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.

00:30 UTC

S201- Vision-Language Models and the Harms of Covert Sexualization

Tuesday October 6, 2026 00:30 - 01:00 UTC

Vision-language models (VLMs) increasingly mediate how bodies are described, moderated, and rendered in online spaces through content moderation, AI-generated images and videos, and descriptions of real bodies. Prior work establishes that VLMs sexually objectify bodies that are partially clothed more than fully clothed ones, and that plus-size bodies — particularly those belonging to women and AFAB persons — are disproportionately censored on social media platforms for being “inappropriate.” However, scholars lack the tools to detect when a model *objectifies* a body, rather than merely describing it, and whether this behavior differs across body *shapes*, rather than just body sizes. This talk describes a study in which we investigate these phenomena using swimwear try-on images matched across body morphology, comparing high-contrast silhouettes (i.e., a smaller waist relative to hips and bust) against lower-contrast silhouettes under identical prompting conditions. We ask whether VLMs describe these bodies differently despite equivalent context and whether unwanted objectification or descriptive drift disproportionately burdens those with high-contrast bodies, with a focus on covert (i.e., safety guardrail compliant) sexualization. By making the harms of these phenomena visible and measurable, this work gives researchers and auditors the ability to hold systems accountable when they objectify or censor women and AFAB persons based on their appearance.

Speakers

Maimuna Majumder

Harvard Medical School & Boston Children's Hospital

Dr. Maimuna (Maia) Majumder (she/they), MPH, PhD (MIT '18) is an Assistant Professor and Inaugural Peter Szolovits Distinguished Scholar in the Computational Health Informatics Program at Harvard Medical School and Boston Children’s Hospital. She is a computational epidemiologist... Read More →

Organizers

Maimuna Majumder

Harvard Medical School & Boston Children's Hospital

Tuesday October 6, 2026 00:30 - 01:00 UTC
Zoom Room #2

Plenary Talk, Technical Statistical Session

Country United States
Session ID 201

04:00 UTC

S203 - AI and Data Science 1

Tuesday October 6, 2026 04:00 - 05:00 UTC

Zoom Room #2

Who Gets Heard? Investigating Accent and Gender Disparities in Automatic Speech Recognition | COMPARATIVE ANALYSIS OF FEATURE EXTRACTION APPROACHES IN A SINGLE-CHANNEL MULTISENSORY SETTING | Bridging Data Silos: A Two-Step Unsupervised Approach to Record Linkage | Mining the Foundations of Truth: Extracting Structured Knowledge Graphs from Unstructured Classical Texts

Speakers

Fouziah Md Yassin

Universiti Malaysia Sabah

Fouziah Md. Yassin is a lecturer in the field of Electronics and Communication Engineering at Universiti Malaysia Sabah (UMS). She obtained her Master of Engineering in Electronic and Communication Engineering from the University of York, United Kingdom. Her research interests include... Read More →

Tisha Prasad

STEM4Change

Tisha Prasad is the co-founder and co-president of STEM4Change, a nonprofit organization dedicated to expanding access to STEM education by teaching students foundational concepts like coding. She also serves as Head of Web Development at VolunteerConnect, where she leads the development... Read More →

Zaturrawiah Ali Omar

Universiti Malaysia Sabah

Zaturrawiah Ali Omar is a lecturer at Universiti Malaysia Sabah (UMS) and a PhD candidate at Universiti Kebangsaan Malaysia (UKM), where her research focuses on record linkage, machine learning, and road traffic injury surveillance in Malaysia. Her work centres on using the Unsupervised... Read More →

Norhafiza Hamzah

UMS

Norhafiza is a lecturer and researcher at Universiti Malaysia Sabah, developing knowledge graph and machine learning frameworks for fact-checking religious misinformation on social media. She teaches courses in Artificial Intelligence, Machine Learning, and Computer Science courses... Read More →

Organizers

IDWSDS Program Committee

IDWSDS

S203 Abstracts pdf

Tuesday October 6, 2026 04:00 - 05:00 UTC
Zoom Room #2

Contributed Session, Technical Statistical Session, Other

Country United States, Malaysia
Session ID 203

07:00 UTC

S204 - Creating Global Connections Through Early Statistical Leadership in Rare Disease Trials

Tuesday October 6, 2026 07:00 - 07:30 UTC

Zoom Room #2

In complex clinical research, collaboration begins well before database lock or final analysis. It begins when statisticians are involved early enough in protocol development to shape what is measurable, sustainable, and meaningful for patients. This presentation uses a rare pediatric dermatology trial as a case study to show how early statistical input can prevent avoidable missing data before the first participant is enrolled.

