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Margarita Kapustina Awarded the 2025–2026 Department of Statistics Award in Data Science

Margarita Kapustina

The Department of Statistics at UBC is pleased to announce that Margarita Kapustina has been selected as the recipient of the 2025–2026 Department of Statistics Award in Data Science.

Kapustina is a PhD candidate in Neuroscience in the Cembrowski Lab at UBC, where her work sits at the intersection of neuroscience and data science. Her research focuses on developing open‑source analytical tools that enable scientists to extract meaningful insights from large‑scale biological datasets.

“This award highlights how developing open‑source analytical tools can transform large-scale biological datasets into meaningful discoveries about the brain's cellular organization and function,” Kapustina said. “These discoveries provide the framework to advance our understanding of neurological diseases and identify novel therapeutic targets.”

Her supervisor, Dr. Mark Cembrowski, praised her contributions and impact: “Margo is a rising star in both data science and computational neuroscience. In just a few years as a graduate student, she has developed a variety of open-source tools enabling analysis of complex transcriptional datasets, which have had broad uptake in the scientific community. She has also applied these tools in a variety of settings to reveal new—and previously unforeseen—rules of how the brain is organized into cell types.”

The Department of Statistics Award in Data Science recognizes students who demonstrate initiative, creativity, and excellence in applying data-driven methods to meaningful questions. The annual $1,000 award is open to undergraduate and graduate students from any program at UBC Vancouver who have made outstanding contributions to the field of data science.

The Department extends its warmest congratulations to Margarita Kapustina on this well‑deserved achievement.

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Dr. Marie Auger Méthé awarded UBC Killam Accelerator Research Fellowship

Dr. Marie Auger-Méthé

Dr. Marie Auger-Méthé is the recipient of one of six UBC Killam Accelerator Research Fellowships which are provided annually from the Killam endowment established through a bequest from the late Dorothy J. Killam. The Killam Accelerator Research Fellowships (KARF) are designed to empower early‑career scholars who have already demonstrated notable impact in their fields and are poised to advance to the next stage of their research careers, providing research funding and valuable time to devote to their work.

Dr. Auger-Méthé is an Associate Professor in the Department of Statistics at the University of British Columbia, jointly appointed with the Institute for the Oceans and Fisheries (IOF). She also holds a Tier II Canada Research Chair in Statistical Ecology and is a leading figure in the investigation of animal movement. Dr. Auger-Méthé is internationally known for developing data analysis tools used by research ecologists to better understand animal behaviour and by government agencies to guide concrete management decisions, and she has collaborated with Indigenous hunters to meaningfully integrate Indigenous knowledge into statistical analysis. Her research output includes papers in ecological and statistics journals, and accompanying R packages.  Her publication record—over 60 peer-reviewed papers as an associate professor—is exceptional and more typical of a full professor in the discipline.

Dr. Auger-Méthé has developed state space and hierarchical models to better capture the complexity of animal movement, yet still maintain interpretability. Her highly cited first-authored 2021 Ecological Monographs paper showcases her expertise in applications of state-space modelling to ecological time series and her ability to communicate complex technical information to ecologists. Her contributions to Hidden Markov Models include accounting for the fine-scale dependence and multiscale structure associated with high-frequency data, providing accurate classification with sparse labels, speeding up fitting algorithms, and automatically selecting the number of hidden states. In a series of papers, she has incorporated Indigenous knowledge into statistical analyses to understand seal behaviour and habitat use.  She has also used citizen science from whale-watching, accounting for the spatially-biased search effort present in such opportunistic datasets.

This fellowship will allow Dr. Auger- Méthé to develop data-based methods and resources to guide decisions to identify critical habitat. The work will build on her research in hierarchical models and in combining different forms of data, including citizen science data and Indigenous Knowledge. Through this work, she will create easy-to-use tools that identify Critical Habitats quickly and accurately and which will facilitate the protection of such habitats via governmental policies (e.g., recovery strategies and marine protected areas). She will also create an open-access repository of Critical Habitat information that can be used by NGOs, First Nations, and other groups when advocating for the protection of imperilled species. Such work is urgently needed to address biodiversity loss and generate systematic ways of meeting Canada’s conservation goals. To demonstrate the usefulness of these tools, she will apply them to marine mammals and seabirds data in areas with increasing shipping and energy developments.

Congratulations, Dr. Auger-Méthé!

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UBC Statistics Director of Finance, HR, and Operations, Kevin Lin, awarded a 2025 Faculty of Science Excellence in Service Award

Kevin Lin

The UBC Department of Statistics congratulates Kevin Lin, Director of Finance, HR, and Operations, on being awarded a 2025 Faculty of Science Excellence in Service Award. 

This award recognizes staff and faculty who have made exceptional contributions beyond their regular responsibilities, advancing the mission and strategic goals of UBC Science through their dedication, service, and impact. 

Kevin has been recognized for his "service and leadership infused with creativity, diligence, empathy, humility, integrity, and intelligence".

Congratulations, Kevin!

Read more about the UBC Faculty of Science Excellence in Service Award.

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Call for nominations for the Department of Statistics Award in Data Science for Academic Year 2025-26

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The Department of Statistics is soliciting nominations for the Department of Statistics Award in Data Science, an award to recognize the importance of developing and applying tools to answer important questions through the analysis of data.

