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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).

Research Areas

Data privacy – As more and more of our everyday transactions and communication take place online, we produce an ever-growing amount of data  describing this behavior. Many online services which do not charge users money instead store this data, either to sell to other entities or to tailor their future services to individual’s preferences. In such an ecosystem, users should be concerned and protected against their sensitive information being leaked directly or indirectly.

Algorithmic fairness – When software decides everything from who sees particular advertisements to which social services an individual receives, a natural question of how these decisions are made, and how equitable these choices are for different individuals (perhaps belonging to different demographic groups). One approach is to explicitly consider the fairness of such choices at the time of designing an algorithm making such choices.

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