2023 / 03 / 15 (三) 14:00-15:30
講者： Wei-Chuan Shih, Ph.D. / Electrical & Computer Engineering University of Houston
講題： Nanobiophotonic liquid biopsy
Abstract: Light-matter interactions can provide rich compositional information from various samples in a non-invasive fashion. Our laboratory has developed opto-analytical spectroscopy, imaging, and sensing technologies to address unmet needs across various biological length scales including molecules, vesicles, cells, and tissue. The central innovations in our work include nano and microengineering, imaging and spectroscopy instrumentation, and machine learning techniques. I will discuss some plasmonics-related examples in this seminar. Harnessing localized surface plasmons (LSP) and coupling modes, we have engineered enhanced light-matter interactions near nanostructured surfaces for molecular sensing, catalysis, photothermal manipulation, and single extracellular vesicle profiling. Detection of blood circulating biomarkers, known as “liquid biopsy”, can potentially increase accuracy by revealing the “invisible”. I will discuss the potential of our nanophotonic technologies in liquid biopsy.
Biography: Wei-Chuan Shih is Cullen Professor of Electrical & Computer Engineering, Biomedical Engineering, Materials Science & Engineering, and Chemistry at the University of Houston. He earned his Ph.D. from MIT in 2007 under the tutelage of Prof. Michael S. Feld and joined University of Houston in 2009 after a stint as Schlumberger research fellow. He received MIT Martin Fellowship, NSF CAREER Award, NASA Early CAREER Faculty Award, and several research and innovation awards at UH. He is SPIE Fellow and SM of NAI, Optica, and IEEE. He has published ~80 journal papers and holds 18 granted US patents. He is Associate Editor for Optica Optics Express and SPIE Journal of Nanophotonics, and Optica Applied Optics previously. His research interests are biophotonics, nanobiophotonics, imaging & spectroscopy, micro/nanofabrication, and machine learning. His current research focus is on exosome-based cancer and Alzheimer’s disease diagnostics supported by NIH and DoD.