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The Data Science for Social Good Workshop will focus on the application of data science techniques to problems of significant societal impact, such as healthcare, data privacy, renewable energy, and transportation. Bringing together disciplines in Computer Science, Industrial and Systems Engineering and Public Policy, it will include research domains such as algorithmic fairness, mechanism design, artificial intelligence, simulation, machine learning and optimization. The schedule is designed for attendees to form meaningful connections, including 2 minute lightning talks as an icebreaker, and breakout sessions separated by academic stage (for mentoring) and research area (for technical discussions).

Who Should Attend

Advanced undergraduates or recent graduates considering graduate school in data science and related fields, including (but not limited to) computer science, economics, operations research, statistics, math, psychology, and public policy.

Organizing Committee

Omar Isaac Asensio, Ph.D., School of Public Policy

Natashia Boland, Ph.D., H. Milton Stewart School of Industrial and Systems Engineering

Rachel Cummings, Ph.D., H. Milton Stewart School of Industrial and Systems Engineering

Jamie Morgenstern, Ph.D., School of Computer Science

Ira Wheaton Jr., Ph.D., H. Milton Stewart School of Industrial and Systems Engineering