I recently graduated in biomedical engineering from EPFL, Switzerland. I spent my last year as an exchange student at UBC, Canada and decided to shift to machine learning there. During and after my studies I have worked on:
A mutation ranking algorithm for mono-genic conditions. This made me switch to machine learning .
Predicting room and building occupancies from wi-fi data to make HVAC control systems more efficient.
I’m currently working as a Data Scientist Trainee in Grab’s User Trust Team. Grab is the leading ride-hailing startup in Asia-Pacific, which explains why you’ve never heard of it. I’m working on NLP to understand users review. It’s a lot of fun, but challenging as reviews can be in Thai, Malay, Indonesian, …
Side Note: Thai doesn’t use whitespacestoseparatewords ! Not so simple for preprocessing .
In my free-time I like to run, play any sports (with a biais towards basketball), drink a beer or smoke a cigar with friends, watch MOOCs and learn about new Machine Learning stuff.
I find most of the ML domains fascinating, but if I had to chose, I would say Natural Language Processing and sample-efficient methods. By the latter I mean topics such as:
PS: Check out my resume for more information.
PSx2: This picture was taken a loooooong time ago, but I thought it was appropriate for this page .