The original design was scientifically ambitious but operationally burdensome, with frequent in-clinic visits, narrow assessment windows, and substantial caregiver burden. Statistically, this created a foreseeable risk of informative missingness, loss to follow-up, and reduced interpretability in a small and vulnerable population. Early statistical leadership helped reframe the design around feasibility as well as rigor.

The talk will illustrate how collaboration among statisticians, clinicians, programmers, operations teams, and digital partners can reduce this risk. Examples include identifying burden-sensitive endpoints, anticipating missing-data pathways, and considering remote ePRO, image capture, or AI-supported skin assessment to replace selected in-person visits without compromising data quality.

The broader message is that statistics is not only an analysis discipline; it is also a design and connecting discipline.

Speakers

Shrutimita Pokhariyal

PHASTAR

Shrutimita Pokhariyal is an experienced biostatistics professional with over 14 years in clinical research, with expertise spanning multiple phases of clinical trials. Her work includes statistical strategy, study design, protocol and SAP development, and collaboration across cross-functional... Read More →

Chairs/Hosts

Shrutimita Pokhariyal

PHASTAR

Organizers

Shrutimita Pokhariyal

PHASTAR

Tuesday October 6, 2026 07:00 - 07:30 UTC
Zoom Room #2

Plenary Talk, Career or Professional Development Session

Country India
Session ID 204

08:00 UTC

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

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

Zoom Room #2

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

09:00 UTC

S206 - Beyond Simulation: Benchmarking for Method Comparison in Statistics and Machine Learning

Tuesday October 6, 2026 09:00 - 09:30 UTC

Zoom Room #2

When initiating a statistical or machine learning analysis, one of the first and most consequential questions is: which method should be used for a given dataset? Traditional approaches for comparing methods include theoretical derivations and data simulation studies, which provide insight into method performance under controlled conditions. However, these approaches may not fully reflect the complexity of real-world data. Benchmarking—systematic comparison of methods across many real datasets—offers a complementary approach that can improve generalizability and provide practical guidance. Despite its common use in computer science, benchmarking remains underutilized in statistical methodology as new methods continue to emerge.

In this talk, I will discuss benchmarking in the context of statistical and machine learning research and contrast it with theory and simulation. I will outline key principles for conducting rigorous benchmarking studies and illustrate them using two case studies: benchmarking random forest variable selection methods for categorical and continuous outcomes and comparing methods for time-to-event data using the mlr3 framework. Together, these examples demonstrate how benchmarking can enhance scientific rigor, provide practical guidance for method selection, and support more transparent and reproducible methodological research.

Speakers

Jaime Speiser

Associate Professor of Biostatistics and Data Science, Wake Forest University School of Medicine

Dr. Speiser is a biostatistician focused on prediction modeling with applications in medicine. Her work involves developing novel machine learning methodology for prediction modeling, providing guidance on best practices for developing prediction models, and collaborating with medical... Read More →

Organizers

Jaime Speiser

Associate Professor of Biostatistics and Data Science, Wake Forest University School of Medicine

Tuesday October 6, 2026 09:00 - 09:30 UTC
Zoom Room #2

Plenary Talk, Technical Statistical Session

Country United States
Session ID 206

09:30 UTC

S207 - On similarity-based models for Bayesian disease mapping

Tuesday October 6, 2026 09:30 - 10:00 UTC

Zoom Room #2

In the 1970s, the conditionally formulated Gaussian Markov random field (GMRF), known as the conditional autoregressive (CAR) model, was introduced in line with Tobler’s first law of geography: "everything is related to everything else, but near things are more related than distant things." The CAR model uses W, the well-known adjacency matrix that encodes the neighbourhood structure of a spatial lattice (e.g., two areas are neighbours if they share a common border).
Since its introduction, the CAR model has undergone many adaptations, with numerous adaptive models proposed in the literature. However, almost all of these models (to the best of our knowledge, all except ours) still adhere to Tobler’s law. Yet, much of the data collected today – often aggregated at the areal level for confidentiality or other reasons – does not necessarily follow this law.
In this talk, we will show that any extra information representing causes of or correlated with the phenomenon of interest can be used to define a similarity structure, rather than relying solely on geographical neighbourhoods. Using simulated data, we illustrate that similarity-based structures can be more effective than traditional neighbourhood-based structures for smoothing both local and global risks. We will show that the correct identification of high- and low-risk areas, crucial for public health planning and resource allocation, is better achieved when the similarity-based structure is used.

