RESEARCH

Overview


My broad research interest lies in the understanding and management of Complex Networked Systems (CNS) that naturally arise in a variety of real-world settings, such as efficient resource allocation in communication and computer networks, distributed operation of large data processing systems, intelligent management of cyber-physical systems (CPS), and learning and targeting in social networks, etc.

The ideal that drives my research efforts is the well-founded development of efficient, robust, adaptable, and scalable protocols that achieve provably good performance despite the stochastic and highly complex dynamics of the underlying networks. To that end, I take a theoretically well- founded and inter-disciplinary approach geared towards the development of diverse methods and fundamental principles that are applicable to the aforementioned wide range of application areas.

Activity


A significant portion of my research in the pursuit of my broad objectives is aimed at the modeling, analysis, and design of large scale wireless & backbone communication and computer networks. My research activities in this direction can be organized into four topics:

  • Foundations (e.g. see [J1, J2, J5, J6, J9, J20, J27, J31, J32]), which aim at establishing an increasingly more comprehensive framework for stochastic network optimization and architecture design for communication networks;

  • Protocol Design (e.g. see [J3, J8, J11, J13, J14, J17-19 J26, J30]), which aims at developing low-complexity, low-overhead, scalable, and provably efficient protocolsalgorithms that carry out the principles and strategies emanating from the theoretical foundations;

  • Performance Analysis (e.g. see [J2, J4, J5, J7, J9, J15, J16, J28, J29]), which aims at the rigorous mathematical analysis of proposed algorithms to establish performance guarantees and to reveal the limits of their applicability;

  • Expanding the Frontiers (e.g. see [J10, J12, J21, J22]), which aim at expanding the framework by incorporating innovative network coding techniques at the physical-level and by exploiting predictability of behavior at the user-level.