Overview:
Join us for our upcoming webinar exploring emerging opportunities for statisticians in AI education! Hear perspectives from statisticians who are actively involved in AI education initiatives, highlighting concrete examples, challenges, and best practices.
Speakers
Tian Zheng, Professor of Statistics at Columbia University
Nick Horton, Beitzel Professor of Technology and Society (Statistics and Data Science) at Amherst College
Moderator
Linglong Kong, University of Alberta
Co-Organizers
Bei Jiang, University of Alberta and Hongtu Zhu, UNC at Chapel Hill
Abstract
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Curriculum Evolution: Rethinking how we teach statistics to both majors and non-statisticians to meet the demands of an AI-driven world.
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Interdisciplinary Research: Moving beyond theoretical silos to solve complex, real-world problems.
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Faculty Development: Preparing the next generation of researchers to lead in a landscape where the lines between data science, AI, and statistics are increasingly blurred.
Statisticians bring unique value to the AI table, from uncertainty quantification to causal inference. This session will identify current bottlenecks and offer a roadmap for statisticians to effectively contribute to and lead the AI educational revolution.
About the Speakers
Dr. Tian Zheng is Professor of Statistics at Columbia University. In her research, she develops novel methods for exploring and understanding patterns in complex data from different application domains such as biology, psychology, climate modeling, etc. Her research has been recognized by the 2008 Outstanding Statistical Application Award from the American Statistical Association (ASA), the Mitchell Prize from ISBA, and a Google research award. She became a Fellow of the American Statistical Association in 2014, a Fellow of the Institute of Mathematical Statistics in 2022, and a Fellow of the American Association for the Advancement of Science in 2024. From 2017 to 2020, she served as Associate Director for Education at the Columbia Data Science Institute. From 2019 to 2025, she was chair of the Department of Statistics at Columbia. Professor Zheng is the recipient of the 2017 Columbia Presidential Award for Outstanding Teaching. In 2021, she was recognized with a Lenfest Distinguished Columbia Faculty Award, which honors the excellence of faculty as teachers and mentors of both undergraduate and graduate students.
Dr. Nick Horton is Beitzel Professor of Technology and Society (Statistics and Data Science) at Amherst College. He served as the editor of the Journal of Statistics and Data Science Education, was co-PI of the NSF-funded Data Science Corps Wrangle/Analyze/Visualize project, chaired the Committee of Presidents of Statistical Societies, co-chaired of the National Academies Committee on Applied and Theoretical Statistics, and chaired the National Academies Consensus Study on Data and Computing Competencies for K-12. Nick has published more than 200 papers and books and is a Fellow of the American Statistical Association, the Institute for Mathematical Statistics, and the American Association for the Advancement of Science.
About the Moderator
Linglong Kong, University of Alberta
About the NISS-CANSSI
Collaborative Data Science Web Series:
The NISS-CANSSI Collaborative Data Science initiative that the National Institute of Statistical Sciences (NISS) in collaboration with the Canadian Statistical Sciences Institute (CANSSI) brings together experts from various fields to tackle complex data challenges through interdisciplinary teamwork and innovative methodologies.
Goals of the Initiative
The goal is to foster progress in:
- Developing new ideas for experimental and observational data-driven learning and discovery that address key questions at the cutting edge of science and scientific deduction;
- Quantifying and summarizing uncertainty in data-driven theories, as well as complex Data Science models, algorithms, and workflows; and
- Establishing new practices for scientific reproducibility and replicability through Data Science.
Featured Webinars
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Date: Thursday, June 12, 2025 at 1-2pm ET
Speakers: Lauren Wengerd, Ohio State University, Depart of Rehabilitation Science and Dave Friedenberg, Battelle; Moderator: Nancy McMillan, Battelle
From MPEG-4 to Deep Learning: Transforming Audio-Visual Analytics for Healthcare and Beyond
Date: Thursday, May 8, 2025 at 1-2pm ET
Speakers: An-Chao Tsai, Department of Computer Science and Artificial Intelligence, National Pingtung University and Anand Paul, LSU Health-New Orleans; Moderator: Qingzhao Yu, Associate Dean for Research at the School of Public Health, Louisiana State University Health, New Orleans
Astronomy & Cosmic Emulation
Changing Climate, Changing Data: A journey of statisticians and climate scientists
Date: Thursday, March 20, 2025 at 1-2pm ET
Speakers: Claudie Beaulieu, Assistant Professor of Ocean Sciences, University of California, Santa Cruz and Rebecca Killick, Professor of Statistics, School of Mathematical Sciences, Lancaster University; Moderator: Emily Casleton, Statistical Sciences Group, Los Alamos National Laboratory (LANL)
Event Type
- NISS Hosted