International Day Of Women in Statistics and Data Science: Full Schedule

Registration opens August 15th at www.idwsds.org.

You will be able to validate your attendance (Check-In to sessions) using your personal schedule.

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08:00 UTC

S205 - Time-to-event data in biometry: Challenges, biases and perspectives

Tuesday October 6, 2026 08:00 - 09:00 UTC

In applied medical statistics, researchers encounter a wide variety of data structures. Among these, time-to-event data play a central role including survival times, transitions between disease stages, and sequences of medical events or progressions of patients’ states over time.
A broad spectrum of analytical approaches is available, ranging from (semi-)parametric methods such as the Cox proportional hazards model to flexible spline-based and other advanced modeling strategies. Depending on the motivation we encounter unique problems as well as unique solutions on which we want to shed light on in this session. Each setting introduces its own methodological challenges and potential sources of bias.
We aim to highlight key issues that arise when working with time-to-event data, including common pitfalls, structural complexities, and opportunities for methodological innovation. We will present different perspectives on model choice, interpretation, and discuss how careful consideration of the underlying data-generating mechanisms can inform both statistical analysis and the design of clinically relevant studies.

Speakers

Marilena Müller

German Cancer Research Center, Heidelberg, Germany

Marilena Müller is a postdoctoral scientist in the Biostatistics department at the German Cancer Research Center in Heidelberg, Germany. She received her B.Sc., M.Sc. and Dr. rer. nat. at the Mathematical Institute at Heidelberg University. The field of studies concerning her dissertation... Read More →

Judith Vilsmeier

Institute of Statistics, Ulm University

Judith Vilsmeier is a doctoral candidate in Biostatistics at Ulm University and a research assistant at the Institute of Statistics. She received both her B.Sc. and M.Sc. in Mathematical Biometry from Ulm University. Her current research interests involve nonstandard event histories... Read More →

Sandra Schmeller

Institute of Statistics, Ulm University

Sandra Schmeller is a postdoctoral researcher in Biostatistics at the Institute of Statistics, Ulm University. She received both her B.Sc. and M.Sc. in Mathematical Biometry from Ulm University and completed her PhD in Biostatistics at Ulm University. Prior to her doctoral studies... Read More →

Ema Požek

Institute for Biostatistics and Medical Informatics, Faculty of Medicine, University of Ljubljana, Slovenia

Ema Požek is a PhD student in statistics at the Institute for Biostatistics and Medical Informatics, Faculty of Medicine, University of Ljubljana. Her methodological interests lie in survival analysis and simulation studies, and her research focuses on developing statistical methods... Read More →

Chairs/Hosts

Marilena Müller

German Cancer Research Center, Heidelberg, Germany

Organizers

Marilena Müller

German Cancer Research Center, Heidelberg, Germany

S205 Abstracts pdf

Tuesday October 6, 2026 08:00 - 09:00 UTC
Zoom Room #2

Invited Session, Technical Statistical Session

Country Germany
Session ID 205

10:00 UTC

S111- Strengthening Statistical Practice Through Collaboration: Perspectives from Women Leaders in STRATOS

Tuesday October 6, 2026 10:00 - 11:00 UTC

Zoom Room #1

The STRATOS (STRengthening Analytical Thinking for Observational Studies) Initiative is an international collaboration of statistical and methodological experts dedicated to improving the design, conduct, analysis, and reporting of biomedical and observational research. Through accessible guidance documents, recommendations, and educational resources, STRATOS seeks to bridge methodological advances and statistical practice.
Presentations illustrate diverse approaches to improving research quality, including the development of international recommendations for analyzing patient-reported outcomes in oncology trials, innovative strategies for teaching Initial Data Analysis (IDA), consensus-based development of guidance for statistical analysis plans in observational studies, and principled approaches to defining estimands and interpreting quality-of-life outcomes. These examples demonstrate how statistical thinking can improve the transparency, reproducibility, relevance, and interpretability of scientific research.
Together, these talks demonstrate the impact of international collaboration, interdisciplinary research, translating complex statistical concepts into practical tools for researchers. The session also highlights the important leadership role of women statisticians in shaping methodological standards, educational initiatives, and research practices.

Speakers

Marianne Huebner

Michigan State University

Marianne Huebner is Professor of Statistics and Director of the Center for Statistical Training and Consulting (CSTAT) at Michigan State University, USA. Her research focuses on statistical methodology for improving transparency, reproducibility, and quality in health and observational... Read More →

Saskia Le Cessie

Leiden University Medical Centre

Prof. Saskia le Cessie is a medical statistician working at the departments of Clinical Epidemiology and Biomedical Data Sciences of Leiden University Medical Center. Her research in medical statistics and epidemiological methods involves (1) collaboration in research projects of... Read More →

Els Goetghebeur

Ghent University

Els Goetghebeur is Professor of Statistics at Ghent University, Belgium, and a leading researcher in causal inference and biostatistical methodology. She co-chairs the Causal Inference Topic Group of the STRATOS Initiative and has contributed extensively to methodological research... Read More →

Lara Lusa

University of Primosrka

Lara Lusa is a professor of Statistics at the Faculty of Mathematics, Natural Sciences and Information Technologies of the University of Primorska, Slovenia and Institute for Biostatistics and Medical Informatics of the University of Ljubljana, Slovenia. Her current research interests... Read More →

Chairs/Hosts

Marianne Huebner

Michigan State University

Organizers

Marianne Huebner

Michigan State University

S111 Abstracts pdf

Tuesday October 6, 2026 10:00 - 11:00 UTC
Zoom Room #1

Invited Session, Technical Statistical Session

Country Germany
Session ID 111

12:00 UTC

S112 - Predicting the Right Treatment for the Right Patient: An AI-Powered Decision Support Framework Based on Predicted Individual Treatment Effects

Tuesday October 6, 2026 12:00 - 12:30 UTC

Zoom Room #1

Medical decisions—ranging from diagnosis to treatment selection—are inherently uncertain. Clinicians often rely on heuristic, experience-driven processes to integrate heterogeneous data. In this context, Predicted Individual Treatment Effects (PITE) offer a principled statistical framework to quantify how much a specific patient benefits from one treatment over another.