Speakers

Helena Baptista

Management Information Centre (MagIC), NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312, Lisboa, Portugal

Helena Baptista is a highly experienced statistician, researcher, and educator, specializing in applied statistics, forecasting, and time series analysis. She has over 25 years of experience in the pharmaceutical industry, finance, and academia, with a strong background in statistical... Read More →

Organizers

Helena Baptista

Management Information Centre (MagIC), NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312, Lisboa, Portugal

Tuesday October 6, 2026 09:30 - 10:00 UTC
Zoom Room #2

Plenary Talk, Technical Statistical Session

Country Portugal
Session ID 207

10:00 UTC

S208 - Optimal Model selection for incidence of Birth Asphyxia: NICU Centers in Greater Accra Region.

Tuesday October 6, 2026 10:00 - 10:30 UTC

Zoom Room #2

Abstract
Birth asphyxia remains a major contributor to neonatal morbidity and mortality in low- and middle-income countries, particularly in sub-Saharan Africa. This study investigated the determinants of birth asphyxia among newborns using a Quasi-Poisson regression model to account for overdispersion in the count data. Secondary data comprising neonatal and maternal records were analysed using descriptive statistics, correlation analysis, and inferential modelling. The Quasi-Poisson model selected after diagnostic assessment confirmed overdispersion in the response variable, making it more appropriate than the standard Poisson model. The Quasi-Poisson regression model for predicting birth asphyxia is given as : Birth Asphyxia = 1.742 +0.385(Birth Weight) + 0.012(Mothers Age)− 0.088(Gestational Age) + 0.0401(Sex)+ 0.301(Mode of Delivery) + 0.158(Parity)+ 0.067(SURVIVE)
The results showed that birth weight, gestational age, mode of delivery, maternal age, parity, and fetal presentation were significant predictors of birth asphyxia. Specifically, lower birth weight and shorter gestational age were associated with a higher incidence of birth asphyxia, while caesarean delivery and abnormal fetal presentation increased the likelihood of adverse birth outcomes.
Keywords: Birth asphyxia, Quasi-Poisson regression, Gestational age, Neonatal outcomes, Maternal health, Ghana.
Authors:
1. Selina Dadzie (Mphil)
2. Irene Kafui Vorsah Amponsah (PhD)

Speakers

Selina Dadzie

Student

Bio
Miss Selina Dadzie is a graduate student in Statistics at the University of Cape Coast, Ghana, where she is pursuing a Master of Philosophy (MPhil) in Statistics. Her research focuses on “Optimal Model Selection for Incidence of Birth Asphyxia: NICU Centers in Accra”, with particular... Read More →

Organizers

Selina Dadzie

Student

Tuesday October 6, 2026 10:00 - 10:30 UTC
Zoom Room #2

Plenary Talk, Technical Statistical Session

Country Ghana
Session ID 208

10:30 UTC

S209 - Temporal and Regional Variations of Effects of Daily Temperature on Annual Precipitation: A Functional Mixed Effect Model Approach

Tuesday October 6, 2026 10:30 - 11:00 UTC

Zoom Room #2

"Given the increasing threat of global warming, it is important to understand not only
global weather patterns but also regional variations throughout countries. Functional
Linear Mixed-effects Model (FLMM), an emerging statistical tool, provides a comprehensive
framework for analyzing functional data (e.g., data viewed as a function
or curve) with repeated observations, allowing researchers to identify patterns and relationships
in the data. This study applies the functional linear mixed-effects model
(FLMM) to recognize the effects of temporal and regional variations of short-time
weather projection (monthly precipitation on daily temperature). We deployed FLMM
using the daily temperature and monthly precipitation of nine weather stations(Dhaka,
Chattogram (Patenga), Chattogram (Ambagan), Rajshahi, Khulna, Barisal, Sylhet,
Rangpur and Mymensingh) of Bangladesh where each station shares the common
population effects with their individual scalar covariate effects along with same slope
functions. To estimate variance parameters and fixed-effects and random effects, the
REML-based EM algorithm proposed by has been applied. Empirical
results show significant differences in the effects of monthly precipitation on daily
temperature among regions of Bangladesh. We anticipated that FLMM is an emerging
model that can reveal the effects of monthly precipitation and the pace of daily
temperature fluctuations over time."

