News & Announcements

We are happy to announce the release of our new physics-inspired low-light image enhancement algorithm VEViD to PhyCV. VEViD, or Vision Enhancement via Virtual Diffraction and Coherent Detection, was recently introduced in a publication in eLight. The algorithm...

We are proud to introduce a powerful low-light enhancement algorithm, VEViD. It builds on more than two decades of research in optical physics in our laboratory and has direct applications in augmented reality, night-time driving, biology, and space exploration. The...

Check out our latest publication entitled "Physics-AI Symbiosis" that just appeared as an invited paper in Machine Learning: Science and Technology! As a mix of perspective and review, the paper explores emerging ideas in which physics is blended with AI to extend the...

We are happy to announce the release of the first Physics-inspired Computer Vision Library: PhyCV. PhyCV has a new class of computer vision algorithms that emulates the propagation of light through a physical medium with natural and engineered diffractive properties...

We are happy to announce that we have made public the code for our latest physics-inspired algorithm which detects edges and their orientations in digital images at various scales. The algorithm, called PAGE, is based on the diffraction equations of optics and...

Professor Bahram Jalali has been elected to the National Academy of Engineering for his contributions to silicon photonics, high time-resolution scientific instruments, and biomedical imaging. For details, please refer to the official announcement from Samueli School...

We are pleased to report a successful AI and Optical Data Science conference last week in San Francisco. This is a symposium we organize every year at the SPIE Photonics West, the largest optics conference in North America. Despite the pandemic, the sessions were well...

Milestones in Silicon Photonics by the Jalali-Lab

Time-of-flight 3D imaging is the key technology in autonomous cars, robotics, and remote sensing. Building on more than 20 years of research on photonic time stretch data acquisition, our laboratory recently demonstrated the world’s fastest time of flight 3D camera....

Our recent work "Deep Cytometry: Deep learning with Real-time Inference in Cell Sorting and Flow Cytometry" which shows that high-throughput label-free cell classification with high accuracy can be achieved through a combination of time stretch quantitative phase...