Teaching & Supervision
Several years of lecturing, tutoring and supervising in computational science — the same instinct that shapes how I consult.
MSc Computational Science (joint degree) · University of Amsterdam
Ran tutorials and supported teaching for the master's introduction to computational science — modelling, simulation and scientific computing — for incoming students.
BSc Informatica · University of Amsterdam
Computer labs, tutorials and the practical project for a bachelor's data-analysis course, teaching students to work with real data in Python.
MSc Computational Science (joint degree) · University of Amsterdam
Co-ran the master's research seminar series, guiding students through reading, presenting and discussing current computational-science research.
MSc Information Studies · University of Amsterdam
Weekly tutorials and assignment feedback for system-dynamics modelling, working primarily with Vensim and AnyLogic.
BSc Science / Mathematics · Trinity College Dublin
Lab tutorials for a first-year statistics course (teaching R) and tutorials for an introductory probability module for mathematics students.
Master's thesis projects I supervised day-to-day at the University of Amsterdam.
“Survival of the Fittest Structure: Evolutionary Learning of Synergistic Dependencies”
MSc Computational Science
Introduced a synergy-aware evolutionary Bayesian-network structure learner using interaction-based triplet screening to recover higher-order, XOR-like synergistic dependencies.
Details ↗“Predictive Modeling of Symptom Reports and Changes in Functional Outcomes in Elderly Suffering from Multi-Morbidity: Leveraging Longitudinal Symptom Data”
MSc Information Studies (Data Science)
Used the Precipitating Events Project cohort of 754 adults aged 70+ to predict symptom reports and changes in functional outcomes in elderly patients with multimorbidity, comparing random forests, multi-output classifiers and regression on longitudinal symptom data.
Details ↗“Predicting the Accuracy of Dynamic Bayesian Network Structure Learning Algorithms”
MSc Computational Science
Benchmarked Bayesian-network structure-learning algorithms on synthetic causal data and predicted their accuracy from dataset and structure properties, aimed at medical causal discovery.
Details ↗BSc Informatica
BSc Informatica
Master's and bachelor's theses where I acted as second supervisor or assessor at the University of Amsterdam.