PhD candidate Micaela Consens wins 2023 T-CAIREM Trainee Rounds Award
Micaela Consens is the winner of the 2023 T-CAIREM Trainee Rounds Award for her research presentation titled "Transforming Genomic Interpretability: A DNABERT Case Study."
Consens is a PhD candidate in computer science with a focus on Machine Learning applications for healthcare at the University of Toronto. She's worked in a variety of domains ranging from software development at the Sick Kids Centre for Computational Medicine and the UHN Techna Institute, to research for the CAMH Krembil Centre for Neuroinformatics.
What inspired you to pursue a doctorate in computer science?
Both of my parents work in the field and shared their love for the problem-solving aspect of this discipline with me early on. As for pursuing the intersection of Machine Learning and healthcare specifically, I have always wanted to work on problems whose solutions have the potential to better people’s lives.
How do you explain your research to those of us without a medical background?
I study how Machine Learning models make decisions in healthcare contexts, like predicting genetic conditions from DNA. My work focuses on ensuring these models are trustworthy and can be understood and regulated, especially when they impact human health.
What inspired you to research this topic?
The lack of interpretability in Machine Learning models applied to healthcare motivated my research. I believe that for these models to be truly beneficial, we need guidelines and tools to ensure their reliability, especially in critical health contexts.
What outcomes do you hope your research will eventually lead to?
My hope is that my research will lead to improved testing and validation methods for Machine Learning models before they are used in healthcare and other important settings.
What do you like to do when you aren’t working?
I love to go running (especially with my dog Siku) and go hiking and camping with my loved ones.
What advice would you give to other researchers who are interested in following in your footsteps?
Get a good night's sleep and get outside: everything is easier when you’re well-rested and relaxed. Once you’ve got that going, don't limit your interests; explore a variety of subjects beyond Computer Science. Diverse knowledge can be valuable when tackling complex problems.
What’s the best part of doing the type of research that you do?
I appreciate that my research brings us closer to understanding how Machine Learning models “think.” This deeper insight can provide valuable contributions to fields like health, biology, and medicine.
About the T-CAIREM Trainee Rounds
Each year T-CAIREM's Trainee Rounds highlight innovative projects from emerging researchers across Canada who are exploring applications of artificial intelligence (AI) in medicine.
T-CAIREM receives dozens of applications from emerging researchers for the annual Trainee Rounds that are shortlisted to ten proposals. The successful applicants then present their research before a panel of AI in healthcare leaders for a cash prize.
Research topics presented in the Trainee Rounds include methodological projects, translational clinical projects, education, data governance, health policy, health economics, and ethics.
