Edison Thomaz

I am an Assistant Professor and Texas Instruments/Kilby Fellow in the Department of Electrical and Computer Engineering at The University of Texas at Austin, where I direct the Human Signals lab. My research focuses on human-centered machine perception using wearable and ubiquitous technologies. My students and I explore how to build computational systems that can make sense of people; systems that can recognize people's behaviors and activities, health condition, emotional state, surronding context, social interactions and more. I am a member of DICE, WNCG, and I am currently an Associate Editor of IMWUT. I also co-lead the Life Sensing Consortium.

Contact Info

ethomaz at utexas dot edu
Twitter: @ethomaz

EER 7.818
2501 Speedway
Austin, TX 78712

Office Hours

Fridays: 1pm-2pm
Meeting at EER Café Patio


Fall 2021
EE382V Human Signals

Spring 2022
EE422C Software Design II

Ph.D. Students

Rebecca Adaimi
Dawei Liang
Priyanka Khante
Xuewen Yao

Ph.D. Alumni

Keum San Chun
Samsung Research America


Recent News

  Fall 2022 Ph.D. Opportunities
I am actively looking for multiple PhD students to join our group in 2022. If you are interested in wearable + mobile computing, hci, ubicomp, and activity recognition, please reach out.
Oct 2021

  Jack Kilby/Texas Instruments Fellowship
I have been appointed as 2021-2022 Fellow of the Jack Kilby/Texas Instruments Endowed Faculty Fellowship in Computer Engineering. Very excited and grateful, thank you for your support UT ECE.
Sept 2021

  Keum San Graduates
Keum San successfully defended his PhD thesis titled "Small-Scale Wireless Sensors for Automated Dietary Monitoring" and becomes the first graduate of the Human Signals Lab. Major milestone.
May 2021

  Ok, Google, What Am I Doing?
Rebecca's paper on acoustic activity recognition with conversational assistants was accepted to IMWUT and presented at Ubicomp 2021. This work shows that it is possible to leverage gaps in voice interactions to learn about a person's context and activities.
Mar 2021

  IFML Grant
The new UT Austin-based Institute for Foundations of Machine Learning (IFML) has awarded us a grant to work on adaptive and continual learning for activity recognition applications. We are excited to extend our research work in this direction.
Feb 2021

  NIH Grant on Kidney Stone Prevention
In collaboration with colleagues at Penn State and Stanford, we are kicking off a 5-year project to explore the use of wearables to prevent kidney stones. Thanks to the National Institute of Diabetes and Digestive and Kidney Diseases for supporting this effort.
Jan 2021

  ECE Seminar: Prof. Cecilia Mascolo
We had the pleasure of hosting Professor Cecilia Mascolo from the University of Cambridge at the ECE Colloquia Seminar. Prof. Mascolo went over her recent work on the use of mobile audio data for health diagnostics.
Dec 2020

Edison Thomaz © 2021