NISS-CANSSI Collaborative Data Science: Exploring Future Directions for the NISS-CANSSI Collaborative Data Science Series
Date: Thursday, February 12, 2026
Time: 13:00–14:00 Eastern time
Location: On Zoom
Join Us
Join us for this special community roundtable on “Exploring Future Directions for the NISS/CANSSI Collaborative Data Science Series.” We would love to have your input.
Presentation Abstract
The NISS-CANSSI Collaborative Data Science webinar series is dedicated to showcasing the power of interdisciplinary collaboration between data scientists and domain experts. This initiative celebrates how the fusion of data science with diverse scientific fields can drive innovation, solve complex problems, and push the boundaries of knowledge. In this webinar, the members of the organizing committee will introduce themselves and provide an overview of the web series. The goal is to engage the community and gather feedback on the types of collaborations and topics community members would like to see featured in future sessions.
Attendees will have the opportunity to:
- Meet the members of the organizing committee and learn about their backgrounds and expertise
- Understand the vision and goals of the NISS-CANSSI Collaborative Data Science webinar series
- Provide input and suggestions on the types of collaborations, scientific domains, and emerging topics they would like to see highlighted
This interactive session will help shape the direction of the webinar series, ensuring that it continues to be a valuable resource for showcasing the transformative impact of collaborative data science. Join us to be a part of this exciting initiative and help shape the future of cross-disciplinary research and discovery.
Planning Committee Members
Qingzhao Yu, Associate Dean for Research at the School of Public Health, Louisiana State University Health Sciences Center, New Orleans
Don Estep, Director, Canadian Statistical Sciences Institute (CANSSI), Canada Research Chair (Tier 1), Department of Statistics and Actuarial Science, Simon Fraser University
Xiao-Li Meng, Whipple V.N. Jones Professor of Statistics, Harvard University
Saman Muthukumarana, Director, Data Science Nexus and Professor and Head, Department of Statistics, University of Manitoba
Sahar Zengeneh, Cascade Insights LLC
Elizabeth Eisenhauer, Senior Statistical Associate, Westat
Jiguo Cao, Canada Research Chair in Data Science, Professor, Department of Statistics and Actuarial Science, Simon Fraser University
Joel Dubin, Professor, Statistics and Actuarial Science, Health Data Science Lab (HDSL) Lead, University of Waterloo
David S. Matteson, Director, NISS, and Professor, Department of Statistics, Cornell University
About the Moderator
Emily Casleton is Chair of the NISS-CANSSI Collaborative Data Science Webinar Planning Committee. She is a statistician in the statistical sciences group at Los Alamos National Laboratory (LANL), and was recruited to LANL as a summer student at the 2012 Conference on Data Analysis (CoDA). She joined the Lab as a postdoc in 2014 after earning her PhD in Statistics from Iowa State University. Since converting to staff in 2015, Emily has routinely collaborated with seismologists, nuclear engineers, physicists, geologists, chemists, and computer scientists on a wide variety of cool data-driven projects. Most recently, her research focus has been on testing and evaluating large AI models. She holds a BS in Mathematics, Political Science from Washington & Jefferson College, 2003; an MS in Statistics from West Virginia University, 2006; and a PhD in Statistics from Iowa State University.
About the NISS-CANSSI Collaborative Data Science Webinar Series
In an era where data transcends traditional boundaries, fostering interdisciplinary collaboration has never been more crucial. Together with the National Institute of Statistical Sciences (NISS), we are proud to present the NISS-CANSSI Collaborative Data Science webinar series dedicated to showcasing data scientists and domain scientists from diverse scientific fields who collaborate to advance science. This initiative celebrates the power of collaboration, demonstrating how the fusion of data science with various disciplines can drive innovation, solve complex problems, and push the frontiers of knowledge beyond the realm of statistics.
Each session features two speakers: a data scientist and a subject matter expert from another domain who have successfully partnered to achieve impactful results. Through their shared experiences and insights, attendees gain a deeper understanding of the collaborative processes that bridge gaps between different scientific landscapes. These seminars not only highlight successful partnerships but also provide a platform for exchanging ideas, methodologies, and best practices that inspire new collaborations.