Speakers

Munniara Yesmin Munni

PME Officer

Munniara Yesmin Munni is a statistician and Monitoring, Evaluation, and Learning (MEL) professional with a Master’s degree in Statistics from Jahangirnagar University, Bangladesh. She currently works with the Christian Commission for Development in Bangladesh (CCDB). Her research... Read More →

Organizers

Munniara Yesmin Munni

PME Officer

Tuesday October 6, 2026 10:30 - 11:00 UTC
Zoom Room #2

Plenary Talk, Technical Statistical Session

Country Bangladesh
Session ID 209

12:00 UTC

S210 - Digitalisation of public institutions in low resource settings.

Tuesday October 6, 2026 12:00 - 13:00 UTC

Zoom Room #2

Digitalizing public institutions in low-resource settings requires balancing technological innovation with systemic equity. Across Africa, infrastructure bottlenecks and high deployment costs often stall digital transformation. This session examines how public sector agencies can successfully transition from fragmented, legacy offline systems to unified digital platforms. We will discuss scalable hybrid architectures that maintain crucial offline functionality for underserved communities while enforcing centralised online data validation, optimizing institutional workflows, and improving financial reconciliation.

Speakers

Louisa Muparuri

ZIMSEC

Dr. Louisa Muparuri is an AI researcher, ICT executive, and digital transformation leader with expertise in artificial intelligence, data science, mathematical modelling, computing, examination systems, and public-sector innovation. She holds a PhD in Mathematics, an MSc in Operations... Read More →

Phyliss Shamiso Mavedzenge

Pulse Pharmaceuticals

Ms Phyliss Mavedzenge. Currently a Resident Innovator and Researcher at Zimbabwe Centre for High Performance Computing and a Business Analytics and Predictive Modelling, short course facilitator at Bindura University . Working on developing systems and models that cater to Zimbabweans... Read More →

Salome Maheya

African Energy Commission of the African Union

Salome Maheya, Senior Policy Officer for Energy Statistics in the African Energy Commission (AFREC) of the African Union. She is responsible for coordinating the production of annual Energy Balances, Energy Modelling and producing energy forecasts for Africa. She is responsible for... Read More →

Lerdinia Mapepa

Women's University in Africa

Ms. L. V. Mapepa is an Academic in the Faculty of Management, Department of Information Systems at the Women’s University in Africa where she has served the institution for over five years across the various fields of teaching, learning and Innovation, Research and STEM initiatives... Read More →

Chairs/Hosts

Chipo Zidana

NUST

Dr. Chipo Zidana is a senior statistician, bio-statistical consultant, and data integration specialist with over 15 years of experience bridging advanced analytical modeling with national policy frameworks. She holds a PhD in Statistics from Çukurova University, specializing in mixture... Read More →

Organizers

Chipo Zidana

NUST

S210 Abstracts pdf

Tuesday October 6, 2026 12:00 - 13:00 UTC
Zoom Room #2

Invited Session, Technical Statistical Session

Session ID 210

13:00 UTC

S211 - Statistical applications across various domains from India

Tuesday October 6, 2026 13:00 - 14:00 UTC

Zoom Room #2

Statistical applications and data analytics drive critical advancements across major global sectors. By leveraging historical data and predictive modeling, these methodologies improve efficiency, reduce risks, and optimize resource allocation worldwide. This session will focus on how statistical tools and methodologies enable data-driven decision making aacross different domains such as banking, business analytics, agriculture and healthcare in India. We have speakers from academia, government and different industries providing us with an inside journey of their work.

