KDD 2019 Announces Duke University Computer Scientist and Microsoft Healthcare Executive as Keynote Speakers for 25th Annual Conference
Cynthia Rudin and Peter Lee to Address Key Industry Challenges Related to Data Science in Interpretable Machine Learning and Healthcare
NEW YORK, June 27, 2019 /PRNewswire/ -- KDD 2019, the premier interdisciplinary data science conference, today announced Cynthia Rudin, Ph.D., associate professor of computer science at Duke University, and Peter Lee, Ph.D., corporate vice president at Microsoft Healthcare, will be keynote speakers at the 25th annual conference. Taking place Aug. 4-8 in Anchorage, AL, KDD 2019 conference sessions will integrate advanced research with significant applications of data science, machine learning, big data and artificial intelligence.
"Keynote presentations at KDD shape the field for years to come; this year, we wanted to invite recognized experts in two very important areas that are at the cusp of innovation and debate within data science," said conference co-chairs Ankur Teredesai, CTO of KenSci and professor at the University of Washington, and Vipin Kumar, regents professor at the University of Minnesota. "Dr. Lee's work in artificial intelligence and cloud computing for healthcare is helping shape the next generation of software and tools at Microsoft. Similarly, Professor Rudin is working to make machine learning processes less complex, more human interpretable and trustworthy, with applications in healthcare AI and criminal justice. This is a fantastic lineup of leaders for participants to hear from, one with deep industry impact, and the other driving academic rigor, who together would normally not share a forum, except at KDD!"
Rudin will argue against the trend in machine learning towards more complex hypothesis spaces in her presentation, "Do Simpler Models Exist and How Can We Find Them?" She will instead make a case for solving the harder constrained optimization problem to find a simpler, but equally accurate, model, covering several new methods for interpretable learning including sparse optimal decision trees and sparse linear integer models.
Rudin focuses her research on machine learning tools that help humans make better, more informed decisions, also known as interpretable machine learning. She studies variable importance measures, causal inference methods, new forms of decision theory, uncertainty quantification, and methods that can incorporate domain-based constraints and other types of domain knowledge into machine learning. Rudin applies her findings to critical societal problems in criminology, healthcare and energy grid reliability.
During his keynote presentation, "The Unreasonable Effectiveness and Difficulty of Data in Healthcare," Lee will discuss the challenges and road blocks that are preventing data and data analysis from fulfilling the promise of better medical diagnostics, more effective therapeutics and improved productivity. With extensive experience in turning basic research into products of commercial impact, he is primed to discuss what is possible in healthcare technology.
Leading Microsoft's R&D project incubation initiatives for better, more efficient healthcare enabled by cloud and AI advances, Lee is widely recognized for his deep expertise. He has worked on innovative silicon and post-silicon computer architectures for Microsoft's cloud, simultaneous language translation for Skype, and deep neural networks for Microsoft's computer vision systems. He previously held roles at DARPA and Carnegie Mellon University, and is currently a member of the boards of directors of the Allen Institute for Artificial Intelligence and the Kaiser Permanente School of Medicine.
KDD 2019 brings together leading experts in the world of data science and artificial intelligence to share their latest research results and apply recent findings to the challenges facing an array of industries. The event is comprised of workshops, tutorials and designated special theme days, which highlight machine learning applications for environmental sustainability, healthcare and deep learning.
KDD 2019 will be held at the Dena'ina Convention Center and William Egan Convention Center in Anchorage, Alaska, Aug. 4-8, 2019. For more information and to register, visit: https://www.kdd.org/kdd2019/attending/registration.
About ACM SIGKDD:
ACM is the premier global professional organization for researchers and professionals dedicated to the advancement of the science and practice of knowledge discovery and data mining. SIGKDD is ACM's Special Interest Group on Knowledge Discovery and Data Mining. The annual KDD International Conference on Knowledge Discovery and Data Mining is the premier interdisciplinary conference for data mining, data science and analytics.
For more information on KDD, please visit: https://www.kdd.org/.
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