17 May Dieter Stoker – Developer introductory Machine Learning course
When you meet Dieter, you might be overwhelmed by the sheer volume of words he can rapidly throw your way. Dieter’s enthusiasm immediately shone through as he started talking about his teaching role: “I’ve recently been hired to spruce up the BiBC Master’s programme with an extra Machine Learning course, focussing on hands-on practice. This course is scheduled to prepare BiBC students for Jeroen de Ridder’s excellent high-level course, so that Jeroen can focus (even) more on high-level understanding. As a student, I’ve assisted the first edition of the BiBC Essentials course, Advanced R, Biological Modelling, and Computational Biology.”
While Dieter catches his breath, I quickly ask him what makes him the right person for the job. “Since I am a learning machine, a.k.a. The Midterminator, it is only natural that I’ve been put on the case to build this course. I jest, and my abysmal performance in the first-ever student-organised BiBC pubquiz clearly shows that I have a lot left to learn. About logos of pharmaceutical companies, for instance, and about Jeroen de Ridder’s favorite music to play during breaks. Luckily, Jeroen has deigned me a worthy vessel upon whom to impart some hard-earned Machine Learning knowledge and teaching prowess, so together we will make sure that the two Machine Learning courses fit together nicely. We try to teach all there is to learn about Machine Learning in Biology and/or electro swing. Insofar as it fits into 4 weeks of cumulative course time, that is. All of this to make sure the next generation’s brightest bioinformatic minds are well-equipped to pierce through the haze of buzzwords and use ML for good.”
Machine Learning experience
Could you tell us a bit more about your own relevant Machine Learning experience? What led you to this position? “Why was I chosen to make this course? I’d like to think it is because of my flowing locks of shiny brown hair and chiseled chin, but that’s probably wishful thinking on my part. Instead, it might be because I did both my Master’s projects in Machine Learning. In one I built a Naïve Bayesian classifier to predict genes possibly involved in the Major Histocompatibility Complex pathway, collaborating with John van Dam and Can Kesmir. In the other I worked on predicting propensity for 3D DNA contacts, i.e. DNA loop formation, using chromatin marks, together with Jeroen de Ridder and Amin Allahyar, the dazzling duo. In other words: I now know precisely how vanishingly little I know about the vast field of Machine Learning, and am hence perfectly prepared to teach others. So I’ve been given to understand.”
What do you like to do besides teaching? “When I’m not writing long-winded, slightly inane statements about my work, I enjoy reading Terry Pratchett and non-fiction and I sing in a choir. I also like doling out homemade slices of cake whenever the opportunity presents itself, sharing e-book recommendations preferably with those far too busy to read them, learning about hobby projects of colleagues, and of course mastering the skill of procrastination. I must be approaching that 10,000 hour mark pretty soon.
Lastly, if anyone in the community has identified a major lack in Machine Learning knowledge in students that absolutely must be fixed in this new introductory Machine Learning course, please let me know your suggestions. You’ll earn major 3Blue1Brownie points in my book. Thanks in advance, and thanks for reading!”