Summary
Matheus Do Carmo Alves is a computer scientist and postdoctoral researcher specializing in AI and reinforcement learning approaches for robotics and decision-making under uncertainty. With nine years of research experience and appointments at USP, Lancaster University and FAPESP, he develops practical algorithms for forecasting, latent parameter estimation and robust statistical learning when data or knowledge are scarce. His work has been published in top venues including NeurIPS, (J)AAMAS and Knowledge-Based Systems, reflecting a balance of theoretical novelty and real-world applicability. Comfortable in cross-cultural teams, he brings a detail-oriented, communicative style informed by diverse collaborations and hands-on roles from academia to industry. Beyond research, his background includes five years coordinating leisure programs and an early passion for acoustic guitar, hints of creativity that influence his problem-solving approach. Based in São Carlos, Brazil, he focuses on translating principled models of uncertainty into reliable solutions for everyday and robotic systems.
9 years of coding experience
4 years of employment as a software developer
Post-doc Mobile Robotics, Post-doc Mobile Robotics at USP - Universidade de São Paulo
Doctor of Philosophy - PhD Ciência da Computação, Doctor of Philosophy - PhD Ciência da Computação at Lancaster University
English, Portuguese