Machine Learning for Prioritization in Conservation
and Disease Surveillance 

In recent years, biologists have come up with a number of innovative applications for machine learning and computationally intensive approaches in ecology, evolution, and conservation. Often these methods are leveraged because they allow ecologists to capitalise on incomplete datasets in systems where the processes generating observed patterns are unknown. Further, because of their predictive nature these algorithms have proved useful for helping us to direct limited resources to the areas of greatest need. In this talk I will discuss two cases where I have applied machine learning in my research program. The first – dealing with predicting suitable habitat for Neotropical primates – will highlight how machine learning can be used for targeted conservation. The second – predicting which bat species may be future carriers of diseases capable of infecting humans – will touch on how these approaches can aid global sampling efforts under the One Health paradigm. Finally, I will finish with a discussion on the importance of communicating these results effectively to managers and the public, and the implications.

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Cylita Guy
University of Toronto
Ecology & Evolutionary Biology

Dr. Cylita Guy obtained her PhD in the department of Ecology and Evolutionary Biology at the University of Toronto, where she currently works as a research associate. Using both fieldwork and computational methods, she is trying to understand why bats seem to be good at carrying viruses that they sometimes share with humans, but rarely get sick from themselves. Cylita is also an experienced science communicator. She spent 10 years working at the Ontario Science Centre, started a Junior Bat Biologist program with the High Park Nature Centre, and organized Canada’s first national science communication conference for graduate students. Cylita has also applied her computational skills to digital media data, previously working as a data scientist for the Canadian Broadcasting Corporation.

Wed, Oct 23, 2019
04:00 PM - 05:30 PM
Centre for Ethics, University of Toronto
200 Larkin