The Doctoral Students
University of Klagenfurt
Ashraf Akl
"Multi-Agent Path Finding with Tunnel-Based ASP solving and Deep Reinforcement Learning"
Peyman Eftekari
"Forecast-Enhanced Multi-Agent PPO for Proactive QoS-Aware 5G RAN Orchestration in Intelligent Transportation Systems"
Philipp Fleiß
"Interoperability between ASP and subsymbolic formalisms "
Sobhan Gharanfoli
"Topics in Logical Neural Networks"
Ali Kookani
"Combining symbolic and subsymbolic methods to solve combinatorial optimization problems "
Graz University of Technology
Kevin Innerebner
"Neuro-Symbolic interpretable Recommender Systems (Cognition-inspired, Fuzzy NN, Graph Transformer)"
Emir Mujic
"Causal Reasoning for Explainable, Data-Driven Decision Making"
Liam Plank
"Safety, Explainability and Ethics in Reinforcement Learning"
Yukun Yang
"Episodic Memories Enable Context-Aware Explainable Planning and Problem Solving: A Normative Mode"
Institute of Science and Technology Austria
Max Cairney-Leeming
"Theory of Private Machine Learning"
Andrei Panferov
"Efficient Training of Large Language Models"
Johannes Kepler University Linz
Hannah Eckert
"Integrating Symbolic and Machine Learning Methods for Multi-Sided and Intersectional Fairness in Recommender Systems"
Anamaria Roberta Hartl
"Efficient Adaptation of Large Language Models for Long-Context Reasoning"
Thomas Pammer
"Learning Rule Networks using Mixed Integer Linear Programming"
Peter Pfeiffer
"Reasoning with Skolem Functions (in the context of Boolean functional synthesis)"
Matthias Plasser
"Data-Free Diffusion for Constraint Satisfaction and Planning Problems"
Paulus Seip
"Computational Logic for Circuit Structure Learning"
Vienna University of Business and Economics
Miguel Vázquez Caraballo
"Verified Neuro-Symbolic Knowledge Graph Repair"
Vishal Nair
"Causal Machine learning"
Maduri Hansanie Mudugamuwa Hewage
"Neuro-Symbolic Models with Constraints"
TU Wien
Tomáš Bisták
"Integrating Logical Rule Languages with Sub-Symbolic Techniques"
Bethany Isabella Cissell
"Normative Reasoning and Deliberation toward Ethical and Explainable AI"
Philipp Danzinger
"Neurosymbolic Methods for Combinatorial Optimization"
Davide Di Stefano
"Trustworthy Agentic-AI for Data Curation: A Neurosymbolic Approach to Rule Discovery and Data Understanding"
Bente Gortworst
"Symbolic Representations of Graph Learning for Enhanced Knowledge Graph Reasoning"
Pablo Manrique Merchan
"Formal Verification for Combinatorial Problems"
Alessandro Pesare
"Neuro-Symbolic Reasoning with Foundation Models: Integrating Symbolic Engines for Agentic AI Reasoning"
Xiangtao Wang
"Neuroscience-Inspired AI based on Predictive Coding"
