People | Finesse Lab

Lab Lead

Erman Acar

Tenured Assistant Professor, University of Amsterdam

Affiliation: Institute for Logic, Language and Computation and Informatics Institute

Focus: Neurosymbolic AI, causality, multiagent systems, and explainability for socially consequential financial decision-making

Finesse Lab is part of SIAS at the University of Amsterdam, with strong ties to ILLC and AI4FinTech.

PhD Student

Adia Lumadjeng

High-performance Structural Equation Learning for Finance

Co-supervised with: Ilker Birbil

Focus: Structural equation learning, finance, and explainable machine learning

PhD Student

Andreas Sauter (VU)

Causal Reinforcement Learning and Discovery

Co-supervised with: Frank van Harmelen (VU), Aske Plaat (University of Leiden)

Focus: Causality, reinforcement learning, and neurosymbolic AI

PhD Student

Angela van Sprang

Interpretable Time Series Transformers

Co-supervised with: Jelle Zuidema

Focus: Concept bottlenecks, transformer interpretability, and multimodal consistency

PhD Student

Arco van Breda

Mechanistic Control for Tabular Transformers

Co-supervised with: Saba Amiri, Ana Oprescu

Focus: Mechanistic interpretability, transformers, and neurosymbolic control

PhD Student

Johannes Bendler (VU)

Categorizing Neurosymbolic Hybrid Intelligence Systems

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

Focus: Neurosymbolic systems and category theory

PhD Student

Mayesha Tasnim

Multi-Agent Learning for Fair and Transparent School Choice

Co-supervised with: Sennay Ghebreab

Focus: Civic AI, matching mechanisms, strategic behavior, and responsible AI

PhD Student

Philip Wozny (VU)

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

Co-supervised with: Albert Bomer (VU)

Focus: Multiagent systems, reinforcement learning, taxation, and climate policy

PhD Student

Raj Bhalwankar

Reasoning in Tabular Foundation Models

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

Focus: Tabular foundation models, reasoning, and representation learning

PhD Student

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, and multiagent reinforcement learning