COFFEE is a student club that offers academic support, networking opportunities and community for electrical and computer engineering students. Since its founding in 2018, the club has grown from a small group to a cornerstone organization making visible, impactful enhancements to student life.
For a master’s thesis describing a processing framework that achieved a 32 million-times improvement in speed and energy efficiency over NVIDIA, the College of Engineering celebrates Sagar Sajeev, a recent electrical and computer engineering alum.
For innovative research on chips that can sustain high speeds without sacrificing power or signal amplification, a feat necessary for realizing the wireless networks of tomorrow, Phat Nguyen has received the Zuhair A. Munir Award for Best Doctoral Dissertation in Engineering at UC Davis.
ImmobiCUFF, a medtech startup founded by five biomedical engineering alumni from the University of California, Davis, believes it has a solution designed to replace shoulder slings.
Kaveh Madani, Ph.D. ’09 has been awarded the 2026 Stockholm Water Prize, known as the “Nobel Prize of Water.” Madani is recognized for his global leadership in water security, climate adaptation and the water-energy-food nexus.
Babak Taheri, Ph.D. ’94, has helped shape the technologies behind smartphones, motion sensing and the Internet of Things. Now, he is investing in the next generation of UC Davis engineers by supporting the André Knoesen Teaching Lab in the Department of Electrical and Computer Engineering.
The election recognizes the efforts of Kim Budil, M.S. '88, Ph.D. '94, to advance nuclear deterrence through technical contributions, as well as her outstanding leadership of the Lawrence Livermore National Lab and advice to the United States government.
Recent alum Tim Linke leveraged ties between UC Davis and Lawrence Livermore National Laboratory to conduct his computational research and develop a new framework that couples atom-scale simulations with code that describes the macroscopic world, all within a single simulation.
What if a smartphone could see what the human eye misses? A new UC Davis-designed app uses machine learning to track subtle hand movements during stroke rehabilitation, giving clinicians more specific data to assess recovery and tailor patient care.
