Bart Selman is a Dutch-American professor of computer science at Cornell University. He helped start and is a main researcher at the Center for Human-Compatible Artificial Intelligence (CHAI) at the University of California, Berkeley. This center is led by Stuart J. Russell. Selman also helps lead the Computing Community Consortium's 20-year plan for AI research. From 2020 to 2022, he was the president of AAAI.
Education
Selman studied at the Technical University of Delft, where he earned a master's degree in physics and graduated in 1983. He later earned his master's degree and PhD in computer science from the University of Toronto in 1985 and 1991, respectively.
Career
Selman worked at AT&T Bell Laboratories before becoming a professor of computer science at Cornell University.
His research includes topics such as solving manageable problems, organizing information, using random search techniques, improving approximations, converting knowledge into usable forms, planning strategies, reasoning with default assumptions, and developing tools to solve complex equations, such as WalkSAT. He also studies how computer science connects to statistical physics, especially how systems change suddenly under certain conditions.
In 2016, Selman helped start an organization called the Center for Human-Compatible AI (CHAI). He led important projects there. His recent work and talks focus on making sure advanced artificial intelligence is safe and follows ethical rules.
Honors and awards
Selman has been awarded six Best Paper Awards for his work. He has also received the Cornell Stephen Miles Excellence in Teaching Award, the Cornell Outstanding Educator Award, a National Science Foundation Career Award, and an Alfred P. Sloan Research Fellowship. He is a Fellow of the AAAI, the AAAS, and the ACM.
Notable research papers
Selman is the author or co-author of more than 100 articles, including:
- Statistical regimes across constrainedness regions, by Carla P. Gomes, Cesar Fernandez, Bart Selman, and Christian Bessiere. Published in the Proceedings of the 10th International Conference on Principles and Practice of Constraint Programming (CP-04), Toronto, Ontario, 2005. Received the Distinguished Paper Award.
- Towards efficient sampling: Exploiting random walk strategies, by Wei Wei, Jordan Erenrich, and Bart Selman. Published in the Proceedings of AAAI-04, San Jose, California, 2004.
- Tracking evolving communities in large linked networks, by John Hopcroft, Brian Kulis, Omar Khan, and Bart Selman. Published in the Proceedings of the National Academy of Sciences (PNAS), February 2004.
- Natural communities in large linked networks, by John Hopcroft, Brian Kulis, Omar Khan, and Bart Selman. Published in the Proceedings of KDD, August 2003.
- Backdoors to typical case complexity, by Ryan Williams, Carla Gomes, and Bart Selman. Published in the Proceedings of IJCAI-03, Acapulco, Mexico, 2003.
- Dynamic restart policies, by Kautz, Henry, Horvitz, Eric, Ruan, Yongshao, Gomes, Carla, and Selman, Bart. Published in the Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-02), Edmonton, Alberta, Canada, 2002, pages 674–682.
- Generating hard satisfiability problems, by Bart Selman, David G Mitchell, and Hector J Levesque. Published in Artificial Intelligence, 1996.
- Noise strategies for improving local search, by Bart Selman, Henry A Kautz, and Bram Cohen. Published in AAAI, 1994.