We fabricate and characterize a range of materials including ferroelectric, oxides, III-V thin-films, 2D layered materials and nanostructured ingots. The structural and transport characterizations enable materials integration in novel electronic, thermal or optical devices.
Electrical and Computer Engineering Research
The Charles L. Brown Department of Electrical and Computer Engineering is well-known for its world-class photonics and high frequency diodes. Our department bridges quantum science, communication and engineering. Our faculty lead cutting-edge research in ultra low-power chip design. We are proud of our long-standing tradition in computer engineering, medical imaging, signals and systems, and machine learning research.
We excel in the design of THz devices and circuits, microelectromechanical components, super-conducting materials, and beyond-CMOS electronics. Our research advances non-Boolean computing, biomolecular sensing, long-range sensing (radio telescopes), wireless communications, and large-scale data storage.
We lead in photodetector research on high-speed, high-power photodiodes and low noise avalanche photodiodes. We also have a rising program in microresonators and modeling and fabrication of photonic integrated circuits. Laser applications enable improved performance of photonic devices.
Our strengths in adaptive and nonlinear control, assured autonomy, and dependable and secure computing lead the way in developing a wide range of resilient robotic and cyber-physical systems, including active magnetic bearings, micro-grids, aerial, ground and underwater vehicles, medical devices, and surgical robots.
Our applications-driven research in IoT systems emphasizes self-powered systems, leveraging energy-efficient, sub-threshold circuit design. Our research on in-memory processing, integrated system design, and advanced materials aims to address computational challenges arising in AI and optimization.
We specialize in the theoretical foundations of signal processing, communications, and machine learning, as well as a wide range of applications, including biomedical image analysis, intelligent and secure networks, social computing, and emerging data storage technologies.