Sequential Uncertainty Monitoring and Interpretability (SUMI) Lab
Sterre Lutz
PhD Researcher
Combining formal methods with machine learning for guaranteed deployment of black-box systems.
Open Position!
PhD Researcher on mathematical methods in computer science for reliable automation
Johannes Koch
PhD Researcher
Improving genetic programming for explainable AI in collaboration with CWI and LUMC.
Daniël Vos
Postdoctoral Researcher
Designing algorithms for safe, interpretable and high-performing control of AI systems.
Alumni
Erik Sennema
MSc, 2023
"Elastic gradient boosting decision trees under
limited labels by sequential epistemic uncertainty quantification:
Elastic CatBoost Uncertainty (eCBU)" with Yury Zhauniarovich and Eduardo Barbaro from ING.
Daan Hofman
MSc, 2023
"VoBERT: Unstable Log Sequence Anomaly Detection" with Yury Zhauniarovich and Eduardo Barbaro from ING.
Daniël van Gelder
MSc, 2022
"Real-Time Passenger Load Estimation using In-Vehicle Data" with Siemens and Oded Cats.
Rens Oude Elferink
MSc, 2024
"Identifying how drivers adapt to automated vehicles by monitoring neural networks" with Luciano Cavalcante Siebert.
Elwin Duinkerken
MSc, 2023
"Robust Shunting in a Dynamic Environment: Deriving Proactive Schedules from a Reactive Policy" with the Dutch Railways.
Cas van Rijn
MSc, 2023
"Combining Multi-Objective Planning with Reinforcement Learning to Solve Complex Tasks in Environments with Sparse Rewards."
Parand Alizadeh Alamdari
MSc, 2020
"Formal Methods with a Touch of Magic."