Prof. Edison Thomaz is an Assistant Professor and Fellow of the Jack Kilby/Texas Instruments Endowed Faculty Fellowship in Computer Engineering in the Chandra Family Department of Electrical and Computer Engineering at The University of Texas at Austin.
He holds a Ph.D. in Human-Centered Computing from the School of Interactive Computing of the Georgia Institute of Technology, and a S.M. in Media Arts and Sciences from the MIT Media Lab. Prior to his academic appointments, Dr. Thomaz held industry positions at leading technology companies such as Microsoft and France Telecom.
Dr. Thomaz's research focuses on the sensing, recognition and modeling of everyday human life activities in service of health and well-being applications. His work combines technical approaches from Ubicomp, HCI, Machine Learning, and Signal Processing. Over the last decade, Dr. Thomaz has developed new human-centered approaches for collecting, visualizing and analyzing activity-centered sensor data using commodity devices. His dissertation work centered on the automatic detection of eating activities in real-world settings. Dr. Thomaz's work has been published and received awards in leading academic conference such as Ubicomp, ICMI, IUI, and CHI. Dr. Thomaz is currently an active member of the NIH-funded Center of Excellence for Mobile Sensor Data-to-Knowledge (http://md2k.org(link is external)) and a leading researcher in the emerging field of personal health informatics. His work has been featured in numerous publications such as MIT Tech Review, The Houston Chronicle, and The Wall Street Journal.