Congratulations to all of the following statisticians who became accredited at the A.Stat and P.Stat level in March 2026.
A.Stat. Accreditations
Jose Manuel Rodriguez Caballero
José is a mathematician and statistician who is a permanent resident of Quebec and in the process of becoming a citizen. Education: master's degree in mathematics (Université de Montréal, 2015), master's degree in statistics (2025), PhD in mathematics (in progress) (Université Laval, since 2024). Experience: teaching (2013–2022), research in quantum cryptography (2019–2021, University of Tartu), statistical consulting (2023–2025, Université Laval). Awards: Brindamour and ERASMUS+ scholarships, contributions to AFP and Wolfram. Skills: cryptography, statistics, programming (C++, Python, R).
Jacob Winch
Jacob switched from neuroscience to statistics during his first year at the University of Alberta. He enjoys finding ways to apply statistical tools to practical, real-world problems. In his third year, he joined Orennia, an energy-analytics firm, as an intern where he wrote reports and built data visualizations and statistical models using energy sector data. After graduating from the University of Alberta in December 2025, he returned to Orennia where he is an associate on the energy storage team, working with data and analytics for investors in the energy sector. His professional interests focus on machine learning, energy economics, and sports analytics.
Veronica (Ka Wai) Lai
Veronica holds a PhD in anaesthesia and intensive care from the Chinese University of Hong Kong, with formal training in quantitative methods, psychometrics, and clinical research. She has specialized training in biostatistics and clinical trial methodology, including Bayesian adaptive trials. Her academic background is grounded in psychology and health sciences, with a strong emphasis on applied statistical analysis in medical and child health research.
She is currently a research associate at the Hospital for Sick Children (SickKids) in Toronto. Her work focuses on clinical trial methodology, outcome design and measurement, patient-reported outcomes, and the evaluation of reporting quality and research usability in pediatric and rare disease contexts. She holds consulting experience with children’s hospital research institutes and international collaborators.
Additionally, she has previously held academic appointments as an assistant professor and postdoctoral fellow in Hong Kong and Canada. Her professional experience includes designing and analyzing randomized controlled trials, validating measurement instruments, conducting program evaluations, and supporting interdisciplinary research teams. Her professional interests focus on improving the rigour, transparency, and interpretability of statistical methods in health research, particularly in intensive care, pediatric and rare disease, and supporting evidence-based decision-making through robust statistical practice.
P.Stat. Accreditations
Vineetha Warriyar
Vineetha holds an MMath in statistics from the University of Waterloo and a PhD in statistics from Memorial University of Newfoundland. Her professional experience spans academic and health research environments, where she has provided statistical leadership in study design, advanced analytical methods, and interpretation across diverse applied fields, including pediatric and maternal health, neurodevelopment, psychiatry, and clinical trials. She currently serves as a biostatistics consultant at the Alberta Children’s Hospital Research Institute at the University of Calgary. In this role, she supports approximately four to five research projects each month and provide statistical guidance to more than 390 members and around 1,000 trainees within the institute. Her work includes developing analysis plans, implementing appropriate statistical models, and ensuring methodological rigour throughout the research process.
Her professional interests include longitudinal and multilevel modelling, causal inference, and the design and analysis of observational and interventional studies. She remains committed to ongoing professional development, enhancing statistical literacy among interdisciplinary teams, and promoting reproducible, high-quality research practices.
David Campbell
David is a professor in the School of Mathematics and Statistics and the School of Computer Science at Carleton University. Academically, he runs a collaborative team researching inferential methodology at the intersections of statistics with machine learning, computing, natural language processing, and applied mathematics to solve problems inspired by industry and government collaborations.
His career path follows a theme of industrial and government collaborations including spending 2021–2023 leading the inferential data science team at the Bank of Canada followed by leading the creation of Carleton University's Bachelor of Data Science degree. Before moving to Carleton University in 2019, he was a faculty member at Simon Fraser University, where he led the creation of one of Canada’s first Bachelors of Data Science degrees. He was the inaugural president of the Data Science and Analytics Section of the Statistical Society of Canada (SSC) and in 2025–2026 he is the president of the Business and Industrial Statistics Section.
Mateen Shaikh
Mateen earned his BMath (statistics) from the University of Waterloo in 2008. In 2009 and 2013, he earned his MSc (statistics) and PhD (statistics), respectively, from the University of Guelph. He was a postdoctoral fellow at McMaster University from 2013 to 2017. Since 2017 he has been a faculty member at Thompson Rivers University, where he is currently an associate professor of statistics and data science in the Department of Mathematics and Statistics.
He primarily teaches courses in statistics at the master's and undergraduate levels. He also supervises students in statistical projects both within discipline and as statistical supervisor in ecology. His research has evolved to address sustainability in statistical learning by better using inconvenient, heterogeneous data in statistical analyses and optimizing algorithms for inference to simultaneously reduce computational demand while broadening the discrete model space. He provides service to statistical communities and statistical service to other communities. He is currently treasurer for the SSC's Business and Industrial Section. He has previously served a term on the SSC's new investigator's committee. He represents his institution at CANSSI and the SSC.