Featured Researcher: Melissa GervaisPosted on October 14, 2019
Get to know Dr. Melissa Gervais, an ICS co-hire with the Department of Meteorology and Atmospheric Science in the College of Earth and Mineral Sciences.
Dr. Gervais uses statistical and machine learning approaches to understanding various aspects of climate science. Some of her research has focused on the North Atlantic Warming Hole, a region of the atmosphere that has experienced reduced rates of warming than the global average.
What do you hope to accomplish with your research?
I hope to gain a better understanding of the processes that might occur with climate change so that we can improve our projections and be more prepared as a society
How does supercomputing enable your research?
I run global climate simulations that require high performance computing
What is your academic background?
Undergraduate from the University of Toronto (Planetary Science), Master’s from the University of Toronto (Atmospheric Physics), and PhD from McGill (Atmospheric and Oceanic Science).
What’s your advice for would-be scientists?
Someone I look up to recently told me that you should always study the questions that you find you just can’t let go of. I think this is great advice.
What are the big problems you hope your research solves — and/or the big opportunities you hope your research seizes?
My research strives to understand the interactions that occur between the ocean-sea ice-atmosphere system in the context of future climate change
What types of interdisciplinary collaborations would you like to build in the future?
I study the interactions between the atmosphere-ocean-sea ice systems so my research topic is very interdisciplinary in nature. The impact of melting ice sheets on this system is something I would love to tackle through collaboration. From a methodology stand point I have been using machine learning in my work and am embarking on the use of deep learning. I think as we move towards using these types of methods that our newer to our fields, we can learn a lot through collaborations with others using the same methods but in different disciplines.
What profession other than your own would you enjoy?
What is something that people are surprised to discover about you?
Your three favorite podcasts?
It’s been a Minute with Sam Sanders, Up First, and Embedded
Who is the most famous science celebrity – or celebrity – that you’ve met?
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