Faculty Updates
This will now be my seventh year as Chair of Physics and most likely my penultimate year – my renewed contract was for two years which will end in 2025. As you can see from the news, we have a lot going on. Thankfully, the […]
Awards
Awards Received by Faculty, Staff and Students October 2023 Professor Martin Guthold was awarded the Kulynych Family Faculty Fellowship. This fellowship has a three-year term beginning July 1, 2023, and ending June 30, 2026. This and other fellowships recognize Wake Forest’s best teacher-scholars. The Wake […]
Recent Changes
Significant Changes Over the Past Year October 2023 The department has had great success in the past year. According to College Factual, the Physics Department now ranks 41 out of 226 colleges and universities in the US for our Bachelor of Science degree, second in […]
2023 Alumni Award
October 2023 In 2018 we implemented a new alumni award. The award is given to a Physics Department alumnus for exceptional achievements and/or service. The award is not limited to physics but covers all areas that our alumni excel in. This year the award is […]
Homecoming Reception 2023
October 2023 The Physics Department faculty and staff invite you to our Homecoming reception and demo show on Saturday, October 21. We will join the Festival on the Quad again this year. We will have a table near the steps of Wait Chapel. Due to the […]
Student Profile – Sophia Lourduraj
Sophia Lourduraj is a current third-year student at Wake Forest studying biophysics. In a discussion with Professor Freddie Salsbury she shares her own unique Wake story and tells us about her interest in the intersection between biology and physics: biophysics. Prof. Salsbury: What led you […]
Fall 2022 Courses
Undergraduate Courses: Graduate Courses:
Organic Neuromorphic Electronics and Biohybrid Systems
Yoeri van de Burgt 1,2 1 Microsystems, Eindhoven University of Technology, Eindhoven, Netherlands2 Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, Netherlands Neuromorphic computing could address the inherent limitations of conventional silicon technology in dedicated machine learning applications. Recent work on large crossbar […]
