Senior Data Scientist
The coolest things I've done in my career are:
I was lucky to work on deep neural networks before they got really hot. Back in 2005, I made an NN-based image orientation system that Epson’s scanners still use. I am the first author of 3 US patents and published 8 papers. I won the Best Paper Award at the Canadian Conference on Artificial Intelligence for one of my papers. I enjoy teaching, and won the Computer Science Student Union Award for Excellence in Teaching for my Introduction to Neural Networks and Machine Learning class.
If I could have a super power it would be:
Keeping my coffee consumption to one cup a day. This requires superpowers.
I'm a "closet" fan of:
Statistical inference with small samples! Big data is what works most of the time, but there is a beauty to being able to draw conclusions with just a little bit of data and a lot of math.
The nerdiest thing I do in my spare time is:
Watch Star Trek re-runs.
Three things still on my bucket list are:
Get a dog
Make an AI that works better than a doctor
Go on a road trip all the way across Europe (I haven’t figured out either when I can take a vacation or the dog-sitting arrangements)
My past experience includes:
I hold a B.Sc. in Math, Computer Science, and Statistics, an M.Sc. in Computer Science and an M.Sc. in Statistics, all from the University of Toronto. I worked on computer vision and machine learning algorithm development at Epson Canada and at Inria (the French Institute for Research in Computer Science) in Grenoble, France. I occasionally take on data science consulting clients. I taught machine learning, programming, and statistics at the University of Toronto since 2009.
My recent insights and projects include: