Dr. Doyle's research is on mathematical foundations for complex networks with applications in biology, technology, medicine, ecology, neuroscience, and multiscale physics that integrates theory from control, computation, communication, optimization, statistics (e.g. Machine Learning). An emphasis on universal laws and architectures, robustness/efficiency and speed/accuracy tradeoffs, adaptability, and evolvability and large scale systems with sparse, saturating, delayed, quantized, uncertain sensing, communications, computing, and actuation. Early work was on robustness of feedback control systems with applications to aerospace and process control. His students and research group developed software packages like the Matlab Robust Control Toolbox and the Systems Biology Markup Language (SBML).