John C. Doyle is Professor of Control and Dynamical Systems, Bioengineering, and Electrical Engineering and at the California Institute of Technology. He has a BS and MS in EE, from MIT, 1977 and a PhD in mathematics, UC-Berkeley, 1984. His current research interests are in theoretical foundations for complex networks, primarily in engineering and biology, and the interplay between robustness, feedback, control, dynamical systems, computation, communications, and statistical physics. Additional interests include theoretical foundations of multiscale physics and financial markets. Prize papers include the IEEE Baker (also ranked in the top 10 "most important'" papers world-wide in pure and applied mathematics from 1981-1993), the IEEE AC Transactions Axelby (twice), and the AACC Schuck. Individual awards include the IEEE Centennial Outstanding Young Engineer, the IEEE Hickernell, the American Automatic Control Council (AACC) Eckman, and the Bernard Friedman. He has held national and world records and championships in various sports.


Many popular technological visions emphasize ubiquitous control, communications, and computing, with systems requiring high levels of not only autonomy and adaptation, but also evolvability, scalability, and verifiability. With current technology these are profoundly incompatible objectives, and both biology and nanotechnology create additional novel multiscale challenges. A rigorous, practical, and unified theoretical framework will be essential for this vision, but until recently, has proven stubbornly elusive. Two of the great abstractions of the 20th century were the separation, in both theory and applications, of 1) controls, communications, and computing from each other, and 2) the systems level from its underlying physical substrate. This horizontal and vertical isolation of systems held both in practical applications and in academic research. It facilitated massively parallel, wildly successful, explosive growth in both mathematical theory and technology, but left many fundamental problems unresolved and a poor foundation for future systems of systems in which these elements must be integrated.

While the search for "unified theories" both of systems and of multiscale physics has been an appealing intellectual challenge for decades, it has only recently become both an urgent technological challenge, and a tangibly reachable research objective. New research offers not only a theoretical research direction of unprecedented promise, but also one that has already proven remarkably useful in a wide variety of practical applications, including biological regulatory networks in signal transduction, metabolism, and gene regulation, shear flow turbulence, networking protocols, global optimization, forest ecology, and financial market volatility.

One unifying theme in this work is the concept of Highly Optimized Tolerance (HOT) that arises when deliberate robust design aims for a specific level of tolerance to uncertainty. The resulting "robust, yet fragile" features of HOT systems are high performance and high throughput, but potentially serious sensitivities to design flaws and unanticipated or rare events, particularly those that can cause catastrophic, cascading failures. HOT provides a framework in which the previously fragmented mathematical tools of robust control, communications, computation, dynamical systems, and statistical physics are unified and brought to bear on a variety of applications. While the focus of this research is on providing a rigorous basis for designing future networks of networks involving ubiquitous control, communications and computing, it is surprisingly relevant to resolving many persistent mysteries at the foundations of physics where interconnected, multiscale systems issues arise. This talk will focus on the most well developed examples, beginning with an explanation of the ubiquity of power laws in natural and man-made systems, which was one of the original motivations for HOT. Additional examples, each with new and novel theories, include a fundamentally new view of turbulence in the highly sheared flows that results from design for drag minimization, the origin of macroscopic dissipation and thermodynamic irreversibility in microscopically reversible dynamics, and aspects of the quantum/classical transition and quantum measurement.