people

Members of the AMS Network


/profiles/janna.jpeg

Prof. Dr. Janna Hastings

University of Zurich

Assistant Professor for Medical Knowledge and Decision Support at the Institute for Implementation Science in Health Care, Medical Faculty, University of Zurich, and a member of the board of directors of the School of Medicine at the University of St.Gallen.

Email
Google Scholar
Homepage


/profiles/ernesto.jpeg

Dr. Ernesto Jiménez-Ruiz

City St George's, University of London

Senior Lecturer in Artificial Intelligence and Director of Research at City St George’s, University of London affiliated to the Research Center for Artificial Intelligence.

Email
Google Scholar
Homepage


/profiles/heiko.jpeg

Prof. Heiko Paulheim

University of Mannheim, Germany

A theme leader in the Data and Web Science Group with a focus on the use of Web-scale knowledge graphs in combination with machine learning techniques.

His group is currently working on a project to integrate indication data from various sources in a knowledge graph and apply machine learning methods to improve the early stage detection of Diabetes.

Email
Google Scholar
Homepage


/profiles/alessandra.jpeg

Prof. Alessandra Mileo

Dublin City University

Alessandra is an Associate Professor and the Principal Investigator at the Insight SFI Research Centre (RC) for Data Analytics at Dublin City University

Email
Google Scholar
Homepage


/profiles/mehwish.jpeg

Associate Prof. Mehwish Alam

Télécom Paris, Institut Polytechnique de Paris

Mehwish is an Associate Professor in the Data, Intelligence and Graphs (DIG) group, with extensive experience on fundamental issues raised in databases, knowledge management, graph mining and artificial intelligence.

Email
Google Scholar
Homepage


/profiles/pascal.jpeg

Prof. Dr. Pascal Hitzler

Kansas State University

Senior Lecturer in Artificial Intelligence and Director of Research at City St George’s, University of London affiliated to the Research Center for Artificial Intelligence.

Email
Google Scholar
Homepage


/profiles/michael.jpeg

Michael Cochez

Vrije Universiteit Amsterdam, Netherlands

Michael is an Assistant Professor in the Learning and Reasoning (L&R) group, a group with a special focus on the ways machine learning, symbolic knowledge and formal reasoning can interact to enhance one another.

In addition to a strong technical position in the field, the L&R group also brings expertise in the application of neurosymbolic AI techniques within the medical domain, where explainability was one of the core components.

Email
Google Scholar
Homepage


/profiles/catia.jpeg

Catia Pesquita

University of Lisbon, Portugal

Explainable Artificial Intelligence applied to Health and Biomedical Informatics.

Email
Google Scholar
Homepage


/profiles/eleonora.jpeg

Eleonora Giunchiglia

TU Wien, Austria

Deep Learning with Logical Constraints.

Email
Google Scholar


/profiles/dagmar.jpeg

Dagmar Gromann

University of Vienna, Austria

Bias in Large language Models and AI. Explainable AI.

Email
Google Scholar
Homepage


/profiles/son.jpeg

Son N. Tran

Deakin University, Australia

Interpretability in AI.

Email
Google Scholar


/profiles/pierre.jpeg

Pierre Levy

University of Montreal, Canada

AI for Collective Intelligence.

Email
Google Scholar
Homepage


/profiles/raghava.jpeg

Raghava Mutharaju

IIIT-Delhi, India

Neurosymbolic AI for Biomedical Relation Extraction.

Email
Google Scholar
Homepage


/profiles/egor.jpeg

Prof. Egor V. Kostylev

University of Oslo, Norway

Logical expressiveness of Graph Neural Networks.

Email
Google Scholar
Homepage


/profiles/jiaoyan.jpeg

Jiaoyan Chen

University of Manchester, UK

Large language models and Knowledge graphs. Integration of biomedical ontologies.

Email
Google Scholar
Homepage


/profiles/artur.jpeg

Prof. Artur d'Avila Garcez

City St. Georges, University of London, UK

President of the Neural-Symbolic Learning and Reasoning Association, extensive experience in applying neurosymbolic AI in a range of domains, including medical imaging.

Email
Google Scholar
Homepage


/profiles/claudia.jpeg

Associate Prof. Claudia d'Amato

University of Bari, Italy

Deep Learning and Knowledge Graphs.

Email
Google Scholar
Homepage


/profiles/wen.jpeg

Wen Zhang

Zhejiang University, China

Research Knowledge Graph; Representation Learning; Artificial Intelligence

Email
Google Scholar
Homepage


/profiles/ilaria.jpeg

Ilaria Tiddi

Vrije Universiteit Amsterdam, Netherlands

Combination of machine learning, semantic technologies, open data and cognitive theories.

Email
Google Scholar
Homepage


/profiles/natalia.jpeg

Natalia Díaz Rodríguez

University of Granada, Spain

Explainable AI, Responsible, Trustworthy AI and AI for social good. Study of gender and sex bias in health related data.

Email
Google Scholar
Homepage


/profiles/jack.jpeg

Jack Gallifant

Harward University

AI researcher and engineer focused on robustness, interpretability, and agentic systems. Former NHS physician now building and evaluating AI for healthcare and beyond.

Email
Google Scholar
Homepage


/profiles/franklyn.jpeg

Franklyn Arron Howe

St George's, London, UK

Professor of Magnetic Resonance Imaging

Email
Google Scholar
Homepage


/profiles/valentina.jpeg

Valentina Tamma

University of Liverpool

A Senior Lecturer at the Department of Computer Science, University of Liverpool. My research interests lie in the area of Ontologies in open and distributed environments, such as Multi-Agent systems, Semantic Web and Grid environments.

Email
Google Scholar
Homepage


/profiles/lia.jpeg

Lia Morra

Politecnico di Torino

Assistant Professor at Politecnico di Torino

Email
Google Scholar
Homepage


/profiles/rita.jpeg

Rita Sousa

University of Mannheim, Germany

Email
Google Scholar


/profiles/sven.jpg

Sven Hertling

University of Mannheim, Germany

Email
Google Scholar