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Mathieu Ravaut

MScAC Data Science Concentration alumnus Mathieu talks about advancing healthcare through machine learning.

By U of T Statistical Sciences

Current Job: Machine Learning Research Schientist, Layer 6

Master’s degree: General engineering (CentraleSupélec) and data science (University of Toronto)

MScAC Cohort: 2017

Hometown: Bordeaux, France

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His love for interdisciplinary research drew Mathieu to U of T’s Master of Applied Computing (MScAC) Data Science Concentration. An internship with AI research lab Layer 6 allowed him to put his multi-faceted education to good use – advancing healthcare through machine learning.

I really believe in the Tech for Good movement – trying to apply new technologies that improve people’s everyday life. Knowing that my internship project might one day improve the life of people with diabetes is a huge motivator for me. - Mathieu Ravaut, machine learning research scientist, Layer 6

Statistical Sciences: When did you become interested in data science?

Mathieu Ravaut: Towards the end of my undergraduate studies, a lot of people were talking about machine learning. I have always been super interested in math and computer science, so I took a few online courses and gradually became very interested in data science.

What made you think that the MScAC program is the best fit for you?

I was admitted to four Master’s programs in Canada, but what swayed me towards the MScAC program were two things: during my undergrad in general engineering, I was exposed to a variety of subjects – mechanics, thermodynamics, math and some computer science. I really enjoyed working at the intersection of so many disciplines, and I didn’t want to lose that variety.

The MScAC program allowed me to choose from courses at two departments – computer science and statistical sciences. I really liked that flexibility. I was also drawn to the eight-month internship. Industry experience was a key factor in my decision.

How did you find your internship?

At an internship expo exclusively held for MScAC students. For three days, the program brings in industry partners, so you’re not on your own looking for an internship. After the expo, most students had several offers to choose from.

What were you working on during your internship?

I worked on a project that applied machine learning to healthcare.

Layer 6 is known for its AI-based research across several fields. One of our partners is a health research lab. I worked on a project with them, clustering people with diabetes.

We are trying to find how many types of diabetes there are. Officially, there is Type 1 and 2, but Type 2 is quite varied. Our goal is to take a step towards personalized health care. If we can identify different types of diabetes, doctors can provide optimal treatment for each type.

Based on the data, we’re also trying to forecast which patients might develop diabetes in the future and which ones are at low risk. We look at all the health data history available.

“The MScAC Data Science Concentration is my preferred internship program to recruit from. The students are exceptionally talented in all three disciplines of computer science, math and machine learning, and their internship research project is supported by a U of T faculty advisor.“ Tomi Poutanen, co-founder, Layer 6

What did a typical day look like for you during your internship?

A typical day would start at the Layer 6 office to catch up with emails, colleagues and sometimes read papers on algorithms. After that, I’d go to the lab to work on the data, alternating between preparing the data, modeling and applying those models offline. At the end of the day, I’d come back to Layer 6 for a debrief to discuss what worked today, what didn’t, and what we should try next.

What was your biggest learning curve during your internship?

I had never worked with such massive data sets before, containing billions of rows of data. No one had really used modern machine learning techniques on this particular data before. My internship project was a first attempt to try to tap into that wealth of information. It was really challenging, but also really exiting, and I learned a lot from it.

What motivates you to do this kind of work?

I really believe in the Tech for Good movement – trying to apply new technologies that improve people’s everyday life. Knowing that my internship project might one day improve the life of people with diabetes is a huge motivator for me.

What are your next steps?

Layer 6 hired me as a machine learning research scientist, so I will continue to work full-time on my project. Working with this incredible data is pretty much a dream come true, but a future dream would be to publish a paper on this project once the research has wrapped up.

Interested in applying to the MScAC Data Science Concentration? Learn more about the program or connect with us at mscac@cs.toronto.edu if you have any questions.

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