Speakers
Arranged alphabetically by first name, within talk category
Keynote speakers
Daphna Harel
Studying queer data while living it: Positionality, power, and practice
Daphna Harel (she/her) is an Associate Professor of Applied Statistics at the Steinhardt School of Culture, Education, and Human Development at New York University. Her research focuses on survey design and analysis, particularly in situations where obtaining meaningful measurements is hard. She aims to improve the quality of survey research by designing better questions, reducing burden on survey respondents, and providing better and more advanced methods for data analysis. Daphna believes that statistical analysis should be conducted in an effort to improve society and quality of life for all people. Her recent work with the NYU QUEER data lab focuses on work at the intersection of LGBTQIA+ lives and statistics, developing new methods to better understand and serve the community.
Hadley Wickham
Hadley is Chief Scientist at Posit PBC, winner of the 2019 COPSS award, and a member of the R Foundation. He builds tools (both computational and cognitive) to make data science easier, faster, and more fun. His work includes packages for data science (like the tidyverse, which includes ggplot2, dplyr, and tidyr) and principled software development (e.g. roxygen2, testthat, and pkgdown). He is also a writer, educator, and speaker promoting the use of R for data science. Learn more on his website, http://hadley.nz.
Regular talk speakers
Chris Battiston
Intersectionality in LGBTQ+ health research: Practical analysis in R Using upset plots)
Chris has over 20 years’ experience as a database administrator / data analyst, with more than half of that in healthcare. He has been a REDCap Administrator for over 10 years and has won numerous awards for training documentation and community involvement. He has extensive experience in survey design and methodology, data quality, regulations, validation, and training users. He volunteers with a number of organizations supporting marginalized populations in data science, data management, and various committees on REDCap. When he’s not geeking out in front of a computer, he’s spending time with his wife and young son.
J. Audra Williams
Belonging is political: Measuring queer sense of belonging in Higher Ed using R
J. Audra Williams (he/they) is second-year Educational Policy and Evaluation PhD student in the Mary Lou Fulton College for Teaching and Learning Innovation at Arizona State University. J. Audra’s research centers the stories and narratives of queer and trans students, staff, and faculty in colleges and universities. He is specifically interested in challenging the tragic trope that is often portrayed for queer and trans people and instead highlighting aspects of queer joy. J. Audra has a growing interest in incorporating QuantCrit and QueerQuant methodologies, bringing critical perspectives to quantitative research on LGBTQ+ experiences in higher education.
Jasmine Daly
High, Low, Jack, & Claude: AI-assisted Shiny development
Jasmine Daly builds human-centered decision systems for nonprofits and mission-driven organizations, helping them make better, fairer, and more confident choices with their data. She creates custom dashboards, predictive models, and AI training & workshops that turn complex, messy data into clear, actionable insights for staff, leadership, and boards.
Joshua Gutoskie
Migrating legacy code to R: A team-based approach to open-source adoption
Joshua Gutoskie is a senior methodologist at Statistics Canada, specializing in survey methodology and statistical methods behind official statistics. He is currently focused on integrating open-source tools, like R and Git, into both new and legacy workflows, with an emphasis on team building and collaboration. Outside of work, Joshua is active in his local 2SLGBTQIA+ inclusive rugby club where he serves as captain of the men’s+ team.
Njoki Njuki
Queer stories through data: Lighting LGBTQ+ cinema with R and Shiny
Njoki Njuki is a biostatistics-trained data professional with over seven years of experience supporting clinical and epidemiological research using large electronic health record (EHR) and longitudinal datasets. She specialises in data preparation, cohort definition, and reproducible statistical programming in R for health research. Njoki holds a BSc in Biostatistics and is currently completing an MSc in Statistics and Data Science (Biostatistics) at Hasselt University. She has presented at international events such as Shiny Conference and the Manchester R User Group, and is an active member of the global R community, co-organising R-Ladies Remote.
Ryan Timpe
The cheesecake ROI: Building a marketing mix model with tidymodels and The Golden Girls
A lifelong enthusiast of math and those iconic plastic bricks, Ryan has been a data scientist at the LEGO Group since 2019. In this role, he uses R and python to construct models to optimize sales and marketing strategies and then promotes their value across the organization. In his spare time, he enjoys backflipping at gymnastics and watching classic sitcoms.
Tamires Martins
Queer stories through data: Lighting LGBTQ+ cinema with R and Shiny
Tamires Martins is a PhD student in Pharmacology at UFSC (Brazil), working on biomarkers of depression and animal behavior. She develops computational tools for biomedical evidence synthesis, with interests in automation, visualization, and reproducible research.
Lightning talk speakers
Hannah Frick
pointblank, was I expecting this?
Hannah Frick is a software engineer at Posit, working mainly on the tidymodels framework. She holds a PhD in statistics and is a co-founder of R-Ladies Global.
Hanne Oberman
Seeing what’s missing: Visualization of incomplete and imputed data
Hanne is a PhD candidate in the department of Methodology and Statistics at Utrecht University, The Netherlands. As part of their research on missing data methods, Hanne created and maintains R packages for valid analyses on incomplete datasets.
Kristin Bott
Beyond drag bingo: Building community at work
Kristin manages the Posit Academy data science education program, including the fantastic mentor crew, and supports learners as they build skills in both code and collaboration. With a background in natural science, teaching, and research, Kristin is interested in making technical topics accessible through the power of learning communities, ultimately empowering individuals to do great work.
Noah Pevie
Factor or network? Modeling the complexity of gender minority stress in transgender communities
Bio TBC
Rafael Henry-Venson
Teaching pharmacokinetics with confidence: How R helps students “see” the science
I am a pharmacology and forensic toxicology expert with a career spanning the Brazilian Scientific Police, HTA consultancy, and academia. Currently, I balance teaching and research with Equality, Diversity, and Inclusion (EDI) leadership, which earned me a shortlisting for the 2025 THE Awards for Outstanding Contribution to EDI for my Rainbow Office Hours initiative. Beyond the classroom, I contribute to the global scientific community as an HTA consultant and Academic Editor for PLoS One.
Trystan Washburne
The two step method: Accurate record keeping for sex and gender
Trystan is a PhD student studying at the University of Stirling, where he’s examining the ways in which transgender participants are recorded in survey data. When he’s not collecting terrible examples of sex and gender questions found in the wild, he enjoys reading fiction and practicing martial arts.
Ursula Kaczmarek
Elevating open data: Creating 3D visuals with NYC ppen climate data
Ursula is a Brooklyn, New York-based data scientist focused on civic tech. She concentrates her research on voter engagement, economic development, and public infrastructure and services. She began her career as a lawyer working on open data policy and spent three years working on civic projects in Tbilisi, Georgia.