It’s now 2018: a brand new year starts ! Like most people, I’d like to take time to think back on 2017 and to decide on new year’s resolutions (which I’ll try not to forget too quickly).
My greatest success in 2017 was that I managed to turn around my teaching: in 2016, I taught for the first time (an introductory course covering probability and statistics for engineers) and I didn’t went great, as I have talked about in earlier posts. This year, the course was very well received by my students, and I felt great about my lecturing. I hope I can keep up the good work and have my lecturing be as good next year!
However, since I’m also very critical, I’m still not completly satisfied with my teaching material: this is something I would like to improve for next year (and I’m looking forward to the summer, during which I will actually have the time to work on it). My biggest worry is that the current material is a bit dry: it involves very little doing or discovering by the students. As a consequence, I’m concerned about students feeling that this is too scholarly and not relevant to real-life. I’m thus going to try to figure out how to get them to practice more next year, probably by giving out programming exercises.
In 2017, I also had some great ideas for my research (which I’ll try to write about in future posts). More and more, I’m drawn towards deep learning (exactly like a moth to a flame: let’s hope for my sake that this story ends up better for me): I’m looking forward to trying to get some real research on this fascinating topic. I also hope to be able to dive into the exciting world of Functional Data Analysis, in which you wonder how statistics would proceed if our observations were random functions: instead of vectors. I’m still not completely sure how I feel about that: I oscillate between the intuition that this is a better approach and the reality that this leads to very counter-intuitive properties.
Finally, 2017 was the year I first supervised a student on a long-term project: I supervised a Master student of EPFL on his final project. I’m amazed at how great this turned out. My student was very sharp and worked super-hard. I’m super happy about the results he got and we’ll be submitting them to NIPS next year (how many master’s project end up there??). I’m just a little bit sad because he’s leaving academia for a more normal job involving statistics. I’m sure he’ll do great work there and I wish him the best on his way.
I look forward to 2018. I’m confident that this will be a great year for me: I’ve got tons of projects for my professional life, both for research and for teaching. My only worry is whether I’ll have the time to do all of them ! This leads me to my only new year’s resolution: trying to be more efficient with my time !
Happy new year ! I wish you all the best.