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Registration opens August 15th at www.idwsds.org.
Type: Invited Session clear filter
Tuesday, October 6
 

02:00 UTC

S103- Decoding Health: AI and Big Data at the Frontier of Precision Medicine
Tuesday October 6, 2026 02:00 - 03:00 UTC
Zoom Room #1
This session explores how artificial intelligence and data science are driving the next generation of precision medicine, drawing on large-scale biobanks, electronic health records (EHRs), and genomic data from both academia and industry. Dr. Marie Loh (Nanyang Technological University / Genome Institute of Singapore) will discuss translational opportunities from HELIOS-SG100K, a multi-ethnic Asian population cohort with rich phenotypic and molecular data, with examples in cardiometabolic disease and atopic dermatitis. Ms. Chih-Ting Yang (Vanderbilt University) will use the All of Us Research Program to show how biobank data can be translated into longitudinal disease staging, illustrated through a study of cardiovascular-kidney-metabolic syndrome. Dr. Sarah Lotspeich (Wake Forest University) will present an LLM-enhanced, ICD-10-based algorithm for recovering missing EHR data, demonstrating accuracy comparable to expert chart review at scale. Rounding out the session, Dr. Christine Hsiung will bring an industry perspective from the genetics sector, sharing applied research insights from Taiwan Biobank genomic data and translational pipelines. Together, these talks span academic and industry approaches, genomic profiling, longitudinal disease modeling, and AI-driven data quality methods, illustrating how data science is reshaping precision medicine across diverse populations and settings.
Speakers
avatar for Sarah Lotspeich

Sarah Lotspeich

Assistant Professor of Statistics, Wake Forest University
Sarah Lotspeich is an Assistant Professor in Statistical Sciences at Wake Forest University. She co-leads the Spatial and Environmental Statistics in Health (SESH) Lab at Wake Forest and the Missing and INcomplete Data (MIND) Lab at UNC Chapel Hill, and is enthusiastic about mentoring... Read More →
avatar for Marie Loh

Marie Loh

Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
Marie Loh is an Assistant Professor in the Lee Kong Chian School of Medicine at Nanyang Technological University, Senior Research Scientist at the Genome Institute of Singapore and Honorary Senior Lecturer at Imperial College London. Asst Prof Loh is a molecular epidemiologist with... Read More →
avatar for Chih-Ting Yang

Chih-Ting Yang

Department of Biostatistics, Vanderbilt University, Nashville, TN, USA
Chih-Ting Yang is a PhD candidate in Biostatistics at Vanderbilt University. Her research focuses on developing and applying statistical methods to complex biomedical data, including microbiome and single-cell omics data, electronic health records, and biobank-linked clinical dat... Read More →
avatar for Chiani Hsiung

Chiani Hsiung

Genetics Generation Advancement Corp.(GGA Corp.)
Dr. Chia-Ni Hsiung (Christine Hsiung) is a Taiwan-based researcher in genomic epidemiology and precision medicine. She holds an MPH from the National Defense Medical Center and a Ph.D. in Precision Medicine from National Tsing Hua University (2026). She currently serves as Senior... Read More →
Chairs/Hosts
YL
Organizers
YL
S103 Abstracts pdf
Tuesday October 6, 2026 02:00 - 03:00 UTC
Zoom Room #1
  Invited Session, Technical Statistical Session

03:00 UTC

S104 - Breaking barriers
Tuesday October 6, 2026 03:00 - 04:00 UTC
Zoom Room #1
An Invited Session Proposal from Statistics Society of Australia (SSA) Women in Statistics Network Supported by the The International Statistical Institute (ISI) Committee on Women in Statistics

Session Title: Breaking barriers

Session Organiser: Alysha De Livera

Session Chair: Ayse Aysin Bilgin

The progression of the talks:

curiosity → identity → contribution → legacy
aspiration → exploration → contribution → impact

Speakers:
1. Jayamini Liyanage, [email protected], La Trobe University, Australia, (PhD Student)
2. Melissa Middleton, PhD, GStat, [email protected], Murdoch Children’s Research Institute, Australia, (Early Career)
3. Alysha De Livera, PhD, AStat, [email protected], Latrobe University, Australia, (Mid Career)
4. Ayse Aysin Bilgin, PhD, [email protected], Macquarie University, Australia Professor (Late Career)
Speakers
avatar for Alysha De Livera

Alysha De Livera

La Trobe University
Dr Alysha De Livera is Co-Chair of the newly established Women in Statistics and Data Science Special Interest Group of the Statistical Society of Australia, and previously served as Co-Chair of its Biostatistics and Bioinformatics Committee. She is an academic in Statistics in the... Read More →
avatar for Ayse Aysin Bilgin

Ayse Aysin Bilgin

Macquarie University, Australia
Honorary Prof Ayse Aysin Bilgin is a Vice President of International Statistical Institute (2025-2029), co-chair of Statistics Education Section of Statistical Society of Australia and was the President of the International Association for Statistical Education (IASE).
She has held a range of academic leadership roles, contributing to curriculum design, program development, and institutional strategy in teaching and learning at Macquarie University in Australia. Bilgin is recognised for her contributions to the scholarship of teaching and learni... Read More →
avatar for Jayamini Liyanage

Jayamini Liyanage

La Trobe University
Jayamini Liyanage is a final-year Biostatistics PhD student at La Trobe University, Melbourne, where her research focuses on developing multivariate meta-analysis methods for analysing high-dimensional biological data. She has published statistical methods and developed an R package... Read More →
avatar for Melissa Middleton

Melissa Middleton

Murdoch Children's Research Institute
Dr Melissa Middleton is an early-career biostatistician at the Murdoch Children’s Research Institute in Melbourne. Her work methodological work focuses on missing data methods and adaptive platform trial design, alongside her collaborative work in clinical trials and observational... Read More →
Chairs/Hosts
avatar for Ayse Aysin Bilgin

Ayse Aysin Bilgin

Macquarie University, Australia
Honorary Prof Ayse Aysin Bilgin is a Vice President of International Statistical Institute (2025-2029), co-chair of Statistics Education Section of Statistical Society of Australia and was the President of the International Association for Statistical Education (IASE).
She has held a range of academic leadership roles, contributing to curriculum design, program development, and institutional strategy in teaching and learning at Macquarie University in Australia. Bilgin is recognised for her contributions to the scholarship of teaching and learni... Read More →
Organizers
avatar for Alysha De Livera

Alysha De Livera

La Trobe University
Dr Alysha De Livera is Co-Chair of the newly established Women in Statistics and Data Science Special Interest Group of the Statistical Society of Australia, and previously served as Co-Chair of its Biostatistics and Bioinformatics Committee. She is an academic in Statistics in the... Read More →
S104 Abstracts pdf
Tuesday October 6, 2026 03:00 - 04:00 UTC
Zoom Room #1
  Invited Session, Career or Professional Development Session

04:00 UTC

S105 - Towards Inclusive Medical AI: Mitigating Data Bias and Fostering Equity
Tuesday October 6, 2026 04:00 - 05:00 UTC
Zoom Room #1
As artificial intelligence becomes deeply integrated into healthcare, addressing inherent biases and ensuring equitable outcomes is paramount. This session explores multidisciplinary strategies for developing inclusive and fair medical AI systems. The panel brings together four experts to discuss critical challenges and actionable solutions. Dr. Heajin Kim (Chair) will highlight the importance of reflecting sex and gender characteristics in medical AI to foster equity. Researcher Jeongyeon Kim will provide a critical analysis of data bias issues within Korea's AI Hub. Dr. Yuseong Chu will review current research trends and methodologies for achieving algorithmic fairness in healthcare. Finally, Dr. Wonjung Park will introduce innovative approaches utilizing synthetic data generation to address dataset imbalances. Together, this session offers a comprehensive roadmap towards trustworthy and inclusive medical AI.
Speakers
avatar for Jeongyeon Kim

Jeongyeon Kim

Researcher
Jeongyeon Kim is a Researcher at the Center for Gendered Innovations in Science and Technology Research (GISTeR). She earned her bachelor’s degree with a double major in Statistics and Information Technology. Her current work focuses on analyzing bias and representativeness in healthcare... Read More →
avatar for Yusung Chu

