Max Robotics — Global Service Robot Directory + US Certification

About

Lifeng Zhou is a robotics and autonomous systems researcher whose work sits at the intersection of multi-robot coordination, adversarial resilience, and submodular optimization. His research addresses some of the most pressing challenges in deploying robot teams in real-world environments, particularly how to maintain robust performance when robots face sensor failures, communication disruptions, or deliberate adversarial attacks. Zhou's most influential contribution, "Resilient Active Target Tracking With Multiple Robots" (2018, 91 citations), established foundational frameworks for keeping robot teams functional under attack — a critical concern for autonomous systems in contested environments. He has consistently extended this theme, developing distributed algorithms that protect swarm-robotics applications against denial-of-service attacks and designing graph neural network approaches that make decentralized tracking scalable across large robot teams. Beyond resilience, Zhou has made notable contributions to risk-aware decision-making, applying Conditional Value-at-Risk to submodular optimization and developing adaptive control frameworks for robots with heterogeneous sensors. His work on self-triggered communications further demonstrates a talent for practical efficiency — reducing coordination overhead without sacrificing tracking performance. With over 330 cumulative citations across his top papers, Zhou has established himself as a leading voice in making multi-robot systems simultaneously intelligent, efficient, and robust enough for adversarial real-world deployment.