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City Data Science Institute

Neural-Symbolic Learning, ACAI Summer School on Statistical Relational Artificial Intelligence.

Neurosymbolic AI: The 3rd Wave

Artur Garcez is Professor of Computer Science at City, University of London. He holds a Ph.D. in Computing (2000) from Imperial College London. He is a Fellow of the British Computer Society (FBCS), member of the ACM, AAAI, IEEE, CGCA, and partner at Cognitive Intelligence, London, and Performance Systems, Rio de Janeiro.

Garcez is Director of the Data Science Institute, and president of the Steering Committee of the Neural-Symbolic Learning and Reasoning Association, London. He was the founding course director of City's MSc in Data Science programme.

Garcez has an established track record of research in Machine Learning, Neural Computation and Artificial Intelligence. He has co-authored two books: Neural-Symbolic Cognitive Reasoning, with Lamb and Gabbay (Springer 2009), and Neural-Symbolic Learning Systems, with Broda and Gabbay (Springer 2002). Garcez has published at Theoretical Computer Science, Neural Computation, Machine Learning, Journal of Logic and Computation, Artificial Intelligence journal, Journal of Applied Logic, Behavioral & Brain Sciences, IEEE Transactions on Neural Networks and Learning Systems, and Studia Logica. He has consistently published at the flagship Artificial Intelligence and Neural Computation conferences AAAI, NeurIPS, IJCAI, AAMAS, IJCNN, ECAI.

Garcez is associate editor of IEEE Transactions in Neural Networks and Learning Systems, editor of the Machine Learning journal, Special Track on Learning and Reasoning, area scientific editor of the Journal of Applied Logics (Logics and Neural Networks), editor of the Journal of Logic and Computation (Reasoning and Learning, with L. Valiant), and associate editor of the Journal of AI Research (JAIR), special track on deep learning and symbolic reasoning. Garcez was a founding co-chair of the International Workshop on Neural-Symbolic Learning and Reasoning (NeSy), held yearly since 2005 and now part of the International Joint Conference on Learning and Reasoning. Garcez was co-organiser of Dagstuhl seminar 14381 on Neural-Symbolic Learning and Reasoning, September 2014, and Dagstuhl seminar 17192 on Human-like Neural-Symbolic Computing, May 2017.

Garcez has acted as reviewer for most of the leading international journals on Logic, Cognitive Science, Neural Computation and Artificial Intelligence, including IEEE Transactions on Neural Networks and Learning Systems, Artificial Intelligence, Machine Learning, Journal of Machine Learning Research, Cognitive Systems Research, AI Communications, Cognitive Science, Neurocomputing, Information and Computation. He has guest-edited three journal special issues, and co-edited two research monographs. He has served on the Senior Programme Committee or Organizing Committee of a large number of international conferences and workshops, including IJCAI, NeurIPS, AAAI, AAMAS, ECAI, ICANN, ASE, HLAI and IJCNN.

Garcez was awarded a two-year Nuffield foundation research grant in the area of neural-symbolic integration (2002-2004). He was Principal Investigator for the EU-funded research project BioGrid (2003-2004) and industry-funded projects RoboCup Physical Visualization League (2007) and Dynamic Fraud Prevention (2009). He was co-investigator in the EU-funded research project Genestream (2003), was awarded a Daiwa Foundation Grant (2006), and has been consistently awarded conference travel grants by The Royal Society (2002, 2003, 2004, 2005, 2007, 2010). Garcez was Principal Investigator for the EPSRC/ESRC/Innovate UK project EP/M50712X/1 Advancing Consumer Protection through Machine Learning (with BetBuddy Ltd.), and the EPSRC/Innovate UK project EP/M507064/1 FareViz: On the Design of Real-Time Data Exploration Tools. Garcez is currently a member of the EPSRC Research Network+ on Human-like Computing (2018-2023), Principal or Co-Investigator in the projects: Smart Big Data Platform for Evidence-based Personalised Support for Healthy and Independent Living at Home (EU H2020, 2019-2023), Yuvoh Investment Analytics Platform (Innovate UK, 2020-2021), and industry-funded projects Deep Learning for Compliance and Fraud Prevention (Kindred plc, 2018-2021) and Safety Validation and Explanation of Autonomous Vehicle Systems (Intel, 2019-2022).

Selected Publications (complete list available here; google scholar profile here):

Contact details
Artur d'Avila Garcez, FBCS
Professor of Computer Science
Department of Computer Science
City, University of London, EC1V 0HB, UK
Tel: + 44 (0)20 7040 8344
Email: a.garcez@city.ac.uk
URL: http://staff.city.ac.uk/~aag/
Twitter: @AvilaGarcez