Please note, this event is now CANCELED, sorry for any inconvenience. Please refer to the following schedule on the series page here: https://www.niss.org/CoLab/collaborative-data-science
Overview:
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Meet the members of the organizing committee and learn about their backgrounds and expertise
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Understand the vision and goals of the NISS-CANSSI web series on Collaborative Data Science
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Provide input and suggestions on the types of collaborations, scientific domains, and emerging topics they would like to see highlighted
Moderator
Committee Members
Qingzhao Yu, Association Dean for Research at the School of Public Health, Louisiana State University Health, 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, Ph.D., Director, Data Science Nexus and Professor & Head of Department of Statistics at University of Manitoba
Sahar Zangeneh, Cascade Insights LLC
Elizabeth Eisenhauer, Senior Statistical Associate, Westat
Jiguo Cao, PhD, 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 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
Advancing Neonatal and Perinatal Research Through Collaborative Biostatistical Innovation
Date: Thursday, January 15, 2026 - 12:00pm to 1:00pm ET
Speakers: Dr. Anup Katheria, Associate Professor of Pediatrics at Drexel University College of Medicine, and Director of the Neonatal Research institute at Sharp Mary Birch Hospital for Women & Newborns and Dr. Abhik Das, Distinguished Fellow, Biostatistics at RTI International; Moderator: Sahar Zangeneh, Cascade Insights LLP
Deep learning with ECG data in the ICU: From modelling to actionable AI
Date: Thursday, November 20, 2025 - 1:00pm to 2:00pm ET
Speakers: Parvin Mousavi, Director, School of Computing at Queen’s University & David Maslove, Associate Professor & Clinician Scientist, Departments of Medicine and Critical Care Medicine, Queen’s University; & Internist and Intensivist, Kingston Health Sciences Centre; Moderator: Joel Dubin, Statistics & Actuarial Sciences Health Data Science Lab (HDSL) Lead, University of Waterloo
Working with Physicists on Quantum ML
Date: Thursday, October 9, 2025 - 1:00pm to 2:00pm ET
Speakers: Dr. Martin T. Wells, Charles A. Alexander Professor of Statistical Sciences, Statistics and Data Science at Cornell University & Dr. Luca Candelori, Mathematician and currently Director of Research at Qognitive, Inc.; Moderator: Dr. Emily Casleton, Statistician, Statistical Sciences Group, Los Alamos National Laboratory (LANL)
Statistical Ecology
Date: Thursday, September 18, 2025 at 1-2pm ET
Speakers: Dr. Laura Cowen (University of Victoria) and Dr. Patrick D. O’Hara (ECCC-CWS, Institute of Ocean Sciences); Moderated by Dr. Saman Muthukumarana (University of Manitoba).
Data Science Techniques for Control of Assistive Devices After Neurological Injury
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