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Research Areas
The Preston M. Green Department Electrical & Systems Engineers focuses research on four distinct areas: applied physics, devices & circuits, signals & imaging, and systems science.
Our faculty, students and staff collaborate across disciplines, creating new knowledge to address some of the world’s most challenging problems. Student research projects are supported by faculty mentors and other university resources. Faculty successfully win backing for their research from many sources, including the federal government, state governments, corporations, foundations, nonprofit agencies, individuals and the university itself.
30 FULL TIME
FACULTY
4.6 MILLION IN
RESEARCH EXPENDITURES
(FY20)
RESEARCH
PARTNERSHIPS
4 RESEARCH AREAS
BREAKING NEW GROUND
Create New Knowledge
By integrating research and teaching, our faculty keep their work relevant. Whether you are an undergraduate student, graduate student or postdoctoral scholar, you will have an opportunity to conduct path-breaking research alongside world-class faculty experts. Learn more about how we're making a difference in the following areas.
Applied Physics
Faculty in this area focus on topics in advanced materials, integrated photonics and optoelectronics, nano-fabrication, and new device concepts.
A one-way street for acoustic waves
Researchers at Washington University in St. Louis and Harvard University have developed a non-reciprocal device for acoustic waves that could be used in next-generation wireless communication and quantum computing.
One step closer to bomb-sniffing cyborg
Researchers showed how they were able to hijack a locust’s olfactory system to both detect and discriminate between different explosive scents
Devices & Circuits
Faculty in this area study nanoelectronics and emerging devices, sensors and sensing systems, and cyberphysical systems.
Signals & Imaging
In this area, the department's research focuses on model-based digital and analog signal and image processing, multiaccess communications, computational linguistics and wireless networking.
Building a better microscope: Using computations, machine learning and signal processing
Ulugbek Kamilov plans to use a three-year, $265,293 grant from the National Science Foundation to capture the information that normally gets lost and add it to the information researchers typically receive from microscopes.
Break it down: A new way to address common computing problem
A computational framework for solving linear inverse problems takes a parallel computing approach.
Systems Science
Our faculty within the department study, design, develop, manage and optimize complex systems including electrical systems, information systems, quantum systems and telecommunication networks.
