Professor Felipe Meneguzzi

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.

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 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.