My research topic is about changing the structure of (Bayesian) belief networks in an online or incremental fashion. Typical questions I aim to answer include why and when one should introduce new concepts, and how one can unsure that newly introduced variables have meaning (semantics).

During programming I & II (both 3 EC courses), first-year artificial intelligence studentslearn about the basics of programming. My task as course coordinator was to prepare andgive lectures, create weekly programming assignments, create the exams and grade these.In addition, I managed a team of eight teaching assistants who helped students during theweekly practicals.

In this course, undergraduates are introduced to a variety of key topics found in AI, alongwith some of the important algorithms in those fields. Algorithms discussed includedVariable Elimination for Bayesian networks and Q-learning in Reinforcement learning.

Responsible for the prolog assignment where students learn to use a declarative, logical language to represent data structures.

A student tutor helps guide the new undergraduate students in the transition from school to university through monthly or bimonthly meetings, where we provide tips for studying, preparing for exams and dealing with all sorts of issues that might pop up. We also keep track of the performance of students, in case of failing or excellent results, to provide outside motivation to keep improving.

A first year programming course where students learn about recursive programming, dynamic programming and more complex algorithms (sorting, path-finding).