This story is published in YFile’s New Faces feature issue 2024. Every September, YFile introduces and welcomes those joining the York University community.
York University’s Faculty of Science is welcoming five new full-time, permanent faculty members this fall.
“The Faculty of Science has hired fantastic new faculty members that will contribute to enhancing our Faculty’s academic excellence, diversity, and research and teaching capacity,” says Faculty of Science Dean Rui Wang. “I look forward to working with our outstanding new colleagues, who bring diverse experiences and perspectives that will strengthen our Faculty as a destination of choice for students and aspiring scientists.”
Divya Sharma
Sharma joins the Department of Mathematics & Statistics as an assistant professor in the data science stream. She holds a PhD in computer science with a specialization in machine learning (ML) from the Indian Institute of Technology Jodhpur.
Following her doctoral studies, Sharma completed a postdoctoral fellowship in the Biostatistics Department at the Princess Margaret Cancer Centre, part of the University Health Network, in Toronto. During this time, she was awarded the Canadian Institutes of Health Research STAGE (Strategic Training for Advanced Genetic Epidemiology) Fellowship for 2020-22. Following that, she worked as a senior biostatistician and clinician investigator at the University Health Network, where she developed artificial intelligence models to address various health outcomes, including liver disease, cancer, sepsis and osteoarthritis. She did so through interdisciplinary collaborations at Toronto General Hospital, the Krembil Research Institute and the Princess Margaret Cancer Centre.
Sharma’s research program focuses on developing novel deep learning models for integrative, high-dimensional modelling of multi-modal big health-care data, comprising clinical, imaging and genomic domains. Her work places a strong emphasis on clinical interpretability and deployability, with innovative ML modelling approaches published in high-impact journals such as Lancet Digital Health and Bioinformatics.
Sharma has recently received the Natural Sciences & Engineering Research Council of Canada Discovery Grant and Launch supplement for 2024, as well as a Resource Allocation Grant 2024 from the Digital Research Alliance of Canada, which will help steer her research program at York and provide computational resources to develop deep learning models for guiding personalized medicine. In her teaching at York, she wants to provide students with a strong foundation in statistics, mathematics and computational principles behind complex concepts in machine learning and data science. Her goal is to equip students so they can become future leaders in the application and development of robust modelling approaches.
Yi Liu
Liu joins the Department of Mathematics & Statistics as an assistant professor. He received his PhD in statistical machine learning from the University of Alberta in 2023, following his postdoctoral fellowship and experience as an assistant lecturer at the same institution. Liu also holds a master’s degree in mathematics from Beijing Normal University.
Liu’s research focuses on developing robust algorithms for differential privacy, functional data analysis and reinforcement learning. His work seeks to balance data utility with privacy preservation, exploring innovative approaches to protect user information while maintaining the integrity of statistical analysis. His research has been presented at top-tier conferences and published in leading journals like Statistica Sinica and Bernoulli.
Liu’s contributions are advancing both theoretical and applied aspects of statistical machine learning, particularly in privacy-preserving technologies and optimization in dynamic environments.
Tianyu Guan
Guan joins the Department of Mathematics & Statistics as an assistant professor. Guan received her PhD in statistics and MSc in actuarial science at Simon Fraser University. Before joining York, she was an assistant professor at Brock University from 2020 to 2024. Guan’s research spans several cutting-edge areas, including sports analytics, functional data analysis, machine learning and data science. She specializes in developing novel statistical and data science methods to analyze data across various fields such as sports, public health and economics.
In recent years, Guan’s research interest in sports analytics has particularly grown. She analyzes sports data to craft better strategies, improve team and player performance, and influence betting odds. She has collaborated with various organizations to advance the use of statistical techniques in sports decision-making. Her goal is to use sports analytics to help teams and players gain a competitive edge.
Bruce Howard
Howard joins the Department of Physics & Astronomy having received his undergraduate degree in physics and astronomy from the University of Pittsburgh and his PhD in physics from Indiana University. Following this, Howard held a postdoctoral position as a research associate at Fermilab, near Chicago.
Howard’s research focuses on experimental particle physics, specifically neutrinos. His main interest is in furthering our understanding of the properties of neutrinos and antineutrinos, especially around the properties at work in the process known as neutrino oscillation. Neutrino oscillation is the phenomenon where a neutrino or antineutrino created as one type can later interact as another type.
Howard’s research efforts at York in the next years will primarily use liquid argon (LAr) time-projection chamber (TPC) detectors to study neutrinos. One focus is on realizing and performing studies with an upcoming, powerful neutrino experiment (DUNE) in which an international collaborative effort will deploy detectors near the beam at Fermilab and far away in South Dakota. The other focus will be on conducting studies with a smaller LAr TPC detector that is currently operating and enabling interesting neutrino studies as well as key opportunities to prepare for the next-generation experiment.
Stephanie Jones
Jones will join the Department of Chemistry as an assistant professor in February 2025. Her research is focused on atmospheric aerosols and environmentally relevant surface films. In particular, she is interested in understanding how atmospheric transformations impact the fundamental properties of aerosols and films. Jones uses single particle levitation methods, as well as neutron and X-ray scattering, to study transformations of aerosols and films in the laboratory to determine their fundamental physicochemical and optical properties.
Jones has an integrated master’s in chemistry from the University of Bristol and a PhD from Royal Holloway University of London. Following her PhD, she undertook a postdoctoral fellowship at the University of Victoria in Canada, before moving back to the U.K. where she worked in industry for a brief period as a product manager at Laser Quantum. She then transitioned back to academia and chemistry, completing a second postdoc in environmental chemistry at the University of Toronto where she expanded her research interests to include the indoor environment.
After successfully obtaining funding for her own position from the German Research Foundation, Jones then moved to the Institute of Meteorology & Climate Research’s Atmospheric Aerosol Research Department at the Karlsruhe Institute of Technology (KIT) in Germany, where she is currently based. Her research at KIT involves the study of photochemically induced transformations of wood smoke aerosol using single droplet studies and large-scale cloud simulation chamber experiments.
Jones is excited to return to Canada and looks forward to contributing to the atmospheric chemistry community.