Current Students (PhD Program in Data Science)
Visual Interestingness - All images are equal, but some images are more equal than others
Advanced deep learning-based computer vision in real-world applications
Decoding Progression of the Intracranial Aneurysm Disease by Applying Probabilistic Graphical and Machine Learning Models
Indel-Aware Parsimony Methods for Phylogenetic Inferences
Analysis of molecular basis for colorectal cancer
AI for colorectal cancer: Towards the improved consensus molecular subtype classification and interpretability
Deep Brain Vessel Profiler: Enhancing Brain Angiograms for Personalized Stroke Management
Supervisors:
Prof. Dr. Björn Menze (UZH)
Prof. Dr. Sven Hirsch (ZHAW)
Critical Phenomena in Financial Markets and Social Networks
Prediction of the spin system of small molecules from high-resolution liquid NMR spectra employing machine learning techniques
Trans-omic approach to colorectal cancer: an integrative computational and clinical perspective
Multimodal computer vision system for describing and identifying old fruit varieties
Mathematical Modeling of Microsatellite Changes in Colorectal Cancer Somatic Mutagenesis
Robust Deep Learning for Industrial Applications
Machine Learning for Perovskite Device Simulation
Current Students (previous PhD Network in Data Science)
Algorithmic Fairness
Estimating Dark Rates of Collusion
Supervisors:
Prof. Dr. Sven Seuken (UZH)
Dr. Andrea Günster (ZHAW)
Improving adherence to treatment by closing the loop from one physician–patient consultation to the next
Data Distribution and Exploitation in a Global Microservice Artefact Observatory
Socially Acceptable AI
Frequentist Estimation of Evolutionary History of Sequences with Substitutions & Indels
Supervisors:
Prof. Dr. Daniel Croll (UNINE)
Prof. Dr. Maria Anisimova
Deep and robust distributional regression with applications to intervention planning in acute ischemic stroke
Applying machine learning to carbon markets: Building trust for a net-zero emissions world
Real-time dynamic modelling of Human-Robot Collaboration environments and human-aware motion planning
Explaining and Predicting Spread in Networks: A Time-varying Multilayer ML Approach
Machine Learning Driven Cognitive Techniques for Trustworthy and Secure 5G/B5G
Supervisors:
Prof. Dr. Burkhard Stiller (UZH)
Dr. Gürkan Gür (ZHAW)
Alumni
Evaluation of Lifelong Machine Learning for Dialogue Systems
Realistic Evolutionary Models for Phylogenetic-Guided Analyses
Multimodal Information Retrieval
Deep learning approaches in medical image analysis
Shape-based Analysis of Intracranial Aneurysms
Progressive Multiple Sequence Alignment with Indel Evolution