Professor Felipe Meneguzzi
I am a researcher on automated planning, goal and plan recognition, multiagent systems, BDI agents, and machine learning. I currently hold a Chair of Computing Science at the University of Aberdeen. I am a Senior Member of the ACM and of AAAI. Before my current position, I was a Professor of AI at the Pontifical Catholic University of Rio Grande do Sul in Brazil, and worked as a Project Scientist in Multiagent Systems at the Robotics Institute of Carnegie Mellon University after completing a Postdoctoral Fellowship at the same university. I obtained my PhD degree at King's College London, with a thesis on Extending agent languages for multiagent domains under the supervision of Professor Michael Luck and co-supervised by Professor Andrew Jones. Prior to my full-time academic career, I worked in the industry as a contractor for Hewlett-Packard Brazil, and worked on a variety of projects with some very interesting people.
For further information, visit my personal website.
- PhD Artificial Intelligence2009 - King's College London
- Executive Council of the AAAI
- Special Committee on AI for the Brazilian Computer Society
- Guest Researcher at the Pontifical Catholic University of Rio Grande do Sul
Prizes and Awards
- Best SPC member award from AAMAS 2021;
- 1st place at the International Planning Competition (IPC) in 2020;
- Distinguished Visiting Fellow award from the Scottish Informatics and Computer Science Alliance (SICSA);
- Best Student paper at IJCNN 2017: An Application to Support Visually-Impaired People through Deep Convolutional Neural Networks;
- Visionary workshop paper at AAMAS 2017: Norm Conflict Identification Using Deep Learning;
- Google Research Award for Latin America in 2016 as well as in 2019;
- 1st place at the 2016 Multi-Agent Programming Contest;
- 2nd place at the 2016 Predictive Analytics in Mental Health Competition (PAC); and
- Runner up to the Microsoft Research Faculty Fellowship in 2013.
My overall research area is Artificial Intelligence and my research spans the areas of Automated Planning, Autonomous Agents and Applications of Machine Learning. The main goal of my research is to develop practical reasoning mechanisms as a means to both refine the capabilities of autonomous agents and to understand reasoning in general. To accomplish this objective, I work on integrating data-driven and symbolic techniques for reasoning and decision-making while maintaining a low complexity for the description formalisms, helping to achieve explainability for human users.
I am currently accepting PhDs in Computing Science.
Please get in touch if you would like to discuss your research ideas further.
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Robust Neuro-Symbolic Goal and Plan RecognitionContributions to Conferences: Papers
Resilience, reliability, and coordination in autonomous multi-agent systemsAI Communications, vol. 35, no. 4, pp. 339-356Contributions to Journals: Articles
HyperTensioN and Total-order Forward Decomposition optimizationsWorking Papers: Preprint Papers
Goal Recognition as Reinforcement LearningChapters in Books, Reports and Conference Proceedings: Conference Proceedings
Editorial: Advances in Goal, Plan and Activity RecognitionFrontiers in Artificial Intelligence, vol. 5, 861669Contributions to Journals: Editorials
Detecting Logical Relation In Contract ClausesWorking Papers: Preprint Papers
Visual Explanation for Identification of the Brain Bases for Developmental Dyslexia on fMRI DataFrontiers in Computational Neuroscience, vol. 15, 594659Contributions to Journals: Articles
Brainhack: Developing a culture of open, inclusive, community-driven neuroscienceNeuron, vol. 109, no. 11, pp. 1769-1775Contributions to Journals: Articles
Norm Conflict Identification Using a Convolutional Neural NetworkCoordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XIII. Aler Tubella, A., Cranefield, S., Frantz, C., Meneguzzi, F., Vasconcelos, W. (eds.). SpringerChapters in Books, Reports and Conference Proceedings: Chapters
Predicting Brain Age at Slice Level: Convolutional Neural Networks and Consequences for InterpretabilityFrontiers in psychiatry, vol. 12, 598518Contributions to Journals: Articles