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).
This workshop is organized by ML@GT faculty including Omar Isaac Asensio, Rachel Cummings, and Jamie Morgenstern.
Please note that workshop attendance is by application only. Applications are now closed.
For more information, please visit the workshop's website.