Yusung Chu

Yonsei University, Postdoctoral Researcher
Dr. Yusung Chu received his B.S. and Ph.D. degrees in Biomedical Engineering from Yonsei University. He is currently a Postdoctoral Researcher in the Department of Precision Medicine at Yonsei University Wonju College of Medicine. His research focuses on medical artificial intelligence... Read More →
avatar for Wonjung Park

Wonjung Park

KAIST
Dr. Wonjung Park is a Postdoctoral Researcher in the Computer Graphics and Visualization Lab at KAIST. She received her Ph.D. in Computer Science from KAIST in 2026. Her research specializes in NeuroImaging and Generative AI, with a particular focus on the biological trustworthiness... Read More →
Chairs/Hosts
HK
Organizers
HK
S105 Abstracts pdf
Tuesday October 6, 2026 04:00 - 05:00 UTC
Zoom Room #1
  Invited Session, Technical Statistical Session

08:00 UTC

S109 - Advances in Statistical Methods for Complex and High-Dimensional Data
Tuesday October 6, 2026 08:00 - 09:00 UTC
Zoom Room #1
This session brings together recent advances in statistical methodology for analyzing complex, high-dimensional, and heterogeneous data arising in modern biomedical and genetic research. The presentations cover a broad range of topics, including variable screening for mixed-type and high-dimensional data, integration of mechanistic and statistical models for infectious disease prediction, semiparametric approaches for meta-analysis, and set-based association testing for functional genetic responses. Together, these talks highlight emerging statistical frameworks that improve flexibility, scalability, and interpretability in the analysis of complex data structures.
Speakers
avatar for Haeun Moon

Haeun Moon

Seoul National University
Haeun Moon is an assistant professor in the Department of Transdisciplinary Innovations and the Department of Statistics at the Seoul National University, South Korea. Before joining SNU, she was a postdoctoral researcher in the Department of Statistics and Data Science at Carnegie... Read More →
avatar for Saebom Jeon

Saebom Jeon

Sungshin Women’s University
Saebom Jeon is an associate professor in the School of Mathematics, Statistics and Data Science at Sungshin Women’s University and a research member of the Biomedical Mathematics Group at the Institute for Basic Science (IBS), Korea. She received her Ph.D. in Statistics from Korea... Read More →
avatar for Eunjee Lee

Eunjee Lee

Chungnam National University
Eunjee Lee is an Associate Professor in the Department of Information and Statistics at Chungnam National University. Her research focuses on functional data analysis, biomedical imaging, brain network analysis, and Bayesian methodology. She has developed statistical models for complex... Read More →
avatar for Sunyoung Shin

Sunyoung Shin

Pohang University of Science and Technology
Sunyoung Shin is an Associate Professor in Department of Mathematics at Pohang University of Science and Technology. Her research lies at the intersection of statistical learning and reinforcement learning, with a focus on developing scalable methods for high-dimensional data, particularly... Read More →
Chairs/Hosts
SY
Organizers
SY
S109 Abstracts pdf
Tuesday October 6, 2026 08:00 - 09:00 UTC
Zoom Room #1
  Invited Session, Technical Statistical Session

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
avatar for Marilena Müller

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 →
avatar for Judith Vilsmeier

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 →
avatar for Sandra Schmeller

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 →
avatar for Ema Požek

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
avatar for Marilena Müller

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 →
Organizers
avatar for Marilena Müller

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 →
S205 Abstracts pdf
Tuesday October 6, 2026 08:00 - 09:00 UTC
Zoom Room #2
  Invited Session, Technical Statistical Session

08:00 UTC

S400 - Building Future Leaders in Statistics and Data Science Japan's Collaborative Model from School Education to Society
Tuesday October 6, 2026 08:00 - 09:00 UTC
Zoom Room #4
As artificial intelligence and data-driven decision-making become integral to society, developing future
leaders in statistics and data science has become an international priority. Beyond teaching statistical
methods or programming skills, education must cultivate statistical thinking, inquiry, evidence-based
reasoning, and the ability to connect data with real-world decision-making throughout learners'
educational journeys.

Japan has been developing an inquiry-based learning framework that progressively connects statistical
and data science education from primary school to university. This framework encourages learners to
investigate authentic questions using data while strengthening statistical literacy through curriculum
reform, inquiry-based learning, student competitions, and university education and research. It is
supported through collaboration among educational institutions, professional societies, public
organizations, and non-profit organizations.

This session introduces four complementary perspectives on this framework. First, it presents how
long-term educational support by a non-profit organization has contributed to nurturing future
statistical talent. Second, it explores how national and international statistical competitions, including the
Statistical Graph Contest and the ISLP International Poster Competition, inspire students and foster
statistical thinking. Third, it shares innovative practices in inquiry-based data science education in
Japanese secondary schools. Finally, it discusses how statistics and data science education can prepare
hybrid talent capable of integrating disciplinary expertise with AI and emerging technologies across
secondary education, higher education, and lifelong learning.

Through these perspectives, the session aims to share Japan's inquiry-based educational framework
with the international community and to promote dialogue on how statistics and data science education
can cultivate future leaders capable of addressing increasingly complex societal challenges.
Speakers
KT

Kiwa Tomaru

Mathematics Teacher, Nagoya University Junior and Senior High School
Kiwa Tomaru is a mathematics teacher at Nagoya University Junior and Senior High School,  where she has designed and taught the compulsory Data Science course since its introduction in 2022, emphasizing reading data correctly over formula-based instruction — work recognized with... Read More →
YK

Yoko Konishi

Professor, University of Tsukuba
Yoko Konishi is a professor at the University of Tsukuba, specializing in applied econometrics and statistics. She received her Ph.D. in Economics from Nagoya University. Her research uses official statistics, private-sector big data, and large-scale surveys to study consumer behavior... Read More →
Tuesday October 6, 2026 08:00 - 09:00 UTC
Zoom Room #4
  Invited Session

09:00 UTC

S110 - Advances in Multi-Source Statistics
Tuesday October 6, 2026 09:00 - 10:00 UTC
Zoom Room #1
This session is organized by the European Survey Research Association – Special Interest Group on multi-source statistics.
As survey research increasingly operates in a complex data ecosystem, integrating probability-based surveys with administrative records, digital traces, non-probability samples, and other non-traditional data sources has become essential for improving inference and studying phenomena that cannot be adequately measured by a single data source. In particular, new data sources can provide better data about hard-to-reach populations and minorities, helping to make these groups more visible in research and evidence-based decision-making. This session will discuss cutting-edge methodologies and innovative case studies that integrate diverse data sources in survey research, with a particular focus on their potential to improve the measurement of underrepresented populations.
Speakers
avatar for Monica Pratesi

Monica Pratesi

University of Pisa
Monica Pratesi is Full Professor of Statistics at the University of Pisa and a member of the Scientific Council of the Italian National Research Council (CNR). She served as President of the International Association of Survey Statisticians (IASS) from 2021 to 2023 and as Director... Read More →
avatar for Char Hilgers

Char Hilgers

German Institute for Economic Research (DIW Berlin), Socio-Economic Panel
Char Hilgers is a PhD student in Sociology at the Humboldt University's Berlin Graduate School of Social Science, funded by the Socio-Economic Panel at DIW Berlin. Their research is on statistical techniques for nonresponse in survey settings: when missingness means something. From... Read More →
avatar for Jisu Kim

Jisu Kim

Utrecht University
Dr. Jisu Kim is currently an assistant professor at Utrecht University, the Netherlands in the department of Interdisciplinary Social Science. She holds a PhD in Data Science from Scuola Normale Superiore in Italy. Prior to her current position, she was a research scientist at Max... Read More →
avatar for Manuela Schmidt

Manuela Schmidt

RPTU Kaiserslautern-Landau
Manuela Schmidt is a researcher at RPTU Kaiserslautern-Landau, where she works on the German Longitudinal Environmental Study (GLEN). Her research focuses on survey methodology, geodata integration, and data quality in quantitative social research.
Chairs/Hosts
CS
Organizers
CS
S110 Abstracts pdf
Tuesday October 6, 2026 09:00 - 10:00 UTC
Zoom Room #1
  Invited Session, Technical Statistical Session

