By Radu Craiu
The Department of Statistical Sciences at the University of Toronto continues to recruit exceptional talent at an accelerated pace. This year, we'd like to give a warm welcome to four fantastic new colleagues.
Liza Bolton will be joining the University of Toronto's Department of Statistical Sciences as an assistant professor, teaching stream, in January. Over the last few years, alongside teaching a large introductory statistics course at the University of Auckland in New Zealand, Liza has run a statistical consulting business, working with clients in education, not-for-profits, transport consulting, and a range of other industry sectors. After living half her life in New Zealand, she looks forward to bringing her experience in research, business, and teaching back to the country in which she was born. Liza is passionate about making the world a more statistically literate place in general and helping her students become better statistical communicators in particular. She is in the process of completing her PhD at the University of Auckland in health and official statistics.
Liza speaks publicly about her work and statistical sciences on a regular basis. You can find some of her more recent media interviews here:
- RNZ: The Cambridge Analytica fallout
- Storyo: Everything you need to fall in love with Statistics
- StatsChat: Lotto… you’re doing it wrong!
Gwen Eadie is an assistant professor jointly appointed between the University of Toronto's Department of Statistical Sciences and the Department of Astronomy & Astrophysics. Her research is in the interdisciplinary field of astrostatistics; she is interested in using and developing modern statistical methods for astronomy applications in order to answer fundamental questions about the universe. Dr. Eadie serves on astrostatistics committees in both the American Statistical Association and the American Astronomical Society. She holds a PhD in Physics and Astronomy from McMaster University, and her PhD was awarded the national J. S. Plaskett Medal. Learn more about her research.
Chris Maddison will be joining the University of Toronto's Departments of Computer Science and Statistical Sciences and the Vector Institute as an assistant professor in July 2020. He works on methods for machine learning, with an emphasis on those that work at scale in deep learning applications. He is particularly interested in methods for numerical integration and optimization, and has worked on gradient estimation, variational inference, Monte Carlo methods, and first-order methods for optimization.
Chris is a member at the Institute for Advanced Study in Princeton in the Special Year on Theoretical Machine Learning, as well as an Open Philanthropy AI Fellow. He received a NeurIPS Best Paper Award in 2014, and was one of the founding members of the AlphaGo project.
Silvana Pesenti recently joined the University of Toronto's Department of Statistical Sciences as an assistant professor in insurance risk management. Her research interests include quantification of risk and uncertainty and developing sensitivity analysis methodologies for models used in insurance and financial risk management. She holds a PhD in Actuarial Science and Insurance from Cass Business School, London, for which she was awarded the Dimitris N. Chorafas Prize by the Weizmann Institute of Science, and a MSc in Mathematics from ETH Zurich. In fall 2019, Silvana received the Dorothy Shoichet Women Faculty Award of Excellence.
