The department extends a hearty welcome to (L-R) Dr. Mingyue Ji, Dr. Jie Xu, Dr. Rickard Ewetz, Dr. Dennis Kim, and Dr. Laura Kim.
Dennis Kim
Dr. Dennis Kim holds a Ph.D. from the California Institute of Technology. Prior to joining UF, he was a postdoctoral associate in the Department of Materials Science and Engineering at the Massachusetts Institute of Technology, and a STROBE postdoctoral fellow and a research scientist in the Department of Physics and Astronomy and Chemistry, respectively, at UCLA. His research background is in picoscale engineering through state-of-the-art scattering, imaging, and quantum mechanical computational techniques. His work has been featured in Nature, Nature Materials, Nature Physics, Physical Review Letters, Science Advances, and PNAS. He is interested in developing and optimizing systems for various thermal, energy, and quantum science applications through a fundamental understanding from the atom up.
Laura Kim
Before joining UF, Dr. Laura Kim was an assistant professor in the Department of Materials Science and Engineering at UCLA. Prior to her appointment, she completed her IC Postdoctoral Fellowship in the Quantum Photonics Laboratory at the Massachusetts Institute of Technology. She received her B.S. and Ph.D. degrees from the California Institute of Technology. Dr. Kim was named a 2020 EECS Rising Star and is a recipient of the 2023 Nanophotonics Early Career Award, UCLA Faculty Career Development Award, the IC Postdoctoral Fellowship, the Gary Malouf Foundation Award, and a National Science Foundation Graduate Research Fellowship. She serves on the Early Career Editorial Advisory Board of Applied Physics Letters. Her current research interests include enhancing quantum-excitation-driven light-matter interactions and developing nanoscale quantum sensing technologies.
Rickard Ewetz
Prior to joining UF, Dr. Rickard Ewetz was an associate professor in the Electrical and Computer Engineering (ECE) Department at the University of Central Florida. He received his Ph.D. degree in ECE from Purdue University in 2016. His research interests are broadly focused on the intersection of hardware and artificial intelligence. This includes creating electronic design automation algorithms, hardware/software co-design methodologies for emerging in-memory computing systems. He is actively working on AI/ML topics such as explainable AI, robust AI, and neuro-symbolic AI. His research is supported by DARPA, DOE, NSF, AFRL, Lockheed Martin Corp, Cyber-Florida, and the Florida High Tech Corridor Council.
Mingyue Ji
Dr. Mingyue Ji received the Ph.D. degree from the Ming Hsieh Department of Electrical and Computer Engineering at the University of Southern California in 2015. He subsequently was a Staff II System Design Scientist with Broadcom Inc. from 2015 to 2016. Prior to joining UF, Ji was an associate professor in the Department of Electrical and Computer Engineering and an adjunct associate professor in the Kahlert School of Computing at the University of Utah.
His research interests span a broad spectrum, including cloud and edge computing, distributed machine learning, and 5G and beyond wireless communications, networking, and sensing. Ji’s research activities cover fundamental theory study, algorithm design and analysis, and practical system implementation and experimentation. He received the NSF CAREER Award in 2022, the IEEE Communications Society Leonard G. Abraham Prize for the Best IEEE Journal on Selected Areas in Communications (JSAC) Paper in 2019, the 2022 Outstanding ECE Teaching Award, and the 2023 Outstanding ECE Research Award at the University of Utah. He has been serving as associate editor for IEEE Transactions on Information Theory since 2022 and IEEE Transactions on Communications since 2020.
Jie Xu
Prior to joining UF, Dr. Jie Xu was an associate professor in the Department of Electrical and Computer Engineering at the University of Miami. He earned his Ph.D. in Electrical Engineering from UCLA in 2015, preceded by his completion of both BS and MS degrees at Tsinghua University in China. Xu’s research interests are at the intersection of edge computing, machine learning and wireless networking. He focuses on advancing machine learning, optimization, and statistical signal processing algorithms to enhance the performance of current and future computing and networking systems.
Additionally, he develops new systems and architectures tailored for emerging applications heavily reliant on machine learning. Dr. Xu has published over 100 research papers in leading journals and conferences, with more than 5000 citations. His research has been supported by federal agencies including National Science Foundation (NSF) and Army Research Office (ARO). Dr. Xu is a recipient of NSF CAREER award, David J. Sumanth Early Career Research Award at UM, Distinguished Ph.D. Dissertation Award at UCLA, and an APCC Best Paper Award.