Dr. Veena Misra, Distinguished Professor of Electrical and Computer Engineering at NC State University and the Director of the NSF ASSIST Nanosystems Center has been selected by the IEEE Sensors Council as a Distinguished Lecturer for 2018-2020.
NC State’s 2017-2018 class of University Faculty Scholars including Dr. Huaiyu Dai, professor of electrical and computer engineering, represent early- and mid-career faculty dedicated to serving the university community and their respective fields through scholarship, research, and engagement.
Two NC State ECE professors were honored with elevation to IEEE Fellow in recognition of their outstanding contributions to the field of electrical and computer engineering.
Achieving promotion and tenure mark significant milestones for the faculty at NC State. 2017 marks the promotion of Drs. Gupta, Oralkan, White, and Lobaton.
Dr. Gregory T. Byrd, professor and Associate Department Head of the Electrical and Computer Engineering Department at NC State University was elected by the IEEE Computer Society as the 2018 First Vice President.
Researchers have developed new software and hardware designs that should limit programming errors and improve system performance in devices that use non-volatile memory (NVM) technologies.
Dr. Daniel D. Stancil, Alcoa Distinguished Professor and Department Head of Electrical and Computer Engineering at North Carolina State University has been named president of the Electrical and Computer Engineering Department Heads Association (ECEDHA).
This is a guest post by Edgar Lobaton – Autonomous systems are becoming a reality in our everyday lives. A few examples that most of us have seen in the news include autonomous vehicles such as the Google Car, and autonomous stores such as Amazon Go. All of these systems require sophisticated sensing, machine learning and artificial intelligence in order to make them work, which fascinates me.
Researchers from North Carolina State University’s Department of Electrical & Computer Engineering have developed an energy-efficient technique for accurately tracking a user’s physical activity based on data from wearable devices.