Felipe Mascarenhas

Papers

Total Citations

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About

Felipe Mascarenhas is a researcher at the intersection of artificial intelligence, robotics, and multi-agent systems, with a particular focus on robotic soccer and machine learning. His most-cited work, "BahiaRT Setplays Collecting Toolkit and BahiaRT Gym" (2022, 10 citations), addresses a critical challenge in AI research: the need for realistic, expert-informed datasets. By developing a software toolkit that allows soccer fans and domain experts to annotate and collect setplays—coordinated team strategies—from simulated robot matches, Mascarenhas bridges the gap between common-sense human knowledge and machine learning models. This contribution is pivotal for training autonomous agents to execute complex, collaborative behaviors in dynamic environments. His work is closely tied to the BahiaRT team, a prominent participant in the RoboCup competition, where his tools enhance the team's strategic play. With a growing citation impact, Mascarenhas’s research not only advances the field of multi-robot coordination but also democratizes data collection, enabling non-experts to contribute to cutting-edge AI. His achievements underscore a commitment to making AI more accessible and effective in real-world, team-based scenarios.