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Research Areas
The Preston M. Green Department of Electrical & Systems Engineering focuses research in 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.
27 FULL TIME
FACULTY
$7 million
RESEARCH EXPENDITURES
(FY23)
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.
Ultrahigh-sensitivity microprobe optimizes detection of molecular fingerprints
A team led by Lan Yang developed a novel whispering-gallery-mode microprobe optimized for ultrahigh sensitivity and increased detection area.
Research network to focus on AI, integrated circuits
Shantanu Chakrabartty and collaborators are looking at the way the brain is structured and its neural mechanisms as a model for hardware and algorithms that make the most of computational performance with the least amount of power. (iStock photo)
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.
Meet DOLCE, a generative AI tool that can reconstruct CT images from limited-view data
Ulugbek Kamilov and Jiaming Liu developed a sophisticated deep learning model that can create high-quality CT images from severely limited data and quantify the uncertainty in the reconstructed images.
Research in Braver and Ching labs could boost thinking, focus
A new NIH grant will support a project that uses computer modeling and precise electric currents to promote an active, focused state of mind.
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.
