In January a collaborative project on improving machine learning prediction accuracy for quantification in non-target screening started between our group and the group of Meelis Kull at the Institute of Computer Science at the University of Tartu kicked off. In the summertime, two PhD students, Louise Malm and Wei Chieh (Harry) Wang joined the project. Harry has already spent a few months in Tartu to expand his knowledge and gain new experiences in machine learning. In addition, Ida Rahu, an MSc student of data science at UT, joined another collaborative project on expanding MS2Tox, a machine learning model to predict toxicity of chemicals detected in nontarget screening (see also GitHub repo).
With all that going on and having the whole Baltic see between the two universities, we felt like a pre-holiday get-together seminar would be a good juice. Mõeldud, tehtud, so we met on Monday afternoon at the almost brand-new Delta building to listen to the presentations of Louise, Harry, and Ida and to discuss the problems and plans for 2023.
Louise Malm reflects back on the day: On Monday, I finally got to meet with my co-supervisor Meelis Kull in person and discuss the PhD project. It was a really nice discussion, and especially beneficial to get inputs from the data science point of view. It was also interesting to hear the other presentations (from Harry’s and Ida’s projects) and the following discussions. Usually, our meetings and seminars are very centered around analytical chemistry, and it was educational to step out of that bubble and understand and explain what may not be clear to people from other fields.