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The Machine Learning Center at Georgia Tech (ML@GT) continues to diversify and expand its leadership team. Starting in January the leadership team will add Deven Desai, Polo Chau, Mark Davenport, Yao Xie, Mark Riedl, and George Lan as associate directors.

Desai, an associate professor in the Scheller College of Business, will be the center’s first associate director for Legal, Policy, Ethics, and Machine Learning. Not a technologist by training, Desai will draw from his experience working at Princeton's Center for Information Technology Policy and Google as Academic Research Counsel to help policy makers, legal scholars and technologists work better together. This includes helping each party understand how a given technology works and what issues it might raise.

“I am excited to be part of ML@GT because of the opportunity to be part of a world class group of thinkers and to connect our work to the world.  I believe there is a need to bridge the worlds of technology and law, policy, and ethics,” said Desai. “ML@GT is poised to increase not only machine learning insights and breakthroughs but also the way in which machine learning is built and used to serve society. I am honored and thrilled to be part of building that future.”

Xie, an associate professor in the H. Milton Stewart School of Industrial Systems Engineering (ISyE), is the first woman to join the leadership team. She will serve as the associate director for machine learning and data science where she will create better synergy between the ongoing research and education efforts between data science and machine learning as Georgia Tech builds a leading program in these areas.

“I am particularly excited to work with the broader community of students and faculty on campus who are interested or involved with machine learning and data science and foster their participation,” said Xie.

Lan, also an associate professor in ISyE has been appointed as the associate director for machine learning and statistics. In this role, Lan will promote research at the intersections between optimization, statistics, and machine learning and how they also apply in engineering. He will also help better facilitate communications for students coming from different home colleges or schools across campus.

“I am excited to be joining the team with active and dynamic academic leaders. I look forward to working with them to address a diverse set of challenges that ML@GT faces, e.g., being adaptive to the priorities and criterions for our affiliated faculty members and students across different academic units,” said Lan.

As the associate director for machine learning and artificial intelligence, Riedl, an associate professor in the School of Interactive Computing, will coordinate ML@GT’s strategy with respect to the broader field of artificial intelligence.

“Artificial intelligence and machine learning have the potential to radically change virtually every aspect of our lives. With thought and care, these technologies can be a force for good. Georgia Tech is well-positioned to be a major voice in how technology and policy shape the future,” said Riedl.

With more corporations integrating machine learning and artificial intelligence into their businesses, the center’s need for managing those relationships has increased significantly. Chau, an associate professor in the School of Computational Science and Engineering, will lead those relationships as the associate director for corporate relations for machine learning.

“I enjoy bringing people together, connecting industry with Georgia Tech researchers, bridging disciplines and innovating at their intersections. I’m excited to begin my new role as it will be a great way to help Georgia Tech further expand its national and global footprint,” said Chau.

As the associate director for community and students, Davenport is charged with creating a tight-knit community among faculty and students. Davenport, an associate professor in the School of Electrical and Computer Engineering, will work closely with the center staff to coordinate events and other opportunities to increase discussion and collaboration between research units.

The six new members will join existing leadership members Irfan Essa, Justin Romberg, Zsolt Kira, and Le Song.

About the Machine Learning Center at Georgia Tech

The Machine Learning Center at Georgia Tech is an interdisciplinary research center bringing together more than 190 faculty members and 60 machine learning Ph.D. students from across the institute for meaningful collaboration and innovation in machine learning and artificial intelligence. Students and faculty are experts in areas including, but not limited, to computer vision, natural language processing, robotics, deep learning, ethics and fairness, computational finance, information security, and logistics and manufacturing. For more information, visit www.ml.gatech.edu