Advances in computational systems now enable machines to identify complex patterns within large datasets, facilitating a shift toward data-driven, individualized healthcare. This work explores using PITE to support clinical decision-making across diverse diseases and contexts. We address critical questions: which AI methods suit specific clinical datasets, how PITE should be validated, and how outcome complexity affects tool reliability.

We demonstrate PITE-based models in various disease settings, each posing unique methodological challenges. Our results show that even under real-world conditions—such as missing data—predictive models maintain interpretability and generate estimates that support clinicians. Notably, our findings highlight that internal validation is insufficient; external validation is essential for robust predictions.

Ultimately, effective PITE-based support requires more than modeling. It demands an adaptive, continuously learning system integrating data management, modeling strategies, regulatory-grade interpretability, and ongoing validation to translate evidence into precise.

Speakers

Pamela Solano

PhD Researcher, Faculty of Computer Science and Data Science, Regensburg University

I am Pamela Solano, a statistician and researcher at the University of Regensburg, Germany. Since 2014, I have worked as a biostatistician. Following my PhD in 2018, my research focus toward statistical modeling approaches with direct societal relevance. I began working in environmental... Read More →

Organizers

Pamela Solano

PhD Researcher, Faculty of Computer Science and Data Science, Regensburg University

Tuesday October 6, 2026 12:00 - 12:30 UTC
Zoom Room #1

Plenary Talk, Technical Statistical Session

Country Germany
Session ID 112

21:00 UTC

S315 - AI and Data Science 3

Tuesday October 6, 2026 21:00 - 22:00 UTC

Zoom Room #3

From Law to Data Governance: Rebuilding from Scratch at the Intersection of Legal Frameworks and AI | AI in Long‑Term Care: Practical Tools for Workflow Efficiency, Documentation Support, and Caregiver Well‑Being | Which one to use, traditional Algorithms or AI? Approaches for Computational Problem-Solving | Optimizing Portfolio Allocation with Unsupervised Machine Learning

Speakers

Charity Nyamuchengwa

clarkson university

Charity is an applied AI practitioner focused on improving workflows, documentation, and safety in long‑term care environments. She develops practical, caregiver‑centered tools including an AI‑assisted documentation helper, a medication‑workflow guidance system, and a synthetic... Read More →

Weijie Pang

Wentworth Institute of Technology

Weijie Pang is a tenure-track assistant professor in School of Computing and Data Science at Wentworth Institute of Technology. After received Ph.D. from Worcester Polytechnic Institute and B.S. and M.S. from Beijing University of Technology, Dr. Pang finished the Post-doc program... Read More →

Daniela Márquez

Universidad Autónoma de Chiapas

I am a lawyer-turned-data-scientist based in Aguascalientes, Mexico. After more than eight years working in Mexico's Federal Judiciary, I pursued an M.Sc. in Data Science, Big Data and Business Analytics at Universidad Complutense de Madrid and am currently completing a B.Sc. in Statistics... Read More →

Jae Sook Cheong

Data Steward with Data Governance

Dr. Jae Sook Cheong is a senior researcher and a data professional. Her works are in the area of data governance, knowledge representation with data analysis, algorithm analysis, and machine learning. With many years of experience across academia, industry, and national R&D institutes... Read More →

Organizers

IDWSDS Program Committee

IDWSDS

S314 Abstracts pdf

Tuesday October 6, 2026 21:00 - 22:00 UTC
Zoom Room #3

Contributed Session, Career or Professional Development Session, Other

Country Mexico, United States, Germany
Session ID 314

22:00 UTC

S316 - AI and Data Science 4

Tuesday October 6, 2026 22:00 - 23:00 UTC

Zoom Room #3

Bayesian Time-Dynamic Mixed-Effects Modeling of Longitudinal Data | When the Data Goes Quiet: Using HDBSCAN to Reveal Gendered Street Crime Patterns Hidden in Official Crime Data | From Gut to Data: A Replicable Forecasting Framework for Rural Micro-Retailers in Data-Poor Environments|Collective Intelligence Lead to Open Innovations

Speakers

Nisha Daniel Raju Daniel

Bayer AG

Dr. Nisha Daniel R is a qualified Dental Surgeon seamlessly bridging the worlds of clinical medicine and advanced digital health informatics. Currently completing her Master of Science in Data Science for Health and Social Care at the University of Edinburgh, her expertise lies at... Read More →

Makena Grigsby

University of California, Riverside

Makena Grigsby recently earned her M.S. in Statistics from the University of California, Riverside. Her academic work focuses on Bayesian modeling, survival analysis, machine learning, and statistical computing. She is especially interested in developing and applying flexible statistical... Read More →

Farah Ahmed

HORUS VISTA LABS and OSU

Farah Ahmed is a Senior Analytics and Insights Lead at Equitable Advisors and the founder and Principal Data Scientist at Horus Vista Labs, an applied data science consultancy serving rural and underserved small businesses. Her work spans demand forecasting, causal inference, and... Read More →

Organizers

IDWSDS Program Committee

IDWSDS

S315 Abstracts pdf

Tuesday October 6, 2026 22:00 - 23:00 UTC
Zoom Room #3

Contributed Session, Technical Statistical Session, Career or Professional Development Session

Country United States, Germany
Session ID 315

08:00 UTC

10:00 UTC

12:00 UTC

21:00 UTC

22:00 UTC

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