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About

David Angeli is a distinguished control theorist whose research spans nonlinear systems, stability analysis, and distributed optimization. Best known for his foundational contributions to input-to-state stability (ISS) theory, his 1999 paper on PD-controlled robotic systems — now boasting over 111 citations — established rigorous stability guarantees for a widely used class of robotic controllers, providing researchers and engineers with essential tools for designing reliable motion control systems. This work cemented his reputation as a leading voice in nonlinear control. Angeli's research has evolved to address emerging challenges in networked and multi-agent systems. His 2015 work on consensus of time-varying nonlinear networks broke new ground by tackling asymptotic consensus under almost-periodic interactions, with elegant applications to coordinated field sampling by mobile robot teams — a problem of growing relevance in environmental monitoring and autonomous systems. More recently, he has turned his attention to distributed convex optimization, exploring causal filtering of gradient information to enhance robustness and resilience in large-scale networked algorithms. Spanning three decades, Angeli's contributions reflect a coherent intellectual trajectory: bringing rigorous mathematical analysis to bear on the increasingly complex, interconnected control systems that define modern engineering practice.