ECE News

April 8, 2022

Junkai Jiang recently receives his 2020 award from the ECE Department – doctoral students who received their Ph.D. degree from Fall 2019 to Fall 2020 were considered for the award based on their faculty advisor’s nomination

April 6, 2022

Three ECE students recognized by National Science Foundation (NSF) for the 2022 Graduate Research Fellowship Program (GRFP): Hae Lim (fellowship) and Spencer Hutchinson & Nicholas Lewis (honorable mentions)

March 8, 2022

The Nobel Prize might be better known, but time and again, the Millennium Technology Prize has been one of the first international awards to recognize great innovation

March 7, 2022

Research.com lists UCSB ECE Professors S. DenBaars, J. Bowers, U. Mishra, A. Teel, P. Kokotovic and L. Coldren among the top Electronics and Electrical Engineering scientists in the world and also ranks UCSB at 6th out of 139 U.S. universities in E & EE and 8th among 644 universities in the world

March 7, 2022

Because LEDs come in various shades, ECE Prof. Steven DenBaars, says customers “need to understand what color temperature they want.”

February 9, 2022

ECE Assistant Professor Kerem Çamsarı receives a prestigious Young Investigator Award from the Office of Naval Research

January 27, 2022

ECE Prof. John Bowers elected as a 2021 American Association for the Advancement of Science Fellow (AAAS)

January 19, 2022

Professor William Smith from UCSB's  Department of Molecular, Cellular and Developmental Biology (EEMB) teams up with ECE professor B. S. Manjunath and his student Angela Zhang in an interdisciplinary undertaking

December 22, 2021

ECE Prof. B.S. Manjunath and four Materials professors receive an NSF grant of $578,000 (2 years) to develop an ultrafast, ultrasensitive direct electron back-scattered diffraction (EBSD) instrument for the widely accessible scanning electron microscopes (SEMs) platform

December 21, 2021

ECE Ass't. Prof. Nina Miolane receives an NSF grant of $334,780 (3 years) for her research project that examines the need to rigorously understand and expand the data types to which deep-learning methods can be applied