Lauren Farrell will be starting as a M.Sc student in Applied and Industrial Mathematics in the fall after completing her B.Sc in Mathematics at Mount Allison University with an honors project focusing on modeling the global monkeypox outbreak. She will continue her work in epidemiology in her Master with her research focusing on cholera.
Sherif Eneye Shuaib is a Ph.D. student at York University. He completed his Msc. in Applied Mathematics from the Prince of Songkla University, Thailand, in January 2020. He is currently working on modeling the impacts of environmental stressors on species distribution and abundance. His research interests include mathematical modeling, population dynamics, and infectious disease modeling. He has also worked as a Teaching Assistant at the Prince of Songkla University in parallel to his MSc. degree and as an Editor at the publication unit, Prince of Songkla University, Pattani Campus, Thailand.
Junzi is a passionate and highly motivated master’s student in Biostatistics at the Dalla Lana School of Public Health. With a solid background in Mathematics and Statistics from McMaster University, she has honed expertise in mathematical modeling, predictive analytics, and statistical methodologies. During undergraduate studies, Junzi worked on significant projects, such as developing an SIFR model for analyzing Ebola Virus Disease transmission and employing time series analysis with ARIMA models to predict environmental factors influencing public health. Junzi is driven to apply those analytical capabilities to address public health challenges and develop data-driven solutions. Enthusiastic about leveraging AI and statistical tools, she is eager to contribute to impactful research that can inform public health policies and improve outcomes.
Weiran (Russell) Wang is a graduate student in Mechanical & Industrial Engineering at the University of Toronto, with a emphasis on machine learning and data analysis. He completed his B.Sc in Applied Mathematics specialist, also from the University of Toronto. Currently, he is working on mathematical modeling of infectious diseases dynamics in the lab. His multidisciplinary experience spans deep learning, computer vision, and predictive analytics, with contributions to projects including ICU bed occupancy forecasting, 3D-Gaussian Splatting optimization, LLM-powered scouting tools, etc
Stella completed her MSc in Mathematical Sciences at AIMS Senegal in July 2025. Her master’s research was on developing a stochastic HIV model under partial information and applying filtering techniques to estimate hidden epidemiological states from partial and noisy observations. In addition, she completed an internship at AIMS Senegal in June 2026, where she used stochastic modelling to study the impact of environmental factors on poliovirus transmission. Her research interests include mathematical epidemiology, stochastic differential equations, inference under uncertainty, nonlinear filtering, infectious disease modelling, and AI-driven approaches for epidemic forecasting and control.
Ebenezer Adeniyi completed his Master of Arts in Applied and Industrial Mathematics at York University. Prior to this, he earned a Bachelor of Science degree in Mathematics with honours from Nigeria’s premier university, the University of Ibadan. His research focuses on mathematical modelling of infectious diseases and the application of quantitative methods to public health. He is currently pursuing a PhD at the Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health, University of Toronto.
M Josee Uwanyirigira holds a Bachelor’s degree in Mathematics and Statistics from the University of Rwanda and a Master’s degree in Mathematical Sciences from the African Institute for Mathematical Sciences (AIMS Rwanda), where she specialized in malaria modelling. She has also worked as a data scientist and modeller within Rwanda’s health sector, applying statistical analysis and predictive modelling to support national health policies and malaria surveillance initiatives. She is currently pursuing a PhD in Applied Statistics at Jomo Kenyatta University of Agriculture and Technology (JKUAT) and is affiliated with the AIMS Research and Innovation Centre (AIMS RIC). Her doctoral research integrates spatial statistical methods and machine learning to examine how climatic and environmental factors influence malaria transmission, identify vulnerable populations and geographic hotspots, and assess future malaria risk under changing climate conditions.