Edison Thomaz

Publications   Teaching   Vita   Prospective Students

Research Assistant Professor
Electrical and Computer Engineering
School of Information
The University of Texas at Austin

I am a member of DICE and WNCG at ECE and the Intelligent Systems Group at the iSchool.

ethomaz at utexas dot edu
Twitter: @ethomaz

Office: EER 7.818
2501 Speedway
Austin, TX 78712

Office Hours: Mondays at 1PM

EE422C - Software Design and Implementation II (Fall 2017)

Methods for engineering software with a focus on abstraction; specification, design, implementation, and testing of object-oriented code using a modern development tool-set for complex systems:

  • Design and implementation of object-oriented programs in Java
  • Abstract data types
  • Inheritance
  • Polymorphism
  • Parameterized types and generic programming
  • Applications of data structures
The course also covers the application of commonly used data types, exception handling and fault tolerance. and teamwork models.

INF385T - Personal Informatics (Spring 2016, Spring 2017, Spring 2018)

Personal Informatics is a new, exciting area of study that focuses on streams of data that emerge from the individual. It provides the foundation for self-experimentation, self-awareness, and behavior change. This class covers many personal informatics topics, including:

  • Sources of personal informatics data
  • Active and passive methods for data collection
  • Concepts, models, and theories around personal data and personal informatics
  • Prototyping and evaluation of apps, user interfaces and visualizations around personal data
  • Sharing and privacy issues for personal data
  • Self-experimentation and self-reflection
  • Behavior change with personal data
  • Practical challenges of personal informatics
The course draws upon theories, methods and techniques from HCI, Ubicomp, and Infovis. Ultimately, the goal is to empower students to explore their own data, and build new applications, models, visualizations and interfaces around personal informatics.

EE382V - Activity Sensing and Recognition (Fall 2016)

This hands-on course focuses on teaching concepts and practical skills for building systems that can sense and infer human activities, context and health measures while leveraging mobile, ubiquitous and wearable computing technologies. Topics covered include:

  • Intro to mobile and ubiquitous computing
  • Machine learning concepts
  • Data collection in the lab and in the field
  • Environmental sensing
  • Wearable sensors and sensing modalities
  • Activity recognition pipelines
  • Privacy and ethical considerations
  • Applications in HCI and health
Classes will be a mix of lectures, discussions around fundamental, advanced and emerging topics in the field, and in-class (lab-like) activities. Additionally, students will be expected to work on a semester-long project.

Edison Thomaz © 2018