Professor Booth is an assistant professor working with the Department of Computer Science at the University of Memphis. His research interests span topics in machine learning, signal processing, algorithmic bias/fairness, and data collection and annotation methods, especially as they pertain to human behavior and experience modeling. He has a diverse background in industry working as a video game and serious game developer and as a R&D engineer on various problems in robotics, computer vision, human-computer interaction systems, and geospatial visualization. Prior to joining, he completed his PhD in Computer Science at the University of Southern California and worked as a postdoctoral scholar in the areas of human-centered and ethical computing at the University of Colorado Boulder. Dr. Booth's research focuses on understanding the complex dynamics of human behaviors, interactions, thinking, and emotions in different contexts. His interdisciplinary work combines theories and knowledge from machine learning, psychology, signal processing, game design, and ethics and aims to advance social good through human-centered computing.
Akane Sano is an Associate Professor at Rice University, Department of Electrical Computer Engineering, Computer Science, and Bioengineering. She directs the Computational Wellbeing Group. Her research focuses on human sensing, data analysis and modeling, and intelligent system development for health, wellbeing, and performance. She is a also member of Rice Digital Health Initiative. Her research projects include NIH funded multimodal machine learning for characterizing and measuring affect and craving profiles for patients with substance use disorders, NSF future of work project: embodied cognitive assistant for shift workers, NIH funded SNAPSHOT study project, Eureka project (symptom prediction and digital phenotyping in schizophrenia using phone data) and IARPA mPerf project (Using mobile sensors to support productivity and employee well-being). She received her PhD at MIT Media Lab, and her MEng and BEng at Keio University, Japan. Before she joined Rice University, she was a Research Scientist in Affective Computing Group at MIT Media Lab, and a visiting scientist/lecturer at People-Aware Computing Lab, Cornell University.
Prof. Etemad is an Associate Professor at the Department of Electrical and Computer Engineering, Queen's University. He holds an endowed professorship of Mitchell Professor in AI for Human Sensing & Understanding. His main area of research is human-centered machine learning and deep learning. Dr. Etemad received his M.A.Sc. and Ph.D. degrees in Electrical and Computer Engineering from Carleton University, Ottawa, Canada, in 2009 and 2014, respectively. Prior to joining Queen’s, he held several industry positions as lead scientist. He has published over 170 papers in top venues in the area (e.g., NeurIPS, ICLR, AAAI, CVPR, T-PAMI, ECCV, ICCV, etc.), is a co-inventor of 10 patents, and has given over 30 invited talks. Dr. Etemad is an Associate Editor for IEEE Transactions on Affective Computing and IEEE Transactions on Artificial Intelligence. He has served as a PC member/reviewer, and has held organizing roles at various venues. He has received a number of awards including Prize for Excellence in Research, Supervisor of the Year Award, Instructor of the Year Award, and several Best Paper Awards (e.g., at ACM ICMI'23). Dr. Etemad’s lab and research program have been funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada, Ontario Centers of Excellence (OCE), Canadian Foundation for Innovation (CFI), Mitacs, and other organizations, as well as the private sector. He has held visiting faculty positions at the University of Cambridge and Google Research.