معرفی
Edison Thomaz is an Associate Professor in the Electrical and Computer Engineering department at The University of Texas at Austin, with an appointment in the School of Information. He directs the Human Signals Lab and holds affiliations with DICE, bioECE, SES, WNCG, iMAGiNE, and CAPS. He also serves as Editor of IMWUT and Steering Committee Chair for UbiComp.
Education:
- Ph.D. in Human-Centered Computing from the School of Interactive Computing of the Georgia Institute of Technology
- S.M. in Media Arts and Sciences from the MIT Media Lab
Dr. Thomaz's research focuses on Activiomics - a discipline applying computational methods to sense, recognize and model people's everyday life activities and context. His work combines environmental and wearable sensors with computational approaches to measure human behaviors at a detailed level, pairing them with bio-physiological signals. His research spans human-centered sensing, machine perception, and computational systems that recognize and model people's behaviors, health conditions, emotional states, contexts, and social interactions.
His recent publications demonstrate a strong focus on wearable sensing technologies, particularly smartwatches, for activity recognition, dietary monitoring, and health applications. Key trends include the use of acoustic sensing for activity recognition, LLM applications for data annotation, and the development of techniques for continuous health monitoring. His work bridges computer science, healthcare, and behavioral science to create practical applications for personal health informatics.
Scientific Awards:
- NSF CAREER award (2023)
- Jack Kilby/Texas Instruments Fellowship (2021-2022)
- Best Paper Award Runner-up at ISWC 2022
- Best Paper Award at ICASSP 2023 Ambient AI Workshop
- William H. Hartwig Fellow
Dr. Thomaz has successfully mentored numerous PhD students who have gone on to positions at Samsung Research America, Oura, and academic postdocs. He has secured significant grant funding including an NIH R01 award for dietary monitoring research, an NIH R01 grant to study digital biomarkers for cognitive impairment, and an NSF CAREER award. His research is supported by collaborations with institutions including the University of Rhode Island, Penn State, and Stanford.
He directs the Human Signals Lab at UT Austin, which focuses on human-centered sensing and machine perception using wearable and ubiquitous technologies. The lab brings together students and researchers working on activity recognition, dietary monitoring, acoustic sensing, and health applications of wearable devices.
