Sciences: Machine Learning, Artificial Inteligence, and Ubiquitous Computing

Department: Systems and Information Engineering

Supervising Faculty Member: Matthew Gerber

Specialization: Machine Learning, Artificial Intelligence, and Ubiquitous Computing

Research Focus: My students and I conduct research in Cyber-Human Systems (CHSs), which couple humans and computing to advance human capabilities and wellbeing. We are interested in how humans perceive safety and risk, how these perceptions influence behavior, and how we might embed humans within CHSs to measure and modify these processes and outcomes. We build mobile technology that uses smartphones and wearable devices to sense human behavior, and we employ methods from machine learning and artificial intelligence to understand these behaviors and assist humans in achieving their objectives.

Position Description: Accepted USOAR students will be integrated into our research lab and will work alongside current graduate students on existing research projects. Activities and responsibilities may include any of the following:  collecting and reading research papers, identifying research questions for investigation, designing and deploying experiments, analyzing experimental data, and writing research papers for publication. These activities will be conducted under the guidance of graduate students and a faculty advisor.

Required skills: Required classes include mathematics at the level of calculus. Preferred (though not required) classes include statistics, probability, and computer programming. More importantly, the student must have a strong work ethic, genuine interest in our particular research projects, an ability to work independently after initial guidance, and very strong time management skills.

What you will learn: 1) Understand the objectives of a graduate research lab and how it functions to achieve these objectives.
2) Understand basic issues in cyber-human systems.
3) Understand some of the technology involved in studying and building cyber-human systems.

Web site link to research: http://ptl.sys.virginia.edu/ptl/members/matthew-gerber