Faculty.Scholar.Visiting

This is a TEFR for Fulbright Scholar Dr. P. Tsai, who will work with Dr. Jingtong Hu in the ECE Department.

Please do not post this position in the Talent Center.

Deep learning models have been deployed in an increasing number of edge and mobile devices to provide healthcare in our lives, from mobile dermatology assistants, mobile eye cancer (leukoria) detection, and emotion detection to comprehensive vital signs monitoring. All these techniques rely on visual assistance of the cameras that come with mobile devices and inevitably lead to different levels of fairness concerns due to the inherent gender, race, and/or socioeconomic bias in existing AI models. Compounding contributing factors include a lack of medical professionals from marginalized communities, inadequate information about those communities, and socioeconomic barriers to participating in data collection and research. In the absence of a diverse population that reflects the U.S. population, potential safety or efficacy considerations could be missed. What is worse, with inadequate data, AI algorithms could misdiagnose underrepresented people, leading to increasing healthcare disparities. Therefore, there is a critical need to address racial, skin color, and socioeconomic inequities in AI-assisted mobile diagnosis.

This project will address the fairness issue in mobile AI assistants, using dermatology diagnosis and skin color inequity as the study case. Instead of collecting equitable demographic datasets in a centralized way, it will develop a federated on-device learning framework for participation inclusion, selective data contribution, and continuous personalization. The framework can continuously learn from new users’ data as they use the mobile apps with little human supervision.

Dr. P. Tsai will mainly help with fairness-aware AI model development.

Successful candidates will have a Bachelor's, Master's, or PhD in electrical engineering or a related area, qualifications commensurate with a Fulbright Scholar, and synergy with strengths in our Swanson School of Engineering (SSOE, http://www.engineering.pitt.edu/) and across campus.

Electrical and Computer Engineering

Assignment Category

Full-time regular

Bargaining Unit Eligibility

This position may be bargaining unit eligible

Campus

Pittsburgh

Required Attachments

Curriculum Vitae