Research and Interests

My research program – at the intersection of network science, limited-communication decision-making, distributed algorithms and security – centers on the development of techniques to efficiently coordinate the operation of spatially distributed large-scale networked dynamic systems. My group works on optimization and control challenges in Cyber-Physical Systems and other networked autonomous systems such as multi-robot systems and networks of smart devices. Some current areas of work include:

  • Distributed Optimization in Large-Scale Systems
    The broad objectives are to design and characterize the performance of distributed optimization algorithms in large-scale systems. We also study how these algorithms operate in adversarial and communication-constrained environments. Techniques being developed here are equally important in the context of efficiently using communication resources as we record explosive growth in the volume of connected devices.
  • Information-efficient Distributed Sensing for Decision-Making
    The goal in this research direction is to develop distributed methods for sensors operating in limited-communication environments. These methods enable fully distributed computation of each sensor’s uncertainty and enhance robustness of networks of sensors. Outcomes of this work are critical in teams of autonomous systems where subsets of sensors may need to be selected for certain tasks with performance requirements.
  • Control of Epidemic Dynamics in Networks
    In this area, we study the problem of mitigating the spread of viral process in network. We model infection propagation in networks using a network epidemic model and propose optimization and machine learning approaches to solving the contagion control problem.   The goals here are to model and characterize defense mechanisms in networked systems, using domain specific, realistic propagation models; and propose techniques for securing the network against viral attacks. The impact of other factors, including traffic flows on the control outcomes are studied.