical systems (CPS). Dr. Shen has made significant contributions to her field, with an H-index of 52 and over 380 publications in top conferences and journals such as SIGCOMM, OSDI, EuroSys, SoCC, ASPLOS, CoNext, Infocom, IEEE/ACM Transactions on Networking (TON), IEEE Transactions on Parallel and Distributed Systems (TPDS), and IEEE Transactions on Mobile Computing (TMC). Her work has received the George N. Saridis Best Transactions Paper Award (2021), best paper awards at CloudCom (2016) and NAS (2018), a best paper runner-up award at ICCCN (2015), best paper award nominations at ICPP (2021), MASS (2011), and CCGrid (2009), and a best-in- session presentation award at INFOCOM (2017). She has also received several prestigious awards, including the Microsoft Faculty Fellowship Award (2010), IEEE TCSC Mid-Career Award (2015), IBM Faculty Award (2015), NSF CAREER Award (2013), and Sigma Xi Clemson Chapter Young Investigator Award (2013). Dr. Shen serves as an Associate Editor for TON, TMC, and IEEE Networking Letters (NL). She also has served as program co-chair and general co-chair for several international conferences and has participated in the program committees of numerous leading conferences.

Tomoki Toda is a Professor at the Global Research Institute for Mobility in Society, Institutes of Innovation for Future Society, Nagoya University. He received his Ph.D. degree from the Graduate School of Information Science at Nara Institute of Science and Technology in 2003. His research interests include sound media information processing, encompassing speech processing (e.g., speech generation, speech analysis, speech recognition, speech assessment, speech translation, and spoken language processing), music processing (e.g., music analysis, music source separation, music generation, singing voice analysis, and singing voice synthesis), and acoustic environment processing (e.g., sound event recognition, anomalous sound detection, audio captioning, and multichannel audio signal processing). He has published more than 550 peer-reviewed journal and conference papers. He has received more than 20 paper and achievement awards, including the 2009 Young Author Best Paper Award from the IEEE Signal Processing Society, the 2013 Best Paper Award from Speech Communication (EURASIP-ISCA), and the 2015 Young Scientists’ Prize in the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology of Japan. He has organized several international challenges on speech generation technologies, including the Voice Conversion Challenge and the VoiceMOS Challenge series. He served as a member of the Speech and Language Technical Committee of the IEEE Signal Processing Society from 2007 to 2009 and again from 2014 to 2016. He has also served as a Senior Area Editor of IEEE Signal Processing Letters, a Senior Editor of APSIPA Transactions on Signal and Information Processing, and an Associate Editor for several journals and transactions. In addition, he served as Chair of the APSIPA Speech and Language Processing Technical Committee.

Dr. Biocca is Director of the M.I.N.D. Labs, New York and member of the Nvidia Deep Learning Center- Centre for Computation and Culture, and Beijing Normal-Hong Kong Baptist University. The M.I.N.D. Lab is an international, multi-university human-computer interaction lab. Dr. Biocca’s research explores human-computer interaction in natural, immersive interfaces and how these interfaces can support user cognition and augment human performance. Dr. Biocca is listed as one of the top 1% scientist as measured by impact and citations (Stanford-Elsevier). Among his more than 250 publications are ten books, including award-winning books on virtual environments and patents in the areas of human-computer interaction and information technology. His work has been cited in more than 36,000 scientific papers. Awarded three chaired professorships including the Newhouse Chair, AT&T Chair, and World Class University Professor Chair. Dr. Biocca has been a professor, researcher, or lecturer for ten US, Europe, and Asia universities, including the University of California-Berkeley, Stanford, University of North Carolina, Sungkyunkwan University, Helsinki School of Economics among others. Prior to obtaining his Ph.D., Dr. Biocca was a Silicon Valley executive who participated in the introduction of mobile computing including the first portable computer. Dr. Biocca was promoted to full professor only seven years after receiving his Ph.D. Dr. Biocca’s research and commentary on media, cognition, and communication have been featured in over 60 news and media organizations spanning more than 15 countries, including CNN, New York Times, Washington Post, BBC Worldwide, among others.

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