09:00 UTC

S305 - The Role of Data Modelling for Better Outcomes in Women’s Health
Tuesday October 6, 2026 09:00 - 10:00 UTC
Zoom Room #3
Dr Rachael Duncan will introduce the session that brings together leading speakers to explore how advanced data modelling can improve outcomes in women’s health, particularly through equity-focused and locally led approaches. The session also highlights the importance of women as data scientists and modellers to ensure better healthcare outcomes. Dr Halima Twabi highlights capacity building in Sub-Saharan Africa, emphasising strengthening local expertise, supporting women data scientists, and applying advanced statistical and causal inference methods to complex health challenges. Dr Annabel Sowemimo contributes a critical perspective on structural inequalities, addressing racism and the need to decolonise healthcare systems. Dr Lucy Teece focuses on with insights from industry on the role of biometrics in cancer drug development. Together, the speakers demonstrate how inclusive, collaborative modelling approaches can generate more relevant, impactful, and equitable evidence for women’s health research and policy.
Speakers
avatar for Rachael Duncan

Rachael Duncan

BioSS
Rachael Duncan is a Statistician in Animal Health and Welfare at BioSS. Since joining BioSS in 2023, she has applied statistical methods to a wide range of challenges in animal health and welfare. Prior to this, she completed her PhD at Lancaster University, where she explored how... Read More →
avatar for Halima Twabi

Halima Twabi

University of Malawi
Halima Twabi is an Associate Professor of Statistics at the Department of Mathematical Sciences, University of Malawi. Her research interests are in causal inference for observational data, multivariate statistics, longitudinal and survival analysis, and statistical modelling and... Read More →
avatar for Annabel Sowemimo

Annabel Sowemimo

King’s College London
Dr Annabel Sowemimo is a doctor, academic, activist and writer, and an NHS Consultant in Sexual & Reproductive Health in South London. Her first book, Divided: Racism, Medicine and Why We Need to Decolonise Healthcare (2023), won the Bread and Roses Award for Radical Publishing and... Read More →
avatar for Lucy Teece

Lucy Teece

AstraZeneca
Dr Teece is an Associate Director of Statistical Science at AstraZeneca. Previously, she was a Lecturer in Medical Statistics in the Department of Health Sciences at the University of Leicester. She was awarded her PhD on “Investigating the presence and impact of competing events... Read More →
Chairs/Hosts
avatar for Rachael Duncan

Rachael Duncan

BioSS
Rachael Duncan is a Statistician in Animal Health and Welfare at BioSS. Since joining BioSS in 2023, she has applied statistical methods to a wide range of challenges in animal health and welfare. Prior to this, she completed her PhD at Lancaster University, where she explored how... Read More →
Organizers
EJ
S304 Abstracts pdf
Tuesday October 6, 2026 09:00 - 10:00 UTC
Zoom Room #3
  Invited Session, Technical Statistical Session

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
avatar for Marianne Huebner

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 →
avatar for Saskia Le Cessie

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 →
avatar for Els Goetghebeur

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 →
avatar for Lara Lusa

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
avatar for Marianne Huebner

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 →
Organizers
avatar for Marianne Huebner

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 →
S111 Abstracts pdf
Tuesday October 6, 2026 10:00 - 11:00 UTC
Zoom Room #1
  Invited Session, Technical Statistical Session

10:00 UTC

S306 - Modern Statistical Methods and Applications in Health Research
Tuesday October 6, 2026 10:00 - 11:00 UTC
Zoom Room #3
This session highlights the breadth of biostatistics through four distinct but complementary talks by statistical researchers. It explores how modern statistical methodologies are advancing health research by addressing challenges in evidence generation, clinical decision-making, and causal inference. The presentations cover Bayesian learning frameworks for individualised treatment recommendations, large language model-assisted tools that improve the efficiency and reproducibility of systematic reviews and meta-analyses, innovative clinical trial designs and the practical challenges that influence their efficiency, and Mendelian randomisation approaches for investigating causal relationships and therapeutic targets in cardiovascular disease. Together, these talks aim to strengthen the reliability, transparency and translation of evidence, thereby supporting more informed clinical and public health decision-making in an increasingly connected global health research landscape.
Speakers
avatar for Pamela Massiel Chiroque Solano

Pamela Massiel Chiroque Solano

University of Regensburg
Pamela Solano is a statistician passionate about transforming complex data into trustworthy clinical decisions. As a researcher at the Faculty of Informatics and Data Science, University of Regensburg, Germany, she develops interpretable AI and Bayesian learning methods that empower... Read More →
avatar for Danyang Dai

Danyang Dai

The University of Sydney
Danyang Dai (Daidai) is a final year PhD student (thesis submitted) at the Queensland Digital Health Centre. She is an applied statistician and infectious disease epidemiology researcher with expertise in large scale health data analysis, disease surveillance, and advanced statistical... Read More →
avatar for Aritra Mukherjee

Aritra Mukherjee

Newcastle University
Aritra Mukherjee is a Research Associate in the Biostatistics Research Group at Newcastle University. Her research focuses on developing innovative statistical methods for clinical trials, with expertise in adaptive trial designs such as multi-arm multi-stage (MAMS) trials, sample... Read More →
avatar for Daianna Gonzalez Padilla

Daianna Gonzalez Padilla

University of Cambridge
Researcher in Genetic Epidemiology at the MRC Biostatistics Unit, University of Cambridge, specializing in Mendelian randomization, a causal inference framework that uses genetic variants to assess the effects of putative risk factors on disease from observational data. My research... Read More →
Chairs/Hosts
RD
Organizers
RD
S305 Abstracts pdf
Tuesday October 6, 2026 10:00 - 11:00 UTC
Zoom Room #3
  Invited Session, Technical Statistical Session

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
avatar for Louisa Muparuri

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 →
avatar for Phyliss Shamiso Mavedzenge

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 →
avatar for Salome Maheya

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 →
avatar for Lerdinia Mapepa

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
avatar for Chipo Zidana

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
avatar for Chipo Zidana

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 →
S210 Abstracts pdf
Tuesday October 6, 2026 12:00 - 13:00 UTC
Zoom Room #2
  Invited Session, Technical Statistical Session
  • Session ID 210

12:00 UTC

S403 - Change point detection and its applications
Tuesday October 6, 2026 12:00 - 13:00 UTC
Zoom Room #4
Change point detection has long been an active and important area of statistical research because structural changes frequently arise in data collected over time or across different conditions. Detecting these changes helps researchers better understand complex processes and make more informed decisions in fields such as public health, finance, genomics, environmental science, manufacturing, and engineering, where the ability to detect shifts in trends, variability, or dependence structures can provide valuable insights into complex systems. As the volume and complexity of modern data continue to grow, the development of robust and efficient change point techniques remains a significant research challenge and opportunity. This invited session brings together researchers from three countries to present new methods and real-world applications of change point analysis. The session will highlight recent advances in the field, encourage international collaboration, and showcase the broad impact of change point research across diverse disciplines.
Speakers
avatar for Rebecca Killick

Rebecca Killick

Clemenson University
Rebecca Killick is Associate Director of Research in Mathematical and Statistical Sciences at Clemson University. Dr. Killick received a PhD in Statistics from Lancaster University, where until 2026, held a Professor and Director of Research positions. In 2019 Dr. Killick was the... Read More →
avatar for Kun Liu

Kun Liu

JPMorgan Chase & Company
Kun Liu is a Vice President and Quant Modeling Lead at JPMorgan Chase with expertise in AI, machine learning, credit risk, fraud detection, and causal inference. He holds a Ph.D. in Statistics from Georgia Tech and has over eight years of experience developing and deploying advanced... Read More →
avatar for Meenu Rani

Meenu Rani

Indian Institute of Technology Ropar
Meenu Rani is a Ph.D. student in the Department of Mathematics at the Indian Institute of Technology Ropar. Her doctoral research focuses on change point detection, including both offline and online settings. Her work has primarily involved applications to financial data.
avatar for Ayten Yiğiter

