AAAI Awards were presented in February at AAAI-24 in Vancouver, Canada. Each year, the Association for the Advancement of Artificial Intelligence recognizes its members, esteemed members of the AI community, and promising students, with the following awards and honors. AAAI Award winners J. Andrew (Drew) Bagnell, Anind K. Dey, Ashok K. Goel, Charles Lee Isbell Jr., Michael L. Littman, Andrew Maas, Milind Tambe, Raquel Urtasun, Brian Ziebart presented invited talks as part of AAAI-24’s program.
2024 AAAI Award for Artificial Intelligence for the Benefit of Humanity
The AAAI Award for Artificial Intelligence for the Benefit of Humanity recognizes the positive impacts of artificial intelligence to protect, enhance, and improve human life in meaningful ways with long-lived effects. The winner of this year’s award is Milind Tambe (Harvard University/Google Research). Milind has been recognized for “ground-breaking applications of novel AI techniques to public safety and security, conservation, and public health, benefiting humanity on an international scale.”
Milind Tambe is Gordon McKay Professor of Computer Science and Director of Center for Research in Computation and Society at Harvard University; concurrently, he is also Principal Scientist and Director for “AI for Social Good” at Google Research. He is recipient of the IJCAI John McCarthy Award, AAAI Feigenbaum Prize, AAAI Robert S. Engelmore Memorial Lecture Award, AAMAS ACM Autonomous Agents Research Award, INFORMS Wagner prize for excellence in Operations Research practice and MORS Rist Prize. He is a fellow of AAAI and ACM. For his work on AI and public safety, he has received Columbus Fellowship Foundation Homeland security award and commendations and certificates of appreciation from the US Coast Guard, the Federal Air Marshals Service and airport police at the city of Los Angeles.
2024 Robert S. Engelmore Memorial Award
The Robert S. Engelmore Memorial Award recognizes outstanding contributions to automated planning, machine learning, and robotics, their application to real-world problems, and extensive service to the AI community. This year’s award goes to Raquel Urtasun (University of Toronto) for her “outstanding contribution to machine learning, computer vision, and entrepreneurship in the field of autonomous driving”.
Raquel Urtasun is the Founder and CEO of Waabi, an AI company building the next generation of self-driving technology. Waabi is the culmination of Raquel’s 20-year career in AI and 10 years of experience building self-driving solutions. Raquel is also a Full Professor in the Department of Computer Science at the University of Toronto, a co-founder of the Vector Institute for AI, and the recipient of several high-profile awards including a Longuet-Higgins Prize, an Everingham Prize, an NSERC EWR Steacie Award, two NVIDIA Pioneers of AI Awards, three Google Faculty Research Awards, an Amazon Faculty Research Award, two Best Paper Runner up Prize awards at CVPR in 2013 and 2017 and more.
2024 AAAI/EAAI Patrick Henry Winston Outstanding Educator Award
The annual AAAI/EAAI Outstanding Educator award was created to honour a person (or group of people) who has made major contributions to AI education that provide long-lasting benefits to the AI community and society as a whole. The 2024 winners are Charles Isbell (University of Wisconsin-Madison) and Michael L. Littman (Brown University) for “innovative teaching of AI and machine learning through online courses reaching many thousands of students and through creative, entertaining outreach to the general public”.
Charles Lee Isbell Jr. is an American computationalist, researcher, and educator. He is Provost and Vice Chancellor for Academic Affairs at the University of Wisconsin–Madison. Before joining the faculty there, he was a professor at the Georgia Institute of Technology College of Computing starting in 2002, and served as John P. Imlay, Jr. Dean of the College from July 2019 to July 2023. His research interests focus on machine learning and artificial intelligence, particularly interactive and human-centered AI. In addition to his research work, Isbell has been an advocate for increasing access to and diversity in higher education.
Michael L. Littman is University Professor of Computer Science at Brown University, where he studies machine learning and decision-making under uncertainty. He has earned multiple university-level awards for teaching and his research has been recognized with three best-paper awards and three influential paper awards. Littman is a Fellow of the Association for the Advancement of Artificial Intelligence and the Association for Computing Machinery. He is currently serving as Division Director for Information and Intelligent Systems at the National Science Foundation. His book “Code to Joy: Why Everyone Should Learn a Little Programming” (MIT Press) was released Fall 2023.
2024 AAAI Distinguished Service Award
The AAAI Distinguished Service award recognizes one individual each year for extraordinary service to the AI community. The winner this year is Ashok Goel, for “outstanding service to the field of artificial intelligence through extensive leadership, especially as Editor-in-Chief of AI Magazine and Founding Editor of the Interactive AI Magazine, and for sustained interdisciplinary scholarship on education in AI and AI in education”.
Ashok K. Goel is a professor of computer science and human-centered computing in the School of Interactive Computing at Georgia Institute of Technology, and the chief scientist with Georgia Tech’s Center for 21st Century Universities. He conducts research into cognitive systems at the intersection of artificial intelligence and cognitive science with a focus on computational design and creativity. Goel is also the executive director of National Science Foundation’s AI Institute for Adult Learning and Online Education and an editor emeritus of AAAI’s AI Magazine.
2024 Classic Paper Award
The 2024 Classic Paper Award was given to the authors of the paper(s) deemed most influential from the Twenty-Third AAAI Conference on Artificial Intelligence, held in 2008 in Chicago, Illinois, USA. This year’s recipients are Brian Ziebart, Andrew Maas, J. Andrew Bagnell, and Anind Dey, who were honored for their paper, “Maximum Entropy Inverse Reinforcement Learning”, and its significant contributions to the development of a probabilistic approach, based on the principle of maximum entropy, to address inverse reinforcement and imitation learning problems.
Brian Ziebart is an Associate Professor in the Department of Computer Science at the University of Illinois Chicago. He earned his PhD in Machine Learning from Carnegie Mellon University where he was also a postdoctoral fellow. From 2020-2021, he was a Software Engineer working on autonomous driving at Aurora Innovation, Inc. His interests include imitation learning, distributionally robust optimization methods, and fair machine learning. He has published over 40 articles in leading machine learning, artificial intelligence, and robotics venues, including a Best Paper at the International Conference on Machine Learning.
Andrew Maas is the co-founder and CEO of Pointable, which builds retrieval systems for RAG-LLM workflows. He previously worked on data-centric deep learning approaches at Apple and was a Co-Founder of Roam Analytics (acquired by Parexel), a natural language extraction platform for healthcare. Andrew earned a PhD in computer science from Stanford University, advised by Andrew Ng and Dan Jurafsky, where his work focused on large-scale deep learning for spoken and written language tasks. Additionally, he teaches a graduate course on Spoken Language Processing at Stanford.
Andrew (Drew) Bagnell is Chief Scientist and co-founder of Aurora (aurora.tech) where he works to develop self-driving vehicles. He also serves as Consulting Professor at CMU’s Robotics Institute and Machine Learning Department. He has worked for two decades at the intersection of ML and robotics in industrial and academic roles. Bagnell’s group has received over a dozen research awards for publications in both robotics and ML communities including best paper awards at ICML, RSS, and ICRA. He received the 2016 Ryan Award, CMU’s award for Meritorious Teaching, and served as founding director of the RI Summer Scholars program.
Anind K. Dey is the Dean of the Information School at the University of Washington. For more than 20 years, he has led a research team focused at the intersection of human-computer interaction, machine learning and ubiquitous computing. His research team has received a number of awards, including best paper awards at CHI, Ubicomp, DIS, and test-of-time awards at Ubicomp and ISWC. He is an ACM Fellow and member of the ACM SIGCHI Academy.