Fair, Effective, and Sustainable Talent Management using Conditional Network Embedding

Formalizing Subjective Interestingness in Exploratory Data Mining

VIrtual GuardIan AngeLs for the post-truth Information Age

Automating Data Science: the Next Frontiers

Accelerating Progress in Network Representation Learning: Systematic Evaluations and New Approaches

AI for Detecting and Mitigating Triggers of Cognitive Biases and Heuristics in Media Content

Challenges in E-Recruitment Systems: Algorithms to Restore Balance in Competitive Markets

Conversational AI Explanation Systems

Doctoral project Robin Vandaele

Fairness and Transparancy of AI Systems

Innovative approaches to tackle the information chaos using AI

Methods for Detecting Triggers of Cognitive Biases and Heuristics in Textual Content

Mining Subjectively Interesting Patterns in Rich Data

Modeling Weighted and Temporal Graphs: Methods and Evaluation

Network and Knowledge Graph Embedding: Theory, Methods, and Applications

Opinion Dynamics and Link Prediction in Networks: Models, Data Efficiency, and Robustness

Principled Data Mining on Graphs: Of Disentangled Nodes and Subjective Patterns

The Communication of Fairness of AI Models and Predictions

Doctoral project Edith Heiter

Doctoral project Valerio Lorenzoni

Inductive Methods for Dimensionality Reduction and Visualization of Large & Complex Data

Leveraging comprehensive cancer systems genetic data to uncover the modus operandi of driver mutations

Pattern Mining for Understanding Learned Representations

The activation of inactive people: studying thresholds and breakthroughs

Towards Audio Context-Aware Hearing Augmentation

Towards Deep Localisation and Separation with Ad Hoc Distributed Microphone Arrays

Unifying Attribution-Based Explanation Methods in Machine Learning

Advancing Language Models with Human Social Reasoning Skills for Socially-Aware Decision-Making

A network embedding approach to a fair, efficient and fulfilling job market.

BOF-ZAP professorship in foundations and applications of exploratory data mining

Conditional Knowledge Graph Embedding

Data Mining without Spilling the Beans: Preserving more than Privacy Alone

Digital innovation for man and society

Exploring Data: Theoretical Foundations and Applications to Web, Multimedia, and Omics Data

Personalised, interactive, and visual exploratory mining of patterns in complex data

Run-time adaptive hierarchical neural architectures for representation learning in modular sensor networks

The impact of content moderation on the ideological diversity of social media

Interactive embedding of high-dimensional data with shape templates

The activation of inactive people: studying thresholds and breakthroughs using AI techniques

BOF-ZAP professorship in foundations and applications of exploratory data mining