Irene Perez-Salesa

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About

Irene Perez-Salesa is an emerging researcher specializing in distributed systems, multi-agent coordination, and networked control, with a particular focus on developing efficient communication strategies for complex robotic and large-scale systems. Her work sits at the intersection of control theory and robotics, addressing fundamental challenges in how networks of agents can collectively estimate and share information with minimal communication overhead. Her most recognized contribution, "Precise Dynamic Consensus under Event-Triggered Communication" (2023), tackles the problem of estimating time-varying signals across distributed networks — a capability critical for applications such as formation control and target tracking in multi-robot systems. Building on this foundation, her subsequent research extends these ideas into distributed state estimation, combining asymptotic Kalman-Bucy filtering with event-triggering mechanisms to significantly reduce inter-agent communication burdens without sacrificing estimation accuracy. Her 2024 work on optimal distributed estimation based on fixed-time consensus further demonstrates her commitment to developing principled, performance-guaranteed solutions for networked systems. Although early in her career — with her top papers accumulating a combined nine citations — Perez-Salesa is establishing a coherent and technically rigorous research agenda that addresses pressing real-world challenges in cooperative robotics and intelligent networked systems, positioning her as a promising voice in her field.