This $1,000 award is offered to an undergraduate or graduate student who has demonstrated initiative and creativity in making outstanding contributions in the field of Data Science. The award is made on the recommendation of the Department of Statistics Awards Committee and, in the case of a graduate student, in consultation with the Faculty of Graduate and Postdoctoral Studies.

The nominee must be an undergraduate or graduate student enrolled at UBC Vancouver during the 2025-26 Winter session or must have graduated in November 2025. The nominator must be a faculty member or someone in a suitable supervisory position, such as a co-op supervisor or research supervisor. Student self-nominations will not be accepted.

The nominator is to submit the following material as a PDF to ea@stat.ubc.ca, with subject line Data Science Award Nomination by Tuesday, February 17, 2026:

  • A description written by the student of their achievements related to Data Science (not to exceed 1 page, minimum 12 point font);
  • A student resume/curriculum vitae; and
  • A supporting letter from the nominator (not to exceed 1 page, minimum 12 point font).

While the Committee will consider high grades in relevant courses, the Committee will look beyond grades to more substantial achievements related to Data Science. Some examples of achievements are:

  • Creative and impactful data analysis via visualization techniques;
  • Development of software to implement an innovative statistical approach; and
  • Improvement of the computational aspects of a data analysis approach.

Such activities might have been as a course project or thesis, an end-product of a relevant co-op experience, or participation in an online Data Science competition, such as Kaggle.

For a list of previous winners, please see our Data Science Award page

If you would like to support this award, please see the UBC Development & Alumni Engagement donation page.

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Xiaoting Li Awarded the Lorraine Schwartz Prize for the 2024/2025 Academic Year

Xiaoting Li

Congratulations to Xiaoting Li, who has been awarded the Lorraine Schwartz Prize for the 2024-25 academic year. The award is given annually by the Department of Mathematics and the Department of Statistics for distinctions in the fields of statistics and probability. 

Xiaoting recently defended her Ph.D. thesis in Statistics, supervised by Professor Harry Joe. Her thesis work on multivariate tail inference and extremes, plus other research during her Master's at McGill led to publications in the journals Entropy, Journal of Multivariate Analysis, Computational Statistics and Data Analysis, Environmetrics, and Journal of the American Statistical Association.  Her important applications of statistics and probability have included systemic risk for financial institutions, extreme flood insurance losses, and other areas. Xiaoting also had valuable roles at UBC as instructor of a course and in service roles.  She is now an Assistant Professor in the Department of Statistics, University of Manitoba.

The prize was established in 1966 in memory of Dr. Lorraine Schwartz, Assistant Professor in the Department of Mathematics from 1960-1965, by her friends and colleagues.  Dr. Schwartz received her PhD from the University of California, Berkeley, in 1960, working with Professor Lucien Le Cam, with a thesis entitled "Consistency of Bayes' Procedures".   She then took a position at UBC where she remained until her untimely death.  However even in her brief career, she made seminal contributions to her field in published research papers that are still cited today.

For more details about the Lorraine Schwartz Prize, please see https://www.stat.ubc.ca/lorraine-schwartz-prize.

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Keegan Korthauer Awarded a 2025 Michael Smith Health Research BC Scholar Award

Keegan Korthauer

The UBC Statistics Department proudly announces that Assistant Professor Keegan Korthauer has been named a recipient of a 2025 Michael Smith Health Research BC Scholar Award.

The Michael Smith Health Research BC Scholar Program is designed to support early-career researchers in establishing their independent careers, building research teams, and developing innovative programs that drive cutting-edge health solutions.

Dr. Korthauer's research group is tackling the complex challenge of extracting meaningful biological insights from massive-scale genomic experiments. Her team develops rigorous statistical frameworks and computational tools to leverage the vast scope and scale of high-throughput sequencing data. This work is critical to uncovering new molecular signals associated with major health issues, including cancer, child health, and development.

About Michael Smith Health Research BC
Michael Smith Health Research BC is the province's health research funding agency. It is dedicated to supporting the best health research, researchers, and research talent to improve health and health care.

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Fanny Dupont and Rachel Lobay Awarded the 2024/2025 Rick White Award

Fanny Dupont and Rachel Lobay Awared the Rick White Award

Fanny Dupont and Rachel Lobay have been awarded the 2024-2025 Rick White Award.

The Rick White Award was established in 2017 to recognize undergraduate and graduate students enrolled in a statistics program who demonstrate excellence in statistical science through collaboration with investigators in another discipline on a substantial application.

Fanny Dupont is supervised by Professor Marie Auger-Methe and has collaborated extensively with ecologists. She is part of a CANSSI collaborative research team that brings together researchers across the fields of statistics, ecology, and medicine to develop statistical models, specifically hidden Markov Models (HMMs), for biologging data. Fanny is the lead author of a paper published in Methods in Ecology & Evolution and has given workshops on hidden Markov models.

Rachel Lobay is supervised by Professor Daniel McDonald and has been working with Delphi Research Group to develop the theory and practice of epidemic detection, tracking, and forecasting. Her contributions include a lead-authored paper in Epidemics and work on two R packages, epiprocess and epipredict. She also co-instructed a workshop on "Epidemic Modelling and Forecasting." 

Congratulations to you both! 

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