Lihong Wang is Bren Professor of Medical and Electrical Engineering at
Caltech. Published 615 journal articles (h-index = 165, citations = 117K, #1
most cited in optics according to Stanford/Elsevier). Delivered 630
keynote/plenary/invited talks. Published the first functional photoacoustic
CT, 3D photoacoustic microscopy, and light-speed compressed ultrafast
photography (the world’s fastest camera). Served as Editor-in-Chief of the
Journal of Biomedical Optics. Received Goodman Book Award; NIH Outstanding
Investigator, NIH Director’s Transformative Research, and NIH Director’s
Pioneer Awards; Optica Mees Medal and Feld Award; IEEE Technical Achievement
and Biomedical Engineering Awards; SPIE Chance Award; IPPA Senior Prize;
honorary doctorate from Lund University, Sweden. Inducted into the National
Academy of Engineering.
We have developed photoacoustic tomography (PAT) for deep-tissue imaging, offering in vivo functional, metabolic, molecular, and histologic imaging from organelles to entire organisms. Additionally, we developed light-speed compressed ultrafast photography (CUP), capable of recording at 219 trillion frames per second. CUP can capture the fastest phenomena, such as light propagation, and can also slow down to record events like neural conduction. Further, our research extends to quantum entanglement for imaging.
PAT combines optical and ultrasonic waves, overcoming the optical diffusion limit (~1 mm) with centimeter-scale deep penetration, high ultrasonic resolution, and optical contrast. Applications include early cancer detection and brain imaging. The annual PAT conference, a part of SPIE’s Photonics West, has been a significant event since 2010.
CUP, with a single exposure, captures transient events on a femtosecond scale. Unlike other ultrafast imagers requiring active illumination, CUP is receive-only and can be paired with various front optics, from microscopes to telescopes, facilitating diverse applications in fundamental and applied sciences, including biology and cosmophysics.
Quantum imaging utilizing Heisenberg scaling enhances spatial resolution linearly with the number of quanta, outperforming the standard quantum scaling’s square-root improvement.