team

I am blessed to work with, supervise and learn from the following individuals.

PhD Students

Adia Lumadjeng

Adia Lumadjeng

High-performance Structural Equation Learning for Finance

Co-supervised with: Ilker Birbil

Focus: structural equation learning, finance, explainable machine learning

Andreas Sauter

Andreas Sauter (VU)

Causal Reinforcement Learning and Discovery

Co-supervised with: Frank van Harmelen (VU), Aske Plaat (Uni. Leiden)

Focus: causality, reinforcement learning, neuro-symbolic AI

Angela van Sprang

Angela van Sprang

Interpretable Time Series Transformers

Co-supervised with: Jelle Zuidema

Focus: concept bottlenecks, transformer interpretability, multimodal consistency

Arco van Breda

Arco van Breda

Mechanistic Control for Tabular Transformers

Co-supervised with: Saba Amiri, Ana Oprescu

Focus: mechanistic interpretability, transformers, neurosymbolic control

Johannes Bendler

Johannes Bendler (VU)

Categorizing neurosymbolic hybrid intelligence systems

Co-supervised with: Frank van Harmelen (VU), Annette ten Teije (VU)

Focus: neurosymbolic systems, category theory

Mayesha Tasnim

Mayesha Tasnim

Multi-Agent Learning for Fair and Transparent School Choice

Co-supervised with: Sennay Ghebreab

Focus: civic AI, matching mechanisms, strategic behavior, responsible AI

Philip Wozny

Philip Wozny (VU)

Multi-Agent Reinforcement Learning for Equitable and Sustainable Tax Policy Design

Co-supervised with: Albert Bomer (VU)

Focus: multi-agent systems, reinforcement learning, taxation, climate policy

Raj Bhalwankar

Raj Bhalwankar

Reasoning in Tabular Foundation Models

Co-supervised with: Pasquale Minervini (University of Edinburgh)

Focus: tabular foundation models, reasoning, representation learning

Satchit Chatterji

Satchit Chatterji

Neurosymbolic AI for Safety and Norms in Multi-Agent Reinforcement Learning

Co-supervised with: Shihan Wang, Giovanni Sileno

Focus: logic, AI safety, game theory, multi-agent reinforcement learning

Alumni

Nicole Orzan

Nicole Orzan (RUG)

Cooperation Under Uncertain Incentive Alignment: A Multi-Agent Reinforcement Learning Perspective

Co-supervised with: Davide Grossi (RUG), Roxana Radulescu (UU)

Focus: multi-agent reinforcement learning, cooperation, uncertain incentive alignment

Renyan Feng

Renyan Feng (Guizhou University)

Knowledge Forgetting in Computation Tree Logic

Co-supervised with: Yisong Wang (Guizhou University, China)

Focus: computation tree logic, knowledge forgetting, logic-based reasoning