Current Students (PhD Program in Data Science)
Multimodal computer vision system for describing and identifying old fruit varieties
Mathematical Modeling of Microsatellite Changes in Colorectal Cancer Somatic Mutagenesis
AI for colorectal cancer: Towards the improved consensus molecular subtype classification and interpretability
Analysis of molecular basis for colorectal cancer
Deep Brain Vessel Profiler: Enhancing Brain Angiograms for Personalized Stroke Management
Supervisors:
Prof. Dr. Björn Menze (UZH)
Prof. Dr. Sven Hirsch (ZHAW)
Robust Deep Learning for Industrial Applications
Advanced deep learning-based computer vision in real-world applications
Critical Phenomena in Financial Markets and Social Networks
Visual Interestingness - All images are equal, but some images are more equal than others
Accelerated lifetime testing and modelling of perovskite solar cells
Goal-Driven Deep Learning in Real-World Applications
Principled deep learning approaches for document recognition in business and engineering processes
Modelling the Management of Unruptured Intracranial Aneurysms and Subarachnoid Haemorrhage
Deep Learning-Based Real-Time EEG Monitoring for Clinical Interventions
Supervisors:
Prof. Dr. Reto Huber (UZH)
Prof. Dr. Sven Hirsch (ZHAW)
Medical Image Analysis for Digital Twinning in Stroke Research
Supervisors:
Prof. Dr. Björn Menze (UZH)
Prof. Dr. Sven Hirsch (ZHAW)
Computational Phylogenetics with Applications to Virus Evolution
Phylogenetic Inference of Insertions and Deletions in Viral Genomes
Temporal Multimodal Explainable AI for Enhanced Diagnosis and Understanding of Multiple Chronic Diseases
Digitalizing the fight against superbugs: using data mining to track antibiotic resistance for travelers to the global South
Towards Reliable Conversational AI for Personalized and Trustworthy Data Exploration in Healthcare
Task-Conditional Visual Interestingness
Current Students (previous PhD Network in Data Science)
Estimating Dark Rates of Collusion
Supervisors:
Prof. Dr. Sven Seuken (UZH)
Dr. Andrea Günster (ZHAW)
Real-time dynamic modelling of Human-Robot Collaboration environments and human-aware motion planning
Socially Acceptable AI
Machine Learning Driven Cognitive Techniques for Trustworthy and Secure 5G/B5G
Supervisors:
Prof. Dr. Burkhard Stiller (UZH)
Dr. Gürkan Gür (ZHAW)
Explaining and Predicting Spread in Networks: A Time-varying Multilayer ML Approach
Algorithmic Fairness
Frequentist Estimation of Evolutionary History of Sequences with Substitutions & Indels
Supervisors:
Prof. Dr. Daniel Croll (UNINE)
Prof. Dr. Maria Anisimova
Alumni
Evaluation of Lifelong Machine Learning for Dialogue Systems
Supervisors:
Prof. Dr. Martin Volk (UZH)
Prof. Dr. Mark Cieliebak (ZHAW)
Data Distribution and Exploitation in a Global Microservice Artefact Observatory
Deep learning approaches in medical image analysis
Supervisors:
Prof. Dr. Torsten Hothorn (UZH)
Prof. Dr. Beate Sick (ZHAW)
Shape-based Analysis of Intracranial Aneurysms
Realistic Evolutionary Models for Phylogenetic-Guided Analyses
Multimodal Information Retrieval
Progressive Multiple Sequence Alignment with Indel Evolution
Applying machine learning to carbon markets: Building trust for a net-zero emissions world
Deep and robust distributional regression with applications to intervention planning in acute ischemic stroke
Supervisors:
Prof. Dr. Torsten Hothorn (UZH)
Prof. Dr. Beate Sick (ZHAW)
Prof. Dr. Helmut Grabner (ZHAW)
Trans-omic approach to colorectal cancer: an integrative computational and clinical perspective
Prediction of the spin system of small molecules from high-resolution liquid NMR spectra employing machine learning techniques
Machine Learning for Perovskite Device Simulation
Decoding Progression of the Intracranial Aneurysm Disease by Applying Probabilistic Graphical and Machine Learning Models