Our research interests include:
  • Statistical signal processing, machine learning, and imaging for information inference and decision making: measurement data modeling, algorithms for hypothesis testing, detection and estimation, classification, prediction, performance analysis, and bounds.
  • Mathematical modeling of complex systems, including networks, biological systems, elelctromagnetic and acoustic waves, optical systems, and physical devices.
  • Optimal design of measurement systems, statistical inference methods, and physical devices: we formulate mathematical utility functions to characterize the performance of specific systems. We then optimally design these systems by maximizing their utility functions with respect to their variables using tools from game theory, risk analysis, price theory, combinatorial optimization, linear programming, greedy methods, and proximal algorithms.
       Applications include biomedicine, defense, energy, and the environment.
       Projects are chosen to match with the students' interests, available funding, and new directions. More details can be found below (move the mouse and click).

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