Ayten Yiğiter

Hacettepe University
Dr. Yiğiter received the B.S., M.S., and Ph.D. degrees in statistics from Hacettepe University, Ankara, Türkiye, in 1995, 2000 and 2006, respectively. In 2007, she was a Visiting Scholar with the University of Missouri-Kansas City, Kansas City, MO, USA. She is currently working... Read More →
Chairs/Hosts
JC
Organizers
JC
S403 Abstracts pdf
Tuesday October 6, 2026 12:00 - 13:00 UTC
Zoom Room #4
  Invited Session, Technical Statistical Session

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
avatar for Sumaiya Sande

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 →
avatar for Swastika Mohapatro

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 →
avatar for Yogita Gharde

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 →
avatar for Sharvari Shukla

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
SJ
Organizers
SJ
S211 Abstracts pdf
Tuesday October 6, 2026 13:00 - 14:00 UTC
Zoom Room #2
  Invited Session, Technical Statistical Session

13:00 UTC

S308 - Pedagogy with Purpose: Tailoring your Statistics Classroom for Specific Audiences
Tuesday October 6, 2026 13:00 - 14:00 UTC
Zoom Room #3
Given the wide variety of opportunities available for learners to gain expertise in statistics and data science, students enter the classroom with different needs and goals. Instructors balance standardized learning outcomes with individualized support, and a happy medium is not always easy to achieve. In this session, sponsored by the Caucus for Women in Statistics and Data Science, we feature a diverse group of educators whose trainees range from high school students just learning first principles to clinicians looking to build biostatistical expertise. The speakers will present their experiences customizing their courses to meet students where they are. First, Dr. Nicole Dalzell will share tips for structuring a first-year statistics course that builds a strong foundation for success in college. Next, Ms. Ashley Mullan will discuss lessons learned from designing a weeklong introductory summer course for high school students. Then, Dr. Taylor Krajewski will describe approaches for adapting communication and content while maintaining rigor, engagement, and accessibility. Finally, Dr. Jamie Joseph will outline considerations for adapting a biostatistics seminar series to provide support for both medical licensure candidates and emerging investigators. The four speakers span a wide array of educational settings, making the session interesting to a general audience. However, all four showcase how thoughtful education can support all members of the global statistics community.
Speakers
avatar for Ashley Mullan

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 →
avatar for Jamie Joseph

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 →
avatar for Nicole Dalzell

Nicole Dalzell

Wake Forest University
Dr. Nicole Dalzell is an Associate Teaching Professor in the Department of Statistical Sciences at Wake Forest University. She loves developing new courses and constantly thinking about how to make her teaching materials and style work better for students. She also enjoys mentoring... Read More →
avatar for Taylor Krajewski

Taylor Krajewski

Duke University
Dr. Taylor Krajewski is an Assistant Professor in the Department of Biostatistics & Bioinformatics and the Department of Population Health Sciences at the Duke University School of Medicine and a member of the Duke Clinical Research Institute. Her research focuses on causal inference... Read More →
Chairs/Hosts
JR
Organizers
avatar for Ashley Mullan

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 →
S307 Abstracts pdf
Tuesday October 6, 2026 13:00 - 14:00 UTC
Zoom Room #3
  Invited Session, Career or Professional Development Session

13:00 UTC

S404 - Coordinating Evidence for Better Research Design: Priors, Assumptions, and Scientific Judgment
Tuesday October 6, 2026 13:00 - 14:00 UTC
Zoom Room #4
This session examines how scientific judgment can be made explicit in research design and decision making with mixed methods evidence, causal knowledge, expert elicitation, and Bayesian priors. Noor Qaragholi opens by showing how qualitative and quantitative evidence can inform strong, untestable causal assumptions in study design, illustrated through CACE estimation in a randomized behavioral intervention with substantial noncompliance. Utkarshani Jaimini then turns to Causal Neuro-Symbolic AI, a framework for building systems that are explainable, interpretable, and causally aware rather than limited to correlational pattern matching. Her work spans knowledge representation, causal inference, and applied machine learning. Anna Heath discusses expert elicitation for Bayesian clinical trial design, focusing on remote, real time exercises that help experts translate experience into probabilistic statements for prior distributions. Lu (Maggie) Qian closes by examining how Bayesian trial design can make scientific judgment explicit without allowing prior choice to become opaque, drawing on FDA guidance and reverse-Bayes methods as an audit tool. Together, the talks show how making assumptions and priors explicit can strengthen research design and support credible, decision relevant conclusions.
Speakers
avatar for Noor Qaragholi

Noor Qaragholi

The Policy & Research Group
Noor Qaragholi is a public health researcher with 15 years of experience conducting qualitative, quantitative, and mixed methods research to improve health programs, services, and systems. As a Senior Research Analyst at The Policy & Research Group, Dr. Qaragholi leads large-scale... Read More →
avatar for Utkarshani Jaimini

Utkarshani Jaimini

University of Michigan Dearborn
Utkarshani Jaimini is an Assistant Professor in the Department of Computer and Information Science at the University of Michigan-Dearborn, where she joined as a faculty in Fall 2025. She holds her doctoral degree from the University of South Carolina. Her research lies at the intersection... Read More →
avatar for Lu Qian

Lu Qian

Zetyra, LLC
Lu (Maggie) Qian is an independent biostatistician and founder of Evidence in the Wild and Zetyra. Her work focuses on Bayesian and adaptive clinical trial design, regulatory alignment, prior specification, prior-data conflict, and operating characteristics of composed adaptive pipelines... Read More →
avatar for Anna Heath

Anna Heath

The Hospital for Sick Children
Dr. Heath is a Scientist at The Hospital for Sick Children (SickKids), Toronto, an Associate Professor at University of Toronto and Honorary Research Fellow at University College London, UK. She is the Canada Research Chair in Statistical Trial Design. She arrived at SickKids in 2018... Read More →
Chairs/Hosts
EE
Organizers
EE
S404 Abstracts pdf
Tuesday October 6, 2026 13:00 - 14:00 UTC
Zoom Room #4
  Invited Session, Technical Statistical Session
  • Session ID 404

14:00 UTC

S309 - Modern Frontiers in Complex Data Analysis: Scalable Bayesian Methods and Dynamic Online Estimation
Tuesday October 6, 2026 14:00 - 15:00 UTC
Zoom Room #3
This session brings together pioneering research that tackles the dual challenges of complexity and scalability in modern statistics and data science. The presentations feature cutting-edge developments in Bayesian hypothesis testing, discrete choice modeling, and streaming spatial data analysis over complex domains. The session begins with two complementary talks introducing highly efficient, closed-form Bayesian alternatives to classical multivariate and random effects testing frameworks. It then transitions to an innovative Bayesian best-worst choice model that utilizes Integrated Nested Laplace Approximation (INLA) for complex preference data analysis. Concluding the discussion is a state-of-the-art online nonparametric estimation of spatially varying coefficient models for streaming spatial data using dynamic bivariate penalized splines over triangulations. Together, these talks highlight the vital role of advanced computational methodologies, spanning objective Bayes, deterministic approximations, and sequential updating algorithms, in achieving rigorous inference and extracting robust insights from complex data structures across diverse scientific domains.
Speakers
avatar for Mai Dao

Mai Dao

Assistant Professor, Wichita State University
Dr. Mai Dao is an Assistant Professor of Statistics in the Department of Mathematics, Statistics, and Physics at Wichita State University. She obtained her Ph.D. from Texas Tech University under the supervision of Professors Min Wang (The University of Texas at San Antonio) and Souparno... Read More →
avatar for Zhuanzhuan Ma

Zhuanzhuan Ma

The University of Texas Rio Grande Valley
Dr. Zhuanzhuan Ma is an Assistant Professor of Statistics in the School of Mathematical and Statistical Sciences at the University of Texas Rio Grande Valley. She earned her Ph.D. in Statistics from Texas Tech University in 2022. Her research interests include Bayesian statistics... Read More →
avatar for Nadeesha Jayaweera

Nadeesha Jayaweera

Assistant Professor, University of Akron
Dr. Nadeesha Jayaweera is an Assistant Professor in the Department of Statistics at the University of Akron. She received her Ph.D. in Statistics from Texas Tech University in 2022 and previously held a postdoctoral research position at Worcester Polytechnic Institute. Her research... Read More →
avatar for Jingru Mu

