![Professor Felipe Meneguzzi Professor Felipe Meneguzzi](/img/200x200/staffpages/uploads/s09fm1/avatar/0SmsGCd23nHsJaZmKwKUdPjQtBnf1PisfQN8FwrT.jpeg)
Chair in Computing Science
- About
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Biography
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. I was a Professor of AI at the Pontifical Catholic University of Rio Grande do Sul in Brazil, where I remain as a Bridges Professor. Before my current position, I 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.
Qualifications
- PhD Artificial Intelligence2009 - King's College London
External Memberships
- Executive Council of the AAAI
- Special Committee on AI for the Brazilian Computer Society
- Bridges Professor 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.
- Research
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Research Overview
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.
Research Areas
Accepting PhDs
I am currently accepting PhDs in Computing Science.
Please get in touch if you would like to discuss your research ideas further.
Research Specialisms
- Artificial Intelligence
- Machine Learning
Our research specialisms are based on the Higher Education Classification of Subjects (HECoS) which is HESA open data, published under the Creative Commons Attribution 4.0 International licence.
- Publications
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Page 1 of 20 Results 1 to 10 of 195
A Practical Operational Semantics for Classical Planning in BDI Agents
Contributions to Conferences: Papers- [ONLINE] https://www.ecai2024.eu/
Explorative Imitation Learning: A Path Signature Approach for Continuous Environments
Contributions to Conferences: PapersReal-time goal recognition using approximations in Euclidean space
Contributions to Conferences: Papers- [ONLINE] Conference website
BDI Agents in Natural Language Environments
Chapters in Books, Reports and Conference Proceedings: Conference ProceedingsEmpowering BDI Agents with Generalised Decision-Making
Chapters in Books, Reports and Conference Proceedings: Conference ProceedingsA Survey of Imitation Learning Methods, Environments and Metrics
Working Papers: Preprint PapersA Survey on Model-Free Goal Recognition
Contributions to Conferences: PapersGoal Recognition via Linear Programming
Working Papers: Preprint PapersAssessment of Radiation-Induced Soft Error on Unmanned Surface Vehicles
IEEE Transactions on Nuclear ScienceContributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/TNS.2024.3378807
Temporally extended goal recognition in fully observable non-deterministic domain models
Applied Intelligence, vol. 54, pp. 470-489Contributions to Journals: Articles