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Welcome to ECE’s Departmental Portal, which strives to bring all applicable departmental information into one accessible and efficient locale for students, faculty and staff alike.
✨ Lightsaber-style antennas are here! ECE PhD student Prya Darshni and Cirrus Logic Distinguished Professor Paul Franzon have demonstrated the first-ever plasma beam antenna, using a laser to turn a thin beam of air into an antenna that transmits radio waves. 🌌🪐💫☄️
By adjusting the laser, the team can control the antenna`s length and angle, so it can sweep a broad range of frequencies without bulky mechanical parts. They also built a contactless feed that drives the plasma beam without touching it, a promising step for satellites and space exploration. The work is published in the IEEE Journal of Microwaves.
Proud to see our ECE graduate students leading research that has never been done before! 📡
Read more: http://ncst.at/kFo250ZUHNS
🐺 Computer engineering breaks into the top 20! NC State`s undergraduate computer engineering program is now No. 19 in the nation in U.S. News & World Report`s 2027 Best Colleges rankings.
Among public universities, computer engineering ranks No. 12 and electrical engineering No. 14. The College of Engineering is rising too, moving up to No. 32 nationally (No. 18 among publics) with eight programs in the top 20.
Interim Dean Veena Misra, former ECE department head, credits "engineering excellence at scale." We couldn`t agree more. Proud of our ECE students, faculty and staff! ❤️🏆
🐺 Fall kickoff, Wolfpack style! Despite a rain delay, hundreds of students turned out for POP Back on Centennial Campus, grabbing free food, playing games and connecting with dozens of student groups and employers.
Our ECE community was right there in the mix, kicking off the year by building the connections and community that make Centennial Campus feel like home.
Here`s to a great year ahead! 🎉
Read more: http://ncst.at/vYCc50ZRELu
☀️ Bright ideas for the power grid! ECE PhD student Arundhuti Haldar co-authored new research showing that combining machine learning models can improve day-ahead solar power forecasts by up to 13% - helping utilities better balance supply and demand as solar energy use grows nationwide.
Published in the Journal of Cleaner Production, the team tested seven forecasting models across two California utilities and found that blending forecasts and tailoring them to each region delivers the biggest gains.
Proud to see our ECE graduate students contributing to research that keeps the clean energy transition running smoothly! 🔋
Read more: http://ncst.at/Uce850ZPEg9