Jingru Mu

Kansas State University
Dr. Jingru Mu is an Associate Professor in the Department of Statistics at Kansas State University. Her research focuses on developing flexible and computationally efficient statistical methods for complex, large-scale, and spatio-temporal data. Her interests include nonparametric... Read More →
Chairs/Hosts
avatar for Mai Dao

Mai Dao

Assistant Professor, Wichita State University
Dr. Mai Dao is an Assistant Professor of Statistics in the Department of Mathematics, Statistics, and Physics at Wichita State University. She obtained her Ph.D. from Texas Tech University under the supervision of Professors Min Wang (The University of Texas at San Antonio) and Souparno... Read More →
Organizers
avatar for Mai Dao

Mai Dao

Assistant Professor, Wichita State University
Dr. Mai Dao is an Assistant Professor of Statistics in the Department of Mathematics, Statistics, and Physics at Wichita State University. She obtained her Ph.D. from Texas Tech University under the supervision of Professors Min Wang (The University of Texas at San Antonio) and Souparno... Read More →
S308 Abstracts pdf
Tuesday October 6, 2026 14:00 - 15:00 UTC
Zoom Room #3
  Invited Session, Technical Statistical Session

15:00 UTC

S118 - Data, Diversity, and Dialogue: Women Shaping the Future of Statistics and Data Science
Tuesday October 6, 2026 15:00 - 16:00 UTC
Zoom Room #1
At a time when data drives decisions across science, industry, and society, the voices shaping this landscape matter more than ever. This invited session brings together distinguished women researchers whose work reflects the power of diversity, collaboration, and intellectual curiosity in statistics and data science.

Through their journeys, the speakers will illustrate how meaningful connections—across disciplines, institutions, and cultures—emerge not only from shared research goals but also from openness, mentorship, and resilience. Their experiences reveal how collaborative environments can spark innovation, amplify impact, and create pathways for future generations of women in the field.

More than a showcase of research, this session is an invitation to reflect on how we build scientific communities that are inclusive, dynamic, and forward-looking. By fostering dialogue and embracing diverse perspectives, we strengthen our collective ability to tackle complex challenges and shape a more connected and equitable future for data science.

This session celebrates the role of women as catalysts for change, bridging ideas and people to advance knowledge and inspire the next generation.

This session is sponsored by the Portuguese Statistical Society an by the Portuguese Country Representative of CWS.
Speakers
avatar for Lisete Sousa

Lisete Sousa

Faculdade de Ciências da Universidade de Lisboa and CEAUL
Lisete Sousa is an Associate Professor in the Department of Mathematical Sciences at the Faculty of Sciences of the University of Lisbon and a researcher at the Centre of Statistics and its Applications (CEAUL). She holds a degree in Statistics and Operations Research, a master’s... Read More →
avatar for Conceição Amado

Conceição Amado

Instituto Superior Técnico, Universidade de Lisboa
Conceição Amado is an Associate Professor in the Department of Mathematics at Instituto Superior Técnico, University of Lisbon. She is a researcher at the Center for Computational and Stochastic Mathematics (CEMAT) and serves as co-coordinator of the M.Sc. in Data Science and Engineering... Read More →
avatar for Marília Antunes

Marília Antunes

Faculdade de Ciências da Universidade de Lisboa and CEAUL
Marília Antunes is an Associate Professor at the Department of Mathematical Sciences at the Faculty of Sciences, University of Lisbon. Since 2023, she is also the Scientific Coordinator of the Centre of Statistics and its Applications (CEAUL). She earned her PhD in Statistics and... Read More →
avatar for Susana Vinga

Susana Vinga

INESC-ID, Instituto Superior Técnico and IDMEC
Susana Vinga is Associate Professor at the Departments of Computer Science and Engineering and Bioengineering at Instituto Superior Técnico, Universidade de Lisboa, and researcher at INESC-ID (Life and Health Technologies). She holds a degree in Mechanical Engineering (1999), a post-graduate... Read More →
Chairs/Hosts
EC
Organizers
EC
S118 Abstracts pdf
Tuesday October 6, 2026 15:00 - 16:00 UTC
Zoom Room #1
  Invited Session, Technical Statistical Session

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
avatar for Lucy D’Agostino McGowan

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 →
avatar for Candice Johnson

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 →
avatar for Maria DeYoreo

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 →
avatar for Lu Wang

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
avatar for Ashley Mullan

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
avatar for Jamie Joseph

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

15:00 UTC

S310 - Read to Lead and Succeed in Statistics and Data Science
Tuesday October 6, 2026 15:00 - 16:00 UTC
Zoom Room #3
In this session, you will learn why it is important for statisticians and data scientists to read books on leadership. You will appreciate how leadership books can inspire statisticians to be better leaders and collaborators. You will be introduced to the perspectives of statisticians about leadership. And you will be challenged to join or start a leadership book club to accelerate your career development.
Speakers
avatar for Ksenija Dumicic

Ksenija Dumicic

University of Zagreb, Faculty of Economics and Business & DOBA University of AS
Ksenija Dumičić, Ph.D., is a tenured full professor in statistics from the University of Zagreb Faculty of Economics & Business and is currently a visiting professor at DOBA University of Applied Sciences in Slovenia. She founded and led Croatia’s first postgraduate study programme... Read More →
avatar for Amanda Golbeck

Amanda Golbeck

College of PUblic Health, University of Arkansas for Medical Sciences
Amanda L. Golbeck is a statistician, academic leader, historian, biographer, and communicator of science. She is known for her authored books, "Equivalence: Elizabeth L. Scott at Berkeley" (Chapman & Hall, 2017) and "Florence Nightingale David: A Passionate Probabilist, Statistician... Read More →
avatar for James Cochran

James Cochran

Professor of Applied Statistics and the Mike and Kathy Mouron Chair, The University of Alabama
Dr. Cochran is Professor of Applied Statistics and the Mike and Kathy Mouron Research Chair with The University of Alabama. He was one of the founders of Statistics without Borders.
avatar for Jessica Utts

Jessica Utts

University of California, Irvine
Jessica Utts is Professor Emerita of Statistics at the University of California, Irvine, where she served as department chair for 5 years. She has held numerous leadership roles in statistics organizations including as President of ASA, the Caucus for Women in Statistics, and WNAR... Read More →
Chairs/Hosts
BN
Organizers
avatar for Amanda Golbeck

Amanda Golbeck

College of PUblic Health, University of Arkansas for Medical Sciences
Amanda L. Golbeck is a statistician, academic leader, historian, biographer, and communicator of science. She is known for her authored books, "Equivalence: Elizabeth L. Scott at Berkeley" (Chapman & Hall, 2017) and "Florence Nightingale David: A Passionate Probabilist, Statistician... Read More →
S309 Abstracts pdf
Tuesday October 6, 2026 15:00 - 16:00 UTC
Zoom Room #3
  Invited Session, Career or Professional Development Session

17:00 UTC

S302 - Emerging Computational Methods in Statistical Inference: Multivariate Analysis, Bayesian Shrinkage, and Advanced Regression Modeling
Tuesday October 6, 2026 17:00 - 18:00 UTC
Zoom Room #1
This session presents novel computational and methodological advancements in modern statistical inference, focusing on complex data structures such as multivariate, longitudinal, and high-dimensional survival data. The presentations span both frequentist and Bayesian paradigms, featuring innovative strategies to overcome long-standing computational bottlenecks commonly encountered in such investigations. The session opens with a new framework for multivariate order-restricted statistical inference under a general grass ordering, applying a pairwise optimization criterion and introducing an efficient vector projection-based algorithm to estimate the order-restricted mean matrix. It then transitions into the Bayesian realm with two complementary presentations on longitudinal quantile regression. These back-to-back talks first present a robust partially collapsed Gibbs sampler to conquer convergence failures in high dimensions and then showcase a Bayesian adaptive LASSO framework that utilizes clustering-based shrinkage for simultaneous optimal quantile estimation and sparse variable selection. The session concludes by extending advanced continuous shrinkage priors to survival analysis, presenting a hybrid minorize-maximize algorithm for high-dimensional proportional hazards models using the horseshoe+ prior. Together, these talks highlight recent developments of highly efficient algorithms to extract reliable inferences from high-dimensional and complicated datasets.
Speakers
avatar for Mai Dao

