Welcome to Complex Systems Control Laboratory (CSCL) web page. Our research lab is engaged in advancing several aspects of modeling and model-based control design for complex systems. In particular, our lab develops: (1) a suite of analytical tools for data-driven modeling of complex nonlinear systems using statistical machine learning methods; (2) distributed (both robust and stochastic) model predictive control design methods for spatially interconnected systems; (3) distributed coverage control algorithms for heterogeneous multi-agent systems operating under uncertainties and with an intermittent communication; (4) fog computing-based algorithms for distributed monitoring and control in smart grids; (5) new countermeasures based on statistical graph-theoretic methods to quickly and accurately detect cyber (and cyber-physical) attacks in smart grids.