Marcus A Pereira
Papers
1
Total Citations
8
H-Index
1
About
Dr. Marcus A. Pereira is a rising leader in safe, decentralized multi-agent control under uncertainty. His research sits at the intersection of stochastic optimal control, reinforcement learning, and distributed optimization, with a focus on ensuring safety guarantees for autonomous systems operating in complex environments. In his highly cited 2022 work, Pereira introduced a novel framework that combines deep forward-backward stochastic differential equations (FBSDEs) with the alternating direction method of multipliers (ADMM) to achieve scalable, safe coordination among multiple agents. By encoding safety via stochastic control barrier functions and computing safe controls through decentralized quadratic programs, his approach overcomes key scalability and robustness challenges in multi-agent systems. This work has already garnered 8 citations, reflecting its timely impact on the fields of robotics and autonomous driving. Pereira’s contributions are paving the way for provably safe, decentralized decision-making in applications ranging from drone swarms to connected vehicle networks, marking him as a researcher to watch in the next generation of control theory.
Research Focus
Key Achievements
Top Papers
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