Mai Dao

Assistant Professor, Wichita State University
Dr. Mai Dao is an Assistant Professor of Statistics in the Department of Mathematics, Statistics, and Physics at Wichita State University. She obtained her Ph.D. from Texas Tech University under the supervision of Professors Min Wang (The University of Texas at San Antonio) and Souparno... Read More →
avatar for Yujie Jia

Yujie Jia

Wichita State University
Yujie Jia is affiliated with Wichita State University, where she is currently a Ph.D. student in the Mathematics, Statistics, and Physics Department. Her research interests include multivariate order-restricted statistical inference, hypothesis testing, maximum likelihood estimation... Read More →
avatar for Sining Zhang

Sining Zhang

Wichita State University
Sining Zhang is a Ph.D. candidate in Applied Statistics at the Department of Mathematics, Statistics, and Physics at Wichita State University under the supervision of Dr. Mai Dao. Her research focuses on Bayesian quantile regression for longitudinal data, with an emphasis on partially... Read More →
avatar for Sarah Ghazawneh

Sarah Ghazawneh

Wichita State University
Sarah Ghazawneh is a Ph.D. candidate in Applied Mathematics at the Department of Mathematics, Statistics, and Physics at Wichita State University under the supervision of Dr. Mai Dao. Her research focuses on Bayesian quantile regression for longitudinal data, with an emphasis on efficient... Read More →
Chairs/Hosts
avatar for Mai Dao

Mai Dao

Assistant Professor, Wichita State University
Dr. Mai Dao is an Assistant Professor of Statistics in the Department of Mathematics, Statistics, and Physics at Wichita State University. She obtained her Ph.D. from Texas Tech University under the supervision of Professors Min Wang (The University of Texas at San Antonio) and Souparno... Read More →
Organizers
avatar for Mai Dao

Mai Dao

Assistant Professor, Wichita State University
Dr. Mai Dao is an Assistant Professor of Statistics in the Department of Mathematics, Statistics, and Physics at Wichita State University. She obtained her Ph.D. from Texas Tech University under the supervision of Professors Min Wang (The University of Texas at San Antonio) and Souparno... Read More →
S119 Abstracts pdf
Tuesday October 6, 2026 17:00 - 18:00 UTC
Zoom Room #1
  Invited Session, Technical Statistical Session

17:00 UTC

S311 - Data Analysis in Engineering and Ecology: Reliability, Branching Processes and Random Fuzzy Sets
Tuesday October 6, 2026 17:00 - 18:00 UTC
Zoom Room #3
This session brings together the last advances on Mathematical Statistics, and Data Analysis, considering the stochastic process framework, as well as more general and flexible probability modelling contexts, involving random elements, to represent uncertainly for data processing, in connection with Statistical Inference and Operations Research. Several practical problems can be analyzed, adopting the presented approaches, in Reliability, Engeneering, Social Sciences, Ecology, and Medicine, just to mention a few.

Three invited speakers make up the invited session:

Lucía Bautista Bárcena, University of Extremadura (Spain).
Carmen Minuesa , University of Extremadura (Spain).
Beatriz Sinova Fernández, University of Oviedo (Spain).
Speakers
avatar for Lucía Bautista

Lucía Bautista

Universidad de Extremadura
Lucía Bautista Bárcena is an Assistant Professor of Statistics and Operations Research at the University of Extremadura (Spain). She holds a BSc in Mathematics from the same institution (2017), where she also completed her MSc in Science Research (2019) and her PhD in Mathematics... Read More →
avatar for Carmen Minuesa Abril

Carmen Minuesa Abril

University of Extremadura
Carmen Minuesa is an Associate Professor in the Department of Mathematics and a member of the Institute of Advanced Scientific Computing at the University of Extremadura (UEx). Her research focuses on stochastic processes. She began her career with a PhD on branching processes and... Read More →
avatar for Beatriz Sinova

Beatriz Sinova

University of Oviedo
Beatriz Sinova Fernández is an Associate Professor in the Department of Statistics and Operational Research and Mathematics Didactics at the University of Oviedo. She holds a Bachelor's degree in Mathematics from the University of Oviedo, a Master's degree in Mathematical Modelling... Read More →
Chairs/Hosts
MD
Organizers
MD
S310 Abstracts pdf
Tuesday October 6, 2026 17:00 - 18:00 UTC
Zoom Room #3
  Invited Session, Technical Statistical Session

18:00 UTC

S120 - Statistical Modeling for Applied Research in Costa Rica
Tuesday October 6, 2026 18:00 - 19:00 UTC
Zoom Room #1
This session brings together four applied studies demonstrating how modern statistical methods can address diverse scientific questions using complex data from Costa Rica. The presentations cover Bayesian hierarchical modeling, penalized regression, machine learning, and generalized additive models, with applications to infectious disease surveillance, biotechnology awareness, and animal production. Despite spanning different disciplines, the talks share a common emphasis on developing interpretable and robust statistical approaches to better understand complex systems through real-world applications in the Costa Rican context.
Speakers
avatar for Marianne Peña Wüst

Marianne Peña Wüst

University of Costa Rica
Marianne is a senior Statistics student from the University of Costa Rica with a background in competitive mathematics. Currently, she has been a research assistant at the Centro de Investigación en Matemática Pura y Aplicada (CIMPA), where she collaborates with projects related... Read More →
avatar for Shirley Rojas-Salazar

Shirley Rojas-Salazar

University of Costa Rica
Shirley Rojas is a professor at the School of Statistics, University of Costa Rica. She completed her undergraduate and graduate studies in Statistics. She enjoys applying statistical methods to better understand complex biological processes and address questions in agricultural and... Read More →
avatar for Jimena Murillo-Montero

Jimena Murillo-Montero

Boston Scientific
I grew up in Costa Rica, in a family with strong academic roots. From an early age, I was drawn specially to mathematics and biology. In 2017, I began studying Microbiology and Clinical Chemistry at the University of Costa Rica. In 2018 I added Statistics as a second major, but during... Read More →
avatar for Laura Obando Esquivel

Laura Obando Esquivel

Universidad de Costa Rica
Laura Obando Esquivel is a student in the Bachelor's Degree in Statistics at the University of Costa Rica and a researcher at the School of Biology, working with the Plant Biotechnology Laboratory and the Center for Research in Pure and Applied Mathematics at the same institution... Read More →
Chairs/Hosts
SR
Organizers
SR
S120 Abstracts pdf
Tuesday October 6, 2026 18:00 - 19:00 UTC
Zoom Room #1
  Invited Session, Technical Statistical Session

18:00 UTC

S505 - Code is for Everyone: Showcasing Tools to Support Learners at all Levels
Tuesday October 6, 2026 18:00 - 19:00 UTC
Zoom Room #5
Code is for Everyone: Showcasing Tools to Support Learners at all Levels
Speakers
avatar for Kelly Bodwin

Kelly Bodwin

California Polytechnic State University
Dr. Kelly Bodwin is an Associate Professor of Statistics and Data Science at California Polytechnic State University, San Luis Obispo. Her research interests include cross-disciplinary work in Digital Humanities, including historical social networks and authorship identification... Read More →
avatar for Mine Cetinkaya-Rundel

Mine Cetinkaya-Rundel

Duke University
Dr. Mine Çetinkaya-Rundel is Professor of the Practice and the Director of Undergraduate Studies at the Department of Statistical Science and the Director of First-Year Experience at Duke University. She is also a Developer Educator at Posit, PBC, an open-source data science software... Read More →
avatar for Cara Thompson

Cara Thompson

Data Visualisation Consultant, Building Stories with Data LTD
Dr. Cara Thompson is a data visualisation consultant with an academic background, specialising in helping research teams and data-driven organisations turn their data insights into to clear and compelling visualisations.

