Brown CS Professor Michael Littman Will Join NSF As Division Director For Information And Intelligent Systems
- Posted by Charlie Clynes
- on May 30, 2022
The National Science Foundation (NSF) announced recently that Professor Michael Littman of Brown CS will join as their division director for information and intelligent systems for the next two years. While retaining his role at Brown, Michael will oversee AI-related research funding and coordinate AI efforts between government agencies in his new role.
Research into artificial intelligence and machine learning has become especially relevant in recent years as technology has progressed to address a wide array of practical problems. Now, says Michael, developing technology in a socially responsible way is one of the key considerations for new research in the field.
“The fact that we’re actually getting these ideas out there into the world means that we have a responsibility to try to make sure that that’s not a negative influence,” he says. Michael pointed to Brown’s role in incorporating social responsibility into the technical education that students receive as one means of promoting this framework. “In the NSF, one of the ways that we can influence that process is by funding people who are researching those kinds of questions in productive ways,” says Michael, who noted that this could also mean changes to the grant proposal and award process.
Engaging with AI development at a national and international level excites Michael, who has already been connected to representatives from the UK and Taiwan. “I’m looking forward to meeting some new people, and I’m interested in getting to see the field from a broader perspective,” he says. “It really is an international endeavor.”
Michael received his doctorate from Brown CS in 1996 and has been a member of the faculty since 2012. Currently co-directing Brown's Humanity-Centered Robotics Initiative, he works mainly in reinforcement learning, but has done research in machine learning, game theory, computer networking, partially observable Markov decision process solving, computer solving of analogy problems, and other areas.
Michael has earned multiple awards for teaching and research and has served on the editorial boards for The Journal of Machine Learning Research and The Journal of Artificial Intelligence Research. He served as General Chair of the International Conference on Machine Learning and Program Chair of the Association for the Advancement of Artificial Intelligence (AAAI) Conference in 2013. He's also an AAAI Fellow and is general chair of the Reinforcement Learning and Decision Making Conference, held this year in Providence. He is an ACM Fellow and was an AAAS Leshner Fellow; recently, he received the AIJ Classic Paper Award at the International Joint Conference on Artificial Intelligence.
For more information, click the link that follows to contact Brown CS Communication and Outreach Specialist Jesse C. Polhemus.