AI for Social Good: Learning and Planning in the End-to-End, Data-to-Deployment Pipeline (Distinguished Lecture)
Prof. Milind Tambe,
University of Southern California –
With the maturing of AI and multiagent systems research, we have a tremendous opportunity to direct these advances towards addressing complex societal problems. I will focus on the problems of public safety and security, wildlife conservation and public health in low-resource communities, and present research advances in multiagent systems to address one key cross-cutting challenge: how to strategically deploy our limited intervention resources in these problem domains. I will discuss the importance of conducting this research via building the full data to field deployment end-to-end pipeline rather than just building machine learning or planning components in isolation. Results from our deployments from around the world show concrete improvements over the state of the art. In pushing this research agenda, we believe AI can indeed play an important role in fighting social injustice and improving society.
Milind Tambe is Helen N. and Emmett H. Jones Professor in Engineering at the University of Southern California(USC) and the Founding Co-Director of CAIS, the USC Center for Artificial Intelligence in Society, where his research focuses on advancing AI and multiagent systems research for Social Good. He is recipient of the IJCAI (International Joint Conference on AI) John McCarthy Award, ACM/SIGAI Autonomous Agents Research Award from AAMAS (Autonomous Agents and Multiagent Systems Conference), AAAI (Association for Advancement of Artificial Intelligence) Robert S Engelmore Memorial Lecture award, INFORMS Wagner prize, the Rist Prize of the Military Operations Research Society, the Christopher Columbus Fellowship Foundation Homeland security award, International Foundation for Agents and Multiagent Systems influential paper award; he is a fellow of AAAI and ACM. He has also received meritorious Commendation from the US Coast Guard and LA Airport Police, and Certificate of Appreciation from US Federal Air Marshals Service for pioneering real-world deployments of security games. Prof. Tambe has also co-founded a company based on his research, Avata Intelligence , where he serves as the director of research. Prof. Tambe received his Ph.D. from the School of Computer Science at Carnegie Mellon University.
Sandra Maria Lopes de Sá
Room 0.19/0.20, IST – Pavilhão de Informática II, Alameda
Mathematics, Physics & Machine Learning Seminar Series (Online)
The Mathematics, Physics & Machine Learning seminar series has started on October 2020 and runs until March 2021.
The seminars aim to bring together mathematicians and physicists interested in machine learning (ML) with ML and AI experts interested in mathematics and physics, with the goal of introducing innovative Mathematics and Physics-inspired techniques in Machine Learning and, reciprocally, applying Machine Learning to problems in Mathematics and Physics.
Attendance is free but registration is required.
More information is available here.
International European Conference on Parallel and Distributed Computing
The 27th International European Conference on Parallel and Distributed Computing (Euro-Par 2021) will take from August 30 to September 3 2021 in Lisbon.
Euro-Par is the prime European conference covering all aspects of parallel and distributed processing, ranging from theory to practice, from small to the largest parallel and distributed systems and infrastructures, from fundamental computational problems to full-fledged applications, from architecture, compiler, language and interface design and implementation, to tools, support infrastructures, and application performance aspects.
The 2021 edition of Euro-Par will be organized as a collaboration between INESC-ID and Instituto Superior Técnico (IST).
– Abstract Submission: February 5, 2021
– Paper Submission Deadline: February 12, 2021
– Author Notification: April 30, 2021
– Camera-Ready Papers: June 6, 2021
More information is available here.