Jason W. Fleischer

Jason W. Fleischer is a Professor of Electrical and Computer Engineering at Princeton University and an Associated Faculty member in the Princeton Materials Institute (PMI). His research spans multiple disciplines at the intersection of physics, engineering, and computational science.

Dr. Fleischer's research focuses on nonlinear optics within the broader context of general wave physics. His work emphasizes propagation problems that are universal to wave systems, leveraging optical systems for controlled input and direct output imaging. Key areas include:

• Optical hydrodynamics, where nonlinear light propagation is described using fluid flow equations
• Statistical physics using incoherent light treated as a photonic plasma
• Quantum optics with megapixel camera-based imaging systems
• Computational imaging techniques for microscopy and biomedical applications
• Machine learning approaches for medical diagnostics, particularly for COVID-19 analysis
• Microfluidic microscopy for high-speed 3D biological imaging

His research has identified significant trends in using wave physics principles across multiple domains. Fleischer's group has demonstrated how nonlinear wave mixing can enable higher resolution, increased field of view, and improved signal-noise properties. Recent work has focused on applying physics-informed machine learning to medical imaging, particularly for COVID-19 diagnosis and treatment planning, with AI systems examining patient data holistically through chest x-rays, ultrasound, radiology reports, and blood tests.

Dr. Fleischer has received numerous scientific honors:

• Fellow of Optical Society of America (2012)
• Department of Energy Plasma Physics Junior Faculty Award (2008)
• Emerson Electric Company Lawrence Keys '51 Faculty Advancement Award (2007)
• Lady Davis Postdoctoral fellowship, Israel (2001-2004)
• University of California Regents Fellowship (1994-1999)
• General Atomics Plasma Fellowship (1994-1999)

Dr. Fleischer has advised over 25 graduate students and postdoctoral researchers who have established successful careers in academia and industry. His research has been supported by various funding agencies enabling interdisciplinary work spanning physics, engineering, and medical applications. Current advisees include Tomo Kiramura-Shimobayashi (postdoc) and graduate students Xiaohang Sun, Yaotian Wang, Mohammad Tariqul Islam, and Shaurya Aarav.

He leads the Imaging Physics Group at Princeton, which integrates computation, materials science, and digital technology to revolutionize imaging systems. The group's work often produces counter-intuitive results, such as sharper pictures through defocusing and improved signal detection by adding noise, with applications in biomedical optics and materials science.