After her PhD in Psychology and a spell teaching research methods at Edinburgh Uni, she embarked on a career in psychometrics at the Royal college of Surgeons of Edinburgh. After ten years of helping surgeons and other medical professionals understand complex patterns in exam data... Read More →
Chairs/Hosts
avatar for Jamie Joseph

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 →
Organizers
avatar for Ashley Mullan

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 →
S506 Abstracts pdf
Tuesday October 6, 2026 18:00 - 19:00 UTC
Zoom Room #5
  Invited Session, Technical Statistical Session

20:00 UTC

S121 - Advances in Statistical Methodology for Complex and High-Dimensional Data
Tuesday October 6, 2026 20:00 - 21:00 UTC
Zoom Room #1
This invited session showcases recent advances in statistical methodology for analyzing increasingly complex, high-dimensional, and structured data arising in biomedical research, imaging, surveys, and longitudinal studies. The presentations introduce innovative approaches to sufficient dimension reduction, scalable spatial topic modeling for multiplexed imaging, Bayesian small area estimation under informative sampling, and Bayesian semiparametric quantile mixed-effects models for longitudinal data with missing responses. Together, these talks highlight modern statistical techniques that combine methodological rigor with computational efficiency to address emerging challenges in data science, while demonstrating broad applicability across diverse scientific disciplines.
Speakers
avatar for Mai Dao

Mai Dao

Assistant Professor, Wichita State University
Dr. Mai Dao is an Assistant Professor of Statistics in the Department of Mathematics, Statistics, and Physics at Wichita State University. She obtained her Ph.D. from Texas Tech University under the supervision of Professors Min Wang (The University of Texas at San Antonio) and Souparno... Read More →
avatar for Chenlu Ke

Chenlu Ke

Virginia Commonwealth University
Dr. Chenlu Ke is an Associate Professor in the Department of Statistical Sciences and Operations Research at Virginia Commonwealth University. Her research focuses on methodological and computational developments for high- and ultrahigh-dimensional complex data, with applications... Read More →
avatar for Yanghyeon Cho

Yanghyeon Cho

University of Idaho
Yanghyeon Cho is an Assistant Professor in the Department of Mathematics and Statistical Science at the University of Idaho. Her research interests include survey sampling and statistical genetics, with a focus on small area estimation, Mendelian randomization, and multi-omics data... Read More →
avatar for Xiyu Peng

Xiyu Peng

Texas A&M University
Dr. Xiyu Peng is an assistant professor in the Department of Statistics at Texas A&M University. Her research focuses on developing statistical and computational methods for resolving temporal and spatial dynamics in single cell omics data with applications in cancer. She got her... Read More →
Chairs/Hosts
YN
Organizers
YN
S121 Abstracts pdf
Tuesday October 6, 2026 20:00 - 21:00 UTC
Zoom Room #1
  Invited Session, Technical Statistical Session

20:00 UTC

S410 - Statistical Inference with Incomplete Data
Tuesday October 6, 2026 20:00 - 21:00 UTC
Zoom Room #4
Incomplete data arise in many scientific fields and present major challenges for modern statistical methodology. Missing values, censoring, and selection bias may substantially affect estimation, hypothesis testing, prediction, and the generalizability of scientific findings. Developing statistical methods that appropriately account for these sources of incompleteness is therefore essential for obtaining reliable conclusions. This session brings together recent methodological advances addressing different aspects of statistical inference with incomplete data. Topics include assessing the generalizability of randomized controlled trials through a sensitivity analysis framework for selection bias, evaluating modern imputation methods for recovering the underlying data distribution, independence testing for high-dimensional incomplete data, and nonparametric testing for censored survival data. Together, these contributions provide complementary perspectives on the analysis of incomplete data and demonstrate how principled statistical methodology can improve inference across a broad range of applications.
Speakers
avatar for Rebecca Andridge

Rebecca Andridge

Professor, The Ohio State University
Rebecca Andridge is a Professor of Biostatistics at The Ohio State University College of Public Health. She conducts methodologic work on imputation methods for missing data, primarily when missingness is driven by the missing values themselves (missing not at random), and on measures... Read More →
avatar for Krystyna Grzesiak

Krystyna Grzesiak

University of Wrocław, Faculty of Mathematics and Computer Science
Krystyna Grzesiak is a PhD candidate at the Institute of Mathematics, University of Wrocław. She conducts research on developing machine learning methods for the analysis of proteomic and metabolomic data.
avatar for Bojana Milošević

Bojana Milošević

Faculty of Mathematics, University of Belgrade
Bojana Milošević is an Associate Professor and Head of the Department of Probability and Statistics at the Faculty of Mathematics, University of Belgrade. Her research interests include nonparametric statistics, statistical hypothesis testing, survival analysis, dependence analysis... Read More →
avatar for Anke Steyn

Anke Steyn

North-West University
Anke Steyn is a lecturer at the North-West University in Potchefstroom, South Africa. Her research interests include survival analysis, goodness-of-fit testing and experimental design. She qualified as an actuary and recently completed her doctoral degree in Statistics. Her great... Read More →
Chairs/Hosts
MC
Organizers
MC
S410 Abstracts pdf
Tuesday October 6, 2026 20:00 - 21:00 UTC
Zoom Room #4
  Invited Session, Technical Statistical Session
  • Session ID 410

20:00 UTC

S506 - Recent Advances in Sequential Inference
Tuesday October 6, 2026 20:00 - 21:00 UTC
Zoom Room #5
Sequential analysis continues to play a central role in modern statistics by enabling data-driven decision making while balancing statistical efficiency, computational cost, and practical constraints. This session highlights recent methodological advances in sequential and multistage inference across a range of contemporary statistical problems. Topics include sequential estimation of distributional overlap with boundary corrections for reliable confidence interval construction, multistage algorithms for efficient data compression under growing dimensions, penalized sequential estimation and variable selection for recurrent event models with high-dimensional covariates, and multistage sampling strategies for constructing minimum-risk confidence regions for multivariate means. Together, these contributions illustrate how sequential methodologies are being extended beyond their classical foundations to address challenges arising from high-dimensional data, adaptive sampling, optimization of statistical risk, and modern computational applications.
Speakers
avatar for Swarnali Banerjee

Swarnali Banerjee

Associate Professor, Director of Data Science Program, Loyola University Chicago
Dr. Swarnali Banerjee is an Associate Professor and Director of Data Science in the Department of Mathematics and Statistics at Loyola University Chicago. She received her Ph.D. in Statistics from the University of Connecticut in 2014. Prior to joining Loyola University in 2016, she... Read More →
avatar for Zhe Wang

Zhe Wang

Denison University
Dr. Zhe Wang is an Assistant Professor in the Department of Data Analytics at Denison University. She earned her B.S. in Statistics from Beijing Normal University and her M.S. and Ph.D. in Statistics from the University of Connecticut. Her research interests include statistical inference... Read More →
avatar for Swathi Venkatesan

Swathi Venkatesan

Fairfield University
Dr. Swathi Venkatesan is an Assistant Professor in the Department of Mathematics at Fairfield University. She earned her PhD in Statistics from the University of Connecticut. Her research interests include sequential estimation and inference, experimental design, and the development... Read More →
avatar for Laura Dumitrescu

Laura Dumitrescu

Fairfield University
Dr. Laura Dumitrescu is an Associate Professor in the Department of Mathematics at Fairfield University, where she has been a faculty member since 2022. Prior to joining Fairfield, she was a member of the Probability and Statistics research group in the School of Mathematics and Statistics... Read More →
Chairs/Hosts
avatar for Swathi Venkatesan

Swathi Venkatesan

Fairfield University
Dr. Swathi Venkatesan is an Assistant Professor in the Department of Mathematics at Fairfield University. She earned her PhD in Statistics from the University of Connecticut. Her research interests include sequential estimation and inference, experimental design, and the development... Read More →
Organizers
avatar for Swathi Venkatesan

Swathi Venkatesan

Fairfield University
Dr. Swathi Venkatesan is an Assistant Professor in the Department of Mathematics at Fairfield University. She earned her PhD in Statistics from the University of Connecticut. Her research interests include sequential estimation and inference, experimental design, and the development... Read More →
S507 Abstracts pdf
Tuesday October 6, 2026 20:00 - 21:00 UTC
Zoom Room #5
  Invited Session, Technical Statistical Session

21:00 UTC

S122 - Advances from Junior Bayesian Statisticians: Bayesian Models for Complex Networks and Relational Data
Tuesday October 6, 2026 21:00 - 22:00 UTC
Zoom Room #1
The junior section of the International Society of Bayesian Statistics (j-ISBA) is excited to present a session showcasing the work of outstanding early-career women researchers from the United States, Italy, and Germany. This session highlights recent advances in Bayesian methodology for analyzing complex relational and structured data, with a focus on flexible probabilistic modeling, scalable computation, and impactful real-world applications.