Speakers

Sumaiya Sande

Wells Fargo

Dr. Sumaiya Sande is a Data Scientist and Credit Risk modelling professional with a PhD in
Statistics and Applied Probability from the National University of Singapore. She specializes in
machine learning, deep learning, statistical modeling, and credit risk analytics, with exp... Read More →

Swastika Mohapatro

Google

Swastika Mohapatra is a Research Data Scientist on the Analytics, Insights, and Measurement team within Google Ads. Over the past two years, her work has focused on building models to accurately measure digital ad campaign performance, sitting at the intersection of predictive modeling... Read More →

Yogita Gharde

ICAR–Directorate of Weed Research (ICAR-DWR), Jabalpur, India.

Dr. Yogita Gharde is currently serving as Senior Scientist (Agricultural Statistics) at the
ICAR–Directorate of Weed Research (ICAR-DWR), Jabalpur, Madhya Pradesh, India. She
earned her M.Sc. and Ph.D. in Agricultural Statistics from the ICAR–Indian Agricultural
Statistics... Read More →

Sharvari Shukla

Symbiosis Statistical Institute, Symbiosis International University

Sharvari Shukla is a Professor and Director at Symbiosis Statistical
Institute, India. Sharvari is a thought leader and well regarded
influencer working at the intersection of Medical Statistics and Data
Science. In a prior assignment she was leading clinical research and
cli... Read More →

Chairs/Hosts

Sayantee Jana

Organizers

Sayantee Jana

S211 Abstracts pdf

Tuesday October 6, 2026 13:00 - 14:00 UTC
Zoom Room #2

Invited Session, Technical Statistical Session

Country India
Session ID 211

14:00 UTC

S212 - Career Perspectives from Industry in the U.S.

Tuesday October 6, 2026 14:00 - 15:00 UTC

Zoom Room #2

This session will feature three 10-minute presentations from women working across industry sectors, including transportation, pharmaceuticals, and government research. Speakers will share insights into their career paths, current roles, and day-to-day responsibilities. The presentations will be followed by a moderated discussion exploring key topics such as career progression, mentorship, opportunities for growth, and leadership, offering attendees practical perspectives on navigating and advancing in the field of statistics and data science.

Speakers

Sonali Garg

Xilio Therapeutics

Sonali Garg is an accomplished statistical programming leader with nearly 20 years of experience across the pharma, biotech, and CRO industries. She holds a graduate degree in biostatistics and an undergraduate degree in statistics.

Throughout her career, Sonali has guided numerous compounds through complex global submission, approval, and post-approval processes. She has prepared multiple successful submissions to the FDA and EMA, navigated regulatory audits, and worked directly with regulators and senior management... Read More →

Christian Douglas

RTI International

Dr. Christian E. Douglas is a Senior Research Statistician at RTI International with more than 14 years of experience supporting clinical trials and large-scale observational studies. Her expertise includes longitudinal data analysis, adaptive trial design, power and sample size estimation... Read More →

Ashley Asmus

RSG Inc.

Ashley Asmus is a researcher, project manager, and data scientist with over nine years of experience working with complex datasets, including six years focused on travel survey data in both public and private sectors. Prior to joining RSG Inc., she served as lead researcher and deputy... Read More →

Chairs/Hosts

Sophie Salem

Statistician, RTI International

Sophie Salem is an early career statistician at RTI International. She provides statistical support on various large-scale federally funded surveys, including the National Health and Nutrition Examination Survey and the National Dementia Workforce Study. She has undergraduate research... Read More →

Organizers

Cynthia Bland

Past Past President, CWS; RTI

I'm the Past Past President of CWS and also a survey statistician and center director at RTI International. I helped start a CWS mentoring initiative called Flash Mentoring and I support our emergent needs mentoring. Both require CWS membership, which is free to students. Please consider... Read More →

Tuesday October 6, 2026 14:00 - 15:00 UTC
Zoom Room #2

Invited Panel, Career or Professional Development Session

Country United States
Session ID 212

15:00 UTC

S213 - Causal Outside the Classroom: How is causal inference used in day-to-day working environments?

