CPSWin Research

The CPSWin lab supports a wide range of fundamental as well as applied research in the areas of cyber physical systems and wireless communications. The core expertise of the group lies in statistical signal processing and information science and its application to modeling and analysis of cyber physical systems, wireless communication systems and complex networks. The group has received funding from federal and state agencies such as National Science Foundation (NSF), NASA, Department of Energy (DOE), Kansas Dept. of Transportation (KDoT), Sandia National Labs, National Renewable Energy Laboratory (NREL), U.S Marines (M2 Technologies), State of Kansas and Kansas State University Targeted excellence program, as well as industry partners Garmin Inc., Trisquare Communications, etc. Researchers in the group have contributed to more than 100 peer reviewed publications.

Key projects in the wireless communication area over the last five years include design of a practical cognitive radio, resource allocation and quality of service assurance in a competitive cognitive radio network, precoding for MIMO and MIMO-OFDM systems, coexistence issues between ultra-wideband and GPS systems, multiuser detection in MC-CDMA systems, and biologically inspired spreading sequence design strategies. The group’s contribution to the fields of spread spectrum communication and MIMO precoding has resulted in two patent applications. Projects in the area of information processing in sensor networks include resource allocation in collaborative target tracking, information fusion strategies for distributed event detection over bandwidth constrained networks, optimal control-based sensor deployment strategies, sensor fusion in biomedical applications, networked control of distributed systems, and automated pavement distress detection via image processing and sensor fusion methods.

Research Thrusts

	Stochastic hybrid system modeling, estimation and multi-agent networked control in smartgrid Compressive sensing-based state estimation in power systems Modeling interaction of communication, control and sensing networks in power systems
	Data imputation in sparsely observable tumor micro-environments Surrogate multi-dimensional sensing modalities to quantify hydration levels Motion artifact detection and removal in biomedical signals Quality of sleep analysis through non-intrusive sensing and data analytics Stochastic modeling, estimation and control for ablation treatment planning
	Stochastic modeling of complex interdependent systems (water, power, transportation, etc.) Multi-dimensional resilience analysis incorporating physical, cyber and social dimensions Scalable resilience evaluation with advanced machine-learning based approaches
	Sensor localization and optimal placement Heterogenous information fusion Collaborative target tracking Energy aware management of heterogenous networks Energy harvesting in IoT Cooperative PHY layer security Interference modeling in mm-wave networks Non-gaussian interference mitigation techniques