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Burke, Robin D.

Professor

Positions

Research Areas research areas

Research

research overview

  • Professor Robin Burke conducts research in personalized recommender systems, a field he helped found and develop. His most recent projects explore fairness, accountability and transparency in recommendation through the integration of objectives from diverse stakeholders. Professor Burke is the author of more than 150 peer-reviewed articles in various areas of artificial intelligence including recommender systems, machine learning, and information retrieval. His work has received support from the National Science Foundation, the National Endowment for the Humanities, the Fulbright Commission, and the MacArthur Foundation, among others.

keywords

  • Recommender systems, Machine learning, Fairness and bias in recommender systems, Multistakeholder recommender systems, Digital humanities, Algorithmic governance

Publications

selected publications

Teaching

courses taught

  • CSCI 4830 - Special Topics in Computer Science
    Primary Instructor - Spring 2021
    Covers topics of interest in computer science at the senior undergraduate level. Content varies from semester to semester. Only 9 credit hours from CSCI 4830 and/or CSCI 4831 can count toward Computer Science BS or BA.
  • CSCI 4950 - Senior Thesis
    Primary Instructor - Fall 2021 / Spring 2022
    Provides an opportunity for senior computer science majors to conduct exploratory research in computer science as an option for the capstone requirement. Department enforced prerequisites: 35 hours of Computer Science coursework including Foundation courses, Upper-Division writing, CS GPA 3.0. Department consent required, contact academic advisor for details. May be repeated up to 8 total credit hours.
  • CSCI 6950 - Master's Thesis
    Primary Instructor - Fall 2022 / Spring 2023
  • INFO 3402 - Information Exposition
    Secondary Instructor - Spring 2019
    Teaches students to communicate information to a wider audience and construct stories with data across a variety of domains. Students will learn to use data for rhetorical purposes, applying visual, statistical and interpretative methods. Students will learn to think critically about ethical and social implications of using data in expository media, including identification of bias.
  • INFO 4608 - Community-Based Design
    Secondary Instructor - Spring 2019
    Surveys techniques in cooperative design with community members as collaborators rather than subjects. Students will explore approaches such as participatory design and co-design. Students will work in teams in partnership with community stakeholders to create tools, experiences, or systems that meet the needs of communities, contribute to social change, and/or lead to advancing academic knowledge. Same as INFO 5608.
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