Tuesday October 6, 2026 15:00 - 16:00 UTC

Zoom Room #2

Causal inference is a term that has become a buzzword and a popular field of research in many fields recently, and arises often in statistics. Causal methodologies can sound overly complex to many collaborators, and others may fixate on the need to have causal results from all possible studies. New researchers and scientists are left with questions of how often to employ these newer methods and frameworks of thinking, when it is appropriate to do so, and what results can actually be drawn from causal analyses.
In this session, we will hear from four professionals who use causal inference in their day-to-day practice. First, Dr. Candice Johnson will discuss whether certain causal studies are inherently gendered by examining hazards in the workforce in male-dominated fields. Dr. Lucy McGowan will talk about whether interaction effects are feasible, clinically significant, and better than subgroup-specific effects in real-world trials. Dr. Maria DeYoreo will explore inferential approaches to estimate causal effects from a study on the effect of state-funded family planning policies on birth outcomes. Finally, Dr. Lu Wang will discuss applying a causal framework to personalized healthcare, demonstrating how causal inference can support flexible, patient-centered decision-making in routine clinical practice.

Speakers

Lucy D’Agostino McGowan

Associate Professor, Wake Forest University

Lucy D’Agostino McGowan is an associate professor in the Department of Statistical Sciences at Wake Forest University. She received her PhD in Biostatistics from Vanderbilt University and completed her postdoctoral training at Johns Hopkins University Bloomberg School of Public... Read More →

Candice Johnson

Michigan State University

Candice Johnson is Assistant Professor in the Department of Epidemiology and Biostatistics at Michigan State University. She studies how work-related exposures and policies affect the health of workers and their families, with a focus on women and pregnant women in the workforce... Read More →

Maria DeYoreo

RAND

Maria DeYoreo is a senior statistician at RAND. Her substantive interests include health care quality and performance measurement, Medicare Advantage, hospice care, and maternal/child health. Her methodological interests include causal inference and quasi-experimental methods, Bayesian... Read More →

Lu Wang

University of Michigan

Dr. Lu Wang received her PhD in Biostatistics from Harvard University in 2008 and joined the faculty at the University of Michigan in the same year. Her research focuses on statistical methods for evaluating dynamic treatment regimes, personalized health care, nonparametric and semiparametric... Read More →

Chairs/Hosts

Ashley Mullan

Vanderbilt University

Ashley Mullan is a PhD student and research assistant in the Department of Biostatistics at Vanderbilt University. She earned her MS in Statistics from Wake Forest University. Her research interests include both methods development for measurement error and missing data and their... Read More →

Organizers

Jamie Joseph

Henry Ford Health

Dr. Jamie Joseph is a faculty biostatistician in the Department of Public Health Sciences at Henry Ford Health with a joint appointment as an Assistant Professor of Research at Michigan State University. She earned her PhD in Biostatistics from Vanderbilt University in 2024. Currently... Read More →

S213 Abstracts pdf

Tuesday October 6, 2026 15:00 - 16:00 UTC
Zoom Room #2

Invited Session, Technical Statistical Session

Session ID 213

17:00 UTC

S214 - Beyond Automation: Using Generative AI to Elevate Critical Thinking, Personalization, Engagement, and Analytics Instruction

Tuesday October 6, 2026 17:00 - 18:00 UTC

Zoom Room #2

Generative AI is rapidly reshaping the landscape of statistics and business analytics education, offering new opportunities to improve course design, assignment development, and feedback processes. This panel will share practical strategies for integrating AI into teaching workflows while maintaining statistical rigor and fostering student understanding.

We highlight approaches for AI-assisted case and assignment design, including adaptive scenarios in which students pose questions, request instructor-controlled synthetic data, and iteratively refine their analyses. These methods promote deeper engagement with modeling choices, assumptions, and critical thinking-core goals of statistics education.

The panel also demonstrates how AI can support assessment and feedback, from automated classwide test analysis to personalized guidance that helps students interpret results and correct misconceptions.

Attendees will leave with concrete examples, implementation tips, and considerations for responsible use of AI tools in statistics and business analytics classrooms.

