TU Delft students interested in statistical machine learning and dependence modeling might feel free to contact me, sending a recent transcript and an indication of their interests.
I have (co)supervised several student theses and projects in statistics and machine learning:
- L. Xue: Comparison of Quantile Regression Forest and D-vine Copula Based Quantile Regression
- K.W. Ho: EM Algorithm and its Extensions for Gaussian and Vine Copula Mixture Models
- Z. Li: Illustration of variable selection methods for clustering based on Gaussian mixture and vine copula mixture models using Alzheimer Data
- F. Kössinger: Vine Copula and Mixture Model Based Analysis of the Sachs Data
- E. Allwright: Development of an Enhanced Additive Logistic Regression Model for European Thunderstorms and their Associated Hazards
- C. Wang, M. Rosenzweig, N. Mumladze, T. Kuznetsova, T. Decker: Scalable Statistics with Large Datasets
- P. Hausenblas, N. Pfeiffer, M. Hamdi, C. Emezue: Building and Applying an Ontology-Based Medical Graph Database