ACM SIGMETRICS / IFIP PERFORMANCE 2022
June 6-10, 2022
(7:00 pm - 8:00 pm IST / 9:30 am - 10:30 am EDT)
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 domains of public health and conservation, and address one key cross-cutting challenge: how to effectively deploy our limited intervention resources in these problem domains. I will present results from work around the globe in using AI for challenges in public health such as Maternal and Child care interventions, HIV prevention, and in conservation such as endangered wildlife protection. Achieving social impact in these domains often requires methodological advances. To that end, I will highlight key research advances in multiagent reasoning and learning, in particular in, restless multiarmed bandits, influence maximization in social networks, computational game theory and decision-focused learning. In pushing this research agenda, our ultimate goal is to facilitate local communities and non-profits to directly benefit from advances in AI tools and techniques.
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 of "AI for Social Good" at Google Research. He is recipient of the IJCAI John McCarthy Award, AAMAS ACM Autonomous Agents Research Award, AAAI Robert S. Engelmore Memorial Lecture Award, and he is a fellow of AAAI and ACM. He is also a recipient of the INFORMS Wagner prize for excellence in Operations Research practice and Rist Prize from MORS (Military Operations Research Society). 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.
Texas A&M University
(6:30 pm - 7:30 pm IST / 9:00 am - 10:00 am EDT)
Universities are large and complex organizations. Many functions of universities (including research and education administration) and their infrastructure (including transportation, facilities, utilities) depend on data supplied by participants or collected through instrumentation during their operation. The resulting data are used to manage these functions across a range of timescales, ranging from planning, through daily operations, to troubleshooting and event response. Due to the constraints and demands of daily operations management, the potential for such data to improve operations has often not been fully realized. This provides an opportunity for university researchers to develop partnerships with operational organizations that capitalize on their institutional data investments to improve campus operations. This talk describes data-driven operational collaborations in the Texas A&M Operational Data Science Lab that support several of the areas listed above. We argue that faculty and students engaged in these activities benefit from exposure to real-world problems, not only through the broader impact that results, but in informing future use-inspired research in these and cognate areas. This can improve positioning for emerging funding opportunities that not only use to Data Science to combine across disciplines, but also integrate vertically from theory, through systems, to practice. Achieving these goals has the potential to transform universities into living laboratories for Data Science, accelerating the pace and effectiveness of research, teaching, and outreach.
Nick Duffield is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, holder of the Royce E. Wisenbaker Professorship I, and Director of the Texas A&M Institute of Data Science (TAMIDS). His research combines foundations and applications of Data Science and computer networking, currently graph sampling and learning, network measurement and resilience, and applications of Data Science to transportation, agriculture, infrastructure, and operations. In his TAMIDS role, he has led the development of new education programs, courses, and training in Data Science, and created the Thematic Labs program that supports development of ecosystems in emerging areas in Data Science and AI, encompassing research, education, and community building. He is an ACM Fellow, IEEE Fellow, and IET Fellow, and was a co-recipient of the ACM Sigmetrics Test of Time Award in both 2012 and 2013 for work in Network Tomography. From 1995 to 2013 Duffield worked at AT&T Labs, Florham Park, NJ, where he was a Distinguished Member of Technical Staff and an AT&T Fellow, and prior to that held faculty and postdoctoral positions in Germany and Ireland. He received his PhD in Physics from the University of London, UK in 1987 and the MMath and BA in Natural Sciences from the University of Cambridge, UK, in 1983 and 1982 respectively.