Speakers

George Reckk

Assoc. Prof. of Practice, Babson College

Mr. Recck has taught at Babson College since 1984. Prior to that, Mr. Recck worked his way toward his undergraduate and MBA degrees from Babson while working in Babson's Computer Center. After receiving his MBA from Babson in 1984, Mr. Recck was promoted to Director of Academic Computer... Read More →

John Draper

The Ohio State University

John Draper is an Associate Professor of Clinical Operations and Business Analytics in the Fisher College of Business at The Ohio State University. He has a PhD and MS in statistics from Ohio State as well as BS degrees in mathematics and statistics from Florida State University... Read More →

Ismael Talke

The Ohio State University

Ismael Talke is a Senior Lecturer in the Management Science Department. He joined Fisher in 2019 after serving as a visiting faculty at Miami University Ohio, department of Information Systems and Analytics, where he taught undergraduate Business Analytics, Statistics, and Business... Read More →

Cheryl Edelmann

Senior Lecturer, University of Dayton

Cheryl Edelmann is a professor of Business Analytics in the Department of MIS, OSC, and Business Analytics at the University of Dayton. Cheryl educates future business professionals in the area of statistics, helping them develop the skills needed to succeed in today’s data-driven... Read More →

Chairs/Hosts

Jessica Kohlschmidt

Caucus for Women in Statistics and Data Science

Dr. Jessica K. Kohlschmidt is a distinguished biostatistician, educator, and leader in the statistical community. A first-generation college student, her early passion for math and teaching evolved into a dedicated career in statistics after discovering its real-world applications... Read More →

Organizers

Jessica Kohlschmidt

Caucus for Women in Statistics and Data Science

Tuesday October 6, 2026 17:00 - 18:00 UTC
Zoom Room #2

Invited Panel, Career or Professional Development Session

Country United States
Session ID 214

20:00 UTC

S215 - Frontiers in Statistical Modeling: High-Impact Doctoral Research from Argentina (Fronteras en la Modelización Estadística: Investigaciones Doctorales de Alto Impacto desde Argentina )

Tuesday October 6, 2026 20:00 - 21:00 UTC

Zoom Room #2

Statistical training in Argentina is characterized by quantitative rigor and methodological innovation. Postgraduate programs of excellence, like the PhD in Statistics at the Universidad Nacional de Rosario, build this foundation. This session showcases this training through four doctoral theses that propose cutting-edge solutions for high dimensionality, spatial dependence, incomplete data, and outliers.
Attendees will learn about:
Associative Mapping: Verónica Lac Prugent combines Multivariate Elastic Net models to address quantitative and qualitative responses in genetic resources, ensuring the empirical robustness of associations.
Multi-Environment Trials: Julia Angelini addresses the limitations of the Sites Regression (SREG) model by proposing an Expectation-Maximization (EM) based imputation method and robust variants to reduce the impact of outliers.
Spatial Prediction: Mariel Lovatto introduces a semiparametric spatial autoregressive model that captures spatial dependence without relying on strict parametric covariance, resulting in improved predictive performance.
Zero-Inflated Data: María José Llop introduces a robust EM-type estimation approach for the partially linear zero-inflated Poisson (PLZIP) regression model, effectively handling extreme observations in complex relationships.
This panel highlights the level of Argentine science and its capacity to generate statistical knowledge with global impact.

Speakers

Verónica Patricia Lac Prugent

National University of Comahue (Universidad Nacional del Comahue), Argentina

She holds a Bachelor's degree in Statistics, a Specialization in Epidemiology, and is a PhD in Statistics. She works as a Professor and researcher in the Department of Statistics at the Faculty of Economics and Administration of the Universidad Nacional del Comahue, where she also... Read More →

Julia Angelini

Facultad de ciencias económicas y estadística, Facultad de Cs. Económicas y Estadística, Universidad Nacional de Rosario

She holds a Bachelor's degree in Statistics, a Specialization in Bioinformatics, and a PhD in Statistics. She serves as a Professor at the Faculty of Economic Sciences and Statistics of the Universidad Nacional de Rosario and as a senior advanced data scientist at NaranjaX. Currently... Read More →

Mariel Lovatto

Universidad Nacional del Litoral (UNL) - CONICET

She holds a degree in Mathematics from the Universidad Nacional del Litoral, and a Master's and a PhD in Statistics from the Universidad Nacional de Rosario. She currently holds a postdoctoral fellowship from CONICET and serves as Head Teaching Assistant at the Faculty of Chemical... Read More →

María José Llop

Facultad de Ingeniería Química, Universidad Nacional del Litoral

She holds a PhD in Statistics from the Universidad Nacional de Rosario and a Bachelor's degree in Applied Mathematics from the Universidad Nacional del Litoral. She is currently a postdoctoral fellow at CONICET; she serves as a Professor at the Faculty of Chemical Engineering and... Read More →

