Registration & Talk details

We invite you to a speaker series focused on learning about equity, diversity and inclusion practices and initiatives in Statistics and Data Science. Our next speaker will be Dr. Aleksandra Korolova, Assistant Professor of Computer Science and Public Affairs, Princeton University. 

Date/Time: March 26, 2026, 11:00am – 12:00pm

Talk title: Lessons from auditing the hidden societal impacts of ad delivery algorithms

Abstract: Although targeted advertising has been touted as a way to give advertisers a choice in who they reach, increasingly, ad delivery algorithms designed by the ad platforms are invisibly refining those choices. In this talk, I will present our findings from "black-box" auditing of the role of ad delivery algorithms in shaping who sees opportunity and political ads using only the tools and data accessible to any advertiser. I will then discuss legal and policy efforts to mitigate the harmful effects of ad delivery in these domains, including their shortcomings and potential paths forward.

Bio: Aleksandra Korolova is an Assistant Professor of Computer Science and Public Affairs at Princeton University, where she is also affiliated with the Center for Information Technology Policy. She studies societal impacts of AI, and develops and deploys algorithms and technologies that enable data-driven innovations while preserving privacy, fairness, and robustness. She also designs and performs algorithm and AI audits. Aleksandra is a co-winner of the 2011 PET Award for outstanding research in privacy enhancing technologies for being among the first to identify privacy risks of microtargeted advertising. Her work on RAPPOR, the first commercial deployment of differential privacy, has been recognized by ACM Conference on Computer and Communications Security 2024 Test-of-Time Award. Aleksandra's research on discrimination in ad delivery has received the 2019 CSCW Honorable Mention Award and Recognition of Contribution to Diversity and Inclusion, was a runner-up for the 2021 WWW Best Student Paper Award, and was a winner of the 2025 FAccT Best Paper Award. Aleksandra is a recipient of the Presidential Early Career Award for Scientists and Engineers, a Sloan Research Fellowship and the NSF CAREER Award.

If you would like to attend this virtual talk, please register using the link below:

https://ubc.zoom.us/meeting/register/bTdpB5a2S5SngAX1d1ch6Q

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This talk is one of the Statistics Equity, Diversity and Inclusion Speaker Series. For more information, please visit: https://www.stat.ubc.ca/seminar-series

Zoom Registration

https://ubc.zoom.us/meeting/register/Z_eCE0H9QqGknxiuC66eBg  

Title

From Diffusion Models to Schrödinger Bridges - When Generative Modeling meets Optimal Transport

Abstract

Denoising Diffusion models have revolutionized generative modeling. Conceptually, these methods define a transport mechanism from a noise distribution to a data distribution. Recent advancements have extended this framework to define transport maps between arbitrary distributions, significantly expanding the potential for unpaired data translation. However, existing methods often fail to approximate optimal transport maps, which are theoretically known to possess advantageous properties. In this talk, we will show how one can modify current methodologies to compute Schrödinger bridges—an entropy-regularized variant of dynamic optimal transport. We will demonstrate this methodology on a variety of unpaired data translation tasks.

van Eeden speakers

Dr. Arnaud Doucet has been invited to be this year's van Eeden speaker by the graduate students in the Department of Statistics at the University of British Columbia. A van Eeden speaker is a prominent statistician who is chosen each year to give a lecture, supported by the UBC Constance van Eeden Fund (https://www.stat.ubc.ca/constance-van-eeden-fund). The 2025 seminar is additionally sponsored by the Canadian Statistical Sciences Institute (CANSSI), the Pacific Institute for the Mathematical Sciences (PIMS), and the Walter H. Gage Memorial Fund.

To join this seminar virtually: Please request Zoom connection details from ea@stat.ubc.ca.

Abstract: The work of the Flexible Learning in Statistics Group ranges from conducting studies of important aspects of statistics education to developing and testing resources for difficult statistics concepts. In this seminar, students will present several recent projects: using student focus groups to assess Shiny apps, developing and testing interactive resources to improve understanding of Bayesian inference, enhancing Stat 251 labs by creating active learning material and introducing pre-lab quizzes, and conducting a study of the impact of exam question wording on the performance of students with English as an Additional Language (EAL). You’ll also hear about StatEngage, the ASDa-led project to guide students through the challenges of consulting.

To join this seminar virtually: Please request Zoom connection details from ea@stat.ubc.ca.

Abstract: This session will be a perspective of what working as a statistics consultant in a contract research organisation for pharmaceutical/biotech companies entails. In addition to an overview of potential career paths, the specific critical tasks and responsibilities involved for a statistician working in real-world data will be discussed.

A look into the type of statistical methodologies through case studies will be provided, demonstrating how they play a role in drug development, regulatory submissions, and health technology assessments. This sets the stage for the discussion of potential research collaborations between UBC students and industry, where students can have the opportunity to advance health research whilst gaining experience on whether a career in health research is of interest.

Zoom Registration

https://ubc.zoom.us/meeting/register/u5Mpfu-orz4uHtMoS6AcwTE_0VZ_DDEghNdA

(If you have any questions about your registration or the seminar, please contact ea@stat.ubc.ca.)

Title

Ethical AI is More than Loss Functions

Abstract

What constitutes a fair algorithm and the ethical use of data is context specific. Algorithms are not neutral and optimization choices will reflect a specific value system and the distribution of power to make these decisions. Data also reflect societal bias, such as structural racism. Ethics and fairness research for health AI spans many fields, including policy, medicine, computer science, sociology, and statistics. Considerations go well beyond loss functions and typical measures of statistical assessment. This talk includes discussion of team construction, who decides the research question, minimum standards for research quality, reproducibility, least publishable units, and community engaged research. Overarching themes are also that centering health equity and developing methodology tailored to specific health questions are critical given the stakes involved.

van Eeden speakers

Professor Sherri Rose has been invited to be this year's van Eeden speaker by the graduate students in the Department of Statistics at the University of British Columbia. A van Eeden speaker is a prominent statistician who is chosen each year to give a lecture, supported by the UBC Constance van Eeden Fund. The 2024 seminar is additionally sponsored by the Canadian Statistical Sciences Institute (CANSSI), the Pacific Institute for the Mathematical Sciences (PIMS), and the Walter H. Gage Memorial Fund.