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