Chairs/Hosts

María Inés Stimolo

Organizers

María Inés Stimolo

Tuesday October 6, 2026 20:00 - 21:00 UTC
Zoom Room #2

Invited Panel, Technical Statistical Session

Country Argentina
Session ID 215

21:00 UTC

S216 - Statistical Methods and Applications 2

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

Zoom Room #2

Mixture-based Nonparametric Estimation of Spatial Covariance Functions with Applications to HIV Key Population Size Estimation across Sub-Saharan Africa | Influenza hospitalization tracking using internet search data and ILI surveillance | The Impact of Recent State Staffing Minimum Mandates on Nursing Home Residents|From Raw Wearable Data to Scientific Inference: A Reproducible Pipeline for Processing Commercial Step Count Data in Aging Cohorts

Speakers

Manushi Siriwardana

Penn State

Manushi Siriwardana is a Ph.D. student in Statistics at Penn State. She will be entering her fourth year of the Ph.D. program in Fall 2024. Her research focuses on spatial statistics, public health, and computational statistics. She is interested in developing statistical methodology... Read More →

Hanqi Shi

Swarthmore College

Hanqi Shi is an undergraduate student at Swarthmore College majoring in Statistics and Computer Science. Her research interests include statistical modeling, machine learning, and interdisciplinary applications.

Angira Mondal

University of Pennsylvania

Angira Mondal is a Senior Statistical Analyst at the Perelman School of Medicine, University of Pennsylvania, where she works in the Policy and Economics of Disability, Aging, and Long Term Care (PEDAL) Lab. Her research focuses on complex healthcare data, including claims analysis... Read More →

Nannan Bo

Duke University; Dartmouth College

Nannan Bo recently completed her Master of Biostatistics at Duke University and will begin her PhD training in the Quantitative Biomedical Sciences program at Dartmouth College in Fall 2026. Her research interests span clinical trial design, Bayesian methods, measurement error, wearable... Read More →

Organizers

IDWSDS Program Committee

IDWSDS

S216 Abstracts pdf

Tuesday October 6, 2026 21:00 - 22:00 UTC
Zoom Room #2

Contributed Session, Technical Statistical Session

Country United States
Session ID 216

22:00 UTC

S217 - Experiences of Early Career Biostatisticians in Clinical Trial and Data Coordinating Centers

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

Zoom Room #2

This session will feature four early career researchers working in academic data coordinating and/or clinical trial centers. The speakers will talk about their (collaborative) biostatistician roles and responsibilities in their respective institutions, sharing about their training journeys and lessons learned along the way.

Speakers

Emily Roberts

University of Iowa

Dr. Emily Roberts is an assistant professor of biostatistics at the University of Iowa. She completed her PhD in Biostatistics at the University of Michigan in 2022, where her dissertation focused on Causal Inference Methods and Intermediate Endpoints in Randomized Clinical Trials... Read More →

Megan McCabe

Assistant Professor, Department of Biostatistics, University of Alabama at Birmingham

Dr. Megan McCabe is an Assistant Professor in the Department of Biostatistics at the University of Alabama at Birmingham (UAB), and the Assistant Director for Clinical Trials Development for the DATA coordinating and Collaborative Research Unit (DATA CRU). She graduated with her PhD... Read More →

Madeline Abbott

Harvard University

I am a Research Associate in the Center for Biostatistics in AIDS Research (CBAR) at Harvard University. I work on clinical trials for the treatment and prevention of HIV and tuberculosis, collaborating closely with clinicians in the International Maternal Pediatric Adolescent AIDS... Read More →

Margaret Banker

Northwestern University

Dr. Margaret Banker is an Assistant Professor of Biostatistics and Informatics in the Department of Preventive Medicine at Northwestern University Feinberg School of Medicine. As a member of the Northwestern University Data Analysis & Coordinating Center (NUDACC), she collaborates... Read More →

Chairs/Hosts

Emily Roberts

University of Iowa

Organizers

Emily Roberts

University of Iowa

S217 Abstracts pdf

Tuesday October 6, 2026 22:00 - 23:00 UTC
Zoom Room #2

Invited Session, Career or Professional Development Session

Country United States
Session ID 217

00:30 UTC

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