Expanding the engineering profession to all.
At UCLA, diversity is an indispensable element of academic excellence. The UCLA Samueli School of Engineering is committed to a diverse faculty and student body, with programs that open the opportunities an engineering education provides to anyone with the talent and the desire to succeed. A population rich in diversity expands the range of knowledge, experiences, and viewpoints, leading to innovative new solutions that otherwise wouldn’t be possible.
Programs to enable the success of all of our students, regardless of ethnic or economic background, are in place – and are working. Over the next decade, we will double the percentage of underrepresented minorities and increase the percentage of women in both our student body and our faculty.
UCLA electrical engineering graduate student Glen Meyerowitz is developing a low-cost ventilator in collaboration with medical professionals at UCLA Health.
Bioengineering professor and director of the Makerspace demonstrates laser-cutting face shields and 3D-printing headbands, while electric engineering doctoral student Glen Meyerowitz showcases a ventilator prototype he designed using everyday household materials.
A research team from the UCLA Samueli School of Engineering has demonstrated that a specially designed surface is able to reduce friction from flowing water by nearly a third. This was done in a first-ever successful boat test on open water in Marina Del Rey, California.
With a deluge of patients suffering from COVID-19 expected to flood hospitals in the very near future, UCLA engineers are part of a quickly growing team working to build up supplies of personal protective equipment for health care workers.
Bioengineers at UCLA Samueli School of Engineering and their colleagues have developed and successfully demonstrated a wearable fabric that can harvest and store energy from the sun.
The California High-Speed Rail Authority has awarded a three-year grant to UCLA to create a database of earthquake fault displacements and develop a predictive model to estimate the fault displacements.