The four talks highlight modern Bayesian approaches for the modeling of networks and high-dimensional relational data. They span generative models for graph-structured data grounded in classical Bayesian principles of exchangeability, Bayesian nonparametric models for interaction networks with evolving community structure, latent variable models that account for uncertainty and reporting bias in social network data, and hierarchical tensor factorization methods for large-scale sparse relational arrays. Across these contributions, speakers develop computationally efficient inferential strategies using tools including variational inference, hybrid Monte Carlo algorithms, and scalable latent variable methods. These approaches enable Bayesian analysis in settings involving millions of observations while maintaining interpretable probabilistic models.

Together, these talks demonstrate the innovative methodological, theoretical, and applied contributions of early-career women Bayesian statisticians.
Speakers
avatar for Federica Zoe Ricci

Federica Zoe Ricci

Swarthmore College
Federica is an Assistant Professor of Statistics (tenure-track) at Swarthmore College, a liberal-arts college located near Philadelphia. She received her PhD in Statistics from UC Irvine. She is currently interested in the development of modeling approaches and scalable computational... Read More →
avatar for Louise Alamichel

Louise Alamichel

Bocconi University
Louise is a post-doctoral researcher at Bocconi University in Milan, working with Daniele Durante. Her research is on Bayesian non-parametric mixture models. On one side, she focuses on the inference of network data using these models, and on the other side, on their asymptotic properties... Read More →
avatar for Martina Contisciani

Martina Contisciani

Center for Critical Computational Studies @ Goethe University Frankfurt
Martina Contisciani is a postdoctoral researcher at the Center for Critical Computational Studies (C3S) at Goethe University Frankfurt. Her research focuses on the development of statistical models and algorithms for the study of complex systems, with a particular interest in inferential... Read More →
avatar for Jie Jian

Jie Jian

The University of Chicago
Jie is a postdoctoral scholar at the Data Science Institute at the University of Chicago. Her research develops interpretable probabilistic and machine-learning methods for network and tensor data. These methods are motivated by applications in brain imaging, climate science, international... Read More →
Chairs/Hosts
EL
Organizers
EL
S122 Abstracts pdf
Tuesday October 6, 2026 21:00 - 22:00 UTC
Zoom Room #1
  Invited Session, Technical Statistical Session
  • Session ID 122

22:00 UTC

S123 - Borrowing Strength: Statistical Strategies for Imperfect Data
Tuesday October 6, 2026 22:00 - 23:00 UTC
Zoom Room #1
This session highlights how modern biostatistics tackles a shared challenge across very different problems: making valid, efficient inference when the data we have is incomplete, limited, imbalanced, or imperfectly comparable to the question we want to answer. Talks in this session explore how statisticians "borrow strength" – from historical or external data sources, from related but heterogeneous datasets, from carefully constructed causal designs, and from generative models that learn the structure of missingness itself – to push beyond the limitations of any single dataset. Together, these four talks, spanning clinical trials, large-scale survey methodology, high-dimensional prediction, and observational causal inference, showcase the breadth of ideas at the intersection of biostatistics, machine learning, and causal reasoning, and the methodological creativity required to turn imperfect data into trustworthy conclusions.
Speakers
avatar for Xiaoting Chen

Xiaoting Chen

New York University
Xiaoting Chen is a 4th-year Biostatistics PhD candidate at New York University School of Global Public Health. Her research focuses on dynamic borrowing methods for clinical trial design, with an emphasis on frequentist frameworks that combine historical and concurrent control data... Read More →
avatar for Yuyu(Ruby) Chen

Yuyu(Ruby) Chen

New York University
Yuyu(Ruby) Chen recently graduated from NYU School of Global Public Health with PhD in Biostatistics. Her PhD work focused on developing and evaluating advanced missing data imputation frameworks tailored for healthcare research, which covers the aspects including clinical trials... Read More →
avatar for Jianan Zhu

Jianan Zhu

New York University
Jianan is a rising fifth-year PhD student in Biostatistics. Her main research interest is on design-based causal inference. She is interested in observational studies, randomized trials, sensitivity analysis, and their applications in health policy research, infectious disease research... Read More →
avatar for Iris Zhang

Iris Zhang

New York University
Iris is a 4th-year Biostatistics PhD student at New York University School of Global Public Health. Her research focuses on statistical machine learning and high-dimensional inference, with an emphasis on transfer learning, representation learning, and AI-driven methods for healthcare... Read More →
Chairs/Hosts
YM
Organizers
avatar for Xiaoting Chen

Xiaoting Chen

New York University
Xiaoting Chen is a 4th-year Biostatistics PhD candidate at New York University School of Global Public Health. Her research focuses on dynamic borrowing methods for clinical trial design, with an emphasis on frequentist frameworks that combine historical and concurrent control data... Read More →
S123 Abstracts pdf
Tuesday October 6, 2026 22:00 - 23:00 UTC
Zoom Room #1
  Invited Session, Technical Statistical Session

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
avatar for Emily Roberts

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 →
avatar for Megan McCabe

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 →
avatar for Madeline Abbott

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 →
avatar for Margaret Banker

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
avatar for Emily Roberts

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 →
Organizers
avatar for Emily Roberts

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 →
S217 Abstracts pdf
Tuesday October 6, 2026 22:00 - 23:00 UTC
Zoom Room #2
  Invited Session, Career or Professional Development Session

22:00 UTC

S508 - Statistical Methods and Applications in One Health
Tuesday October 6, 2026 22:00 - 23:00 UTC
Zoom Room #5
This session will showcase statistical methods and data-driven approaches for One Health, reflecting the interconnected health of humans, animals, and the environment. Presentations by women graduate students in statistics will highlight innovative methodological and applied research across One Health domains, spanning the development and application of statistical methods for handling complex, high-dimensional, and heterogeneous data, improving prediction and inference, and addressing uncertainty in human, animal, and environmental health systems. The session also provides a platform for emerging researchers to share their work, engage with the statistical community, and foster collaboration and mentorship.
Speakers
avatar for Sonja Friesen

Sonja Friesen

University of Guelph
Sonja graduated from the University of Manitoba with a BSc in Data Science with a minor in Biological Sciences and recently began a Master's in Statistics with a One Health Concentration at the University of Guelph. She enjoys working on any project that combines health care, R programming... Read More →
avatar for Ayisha Cok

Ayisha Cok

University of Guelph
Ayisha N. COK is a Ph.D. student in Statistics at the University of Guelph. Her research focuses on developing statistical methods for high-dimensional biomedical data, with interests in measurement error, genotype imputation, meta-analysis, Bayesian methods, and integrative data... Read More →
avatar for Heshani Mendis

Heshani Mendis

University of Manitoba
Heshani Mendis is an MSc student in Statistics at the University of Manitoba, Winnipeg, Canada. Her research interests lie in statistical machine learning, with a focus on tree-based ensemble methods and flexible splitting criteria for random forests. Her current work introduces a... Read More →
avatar for Nimsara Dissanayaka

Nimsara Dissanayaka

University of Guelph
Nimsara Dissanayaka a PhD student in Applied Statistics at the University of Guelph. Her research focuses on circular data analysis mainly the development of circular regression models, model assessment, and prediction. She is particularly interested in environmental applications... Read More →
Chairs/Hosts
EA

Elif Acar

University of Guelph
Organizers
EA
S508 Abstracts pdf
Tuesday October 6, 2026 22:00 - 23:00 UTC
Zoom Room #5
  Invited Session, Technical Statistical Session
 
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