Plenary Speakers |
Prof. Joseph Rosen School of Electrical and Computer Engineering Ben-Gurion University of the Negev, Israel | |
| Speech Title: Advanced imaging tasks using phase-only spatial light modulators | |
Abstract: Phase-only
spatial light modulators (SLMs) positioned in the aperture of optical imaging
systems can extend the missions of these systems. This review briefly describes
the evolution of SLM-aided imaging systems from the well-known Fresnel
incoherent correlation holography recorder to the most recent versions of
interferenceless coded aperture holography systems. | |
About the Speaker:
Joseph Rosen is the Benjamin H. Swig Professor of Optoelectronics in the School of
Electrical and Computer Engineering, Ben-Gurion University of the Negev,
Israel. He received his BSc, MSc, and DSc degrees in electrical
engineering from the Technion - Israel Institute of Technology. He is a fellow
of OPTICA (formerly The Optical Society of America, OSA) and SPIE (The
International Society for Optics and Photonics). His
research interests include holography, image processing, optical microscopy,
diffractive optics, interferometry, biomedical optics, optical computing, and
statistical optics. He has coauthored more than 300 scientific journal papers,
book chapters, and conference publications.
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Prof.
Saulius JUODKAZIS
Professor and Deputy Director of the Optical Sciences Centre at Swinburne University of Technology, Melbourne, Australia | |
| Prof.
YongKeun (Paul) Park KAIST, Daejeon, 3414, South Korea | |
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Speech Title: Holotomography and artificial intelligence: label-free
3D imaging, classification, and inference of live cells, tissues, and organoids
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Abstract:
Holotomography (HT) is a powerful label-free
imaging technique that enables high-resolution, three-dimensional quantitative
phase imaging (QPI) of live cells and organoids through the use of refractive
index (RI) distributions as intrinsic imaging contrast1-3. Similar
to X-ray computed tomography, HT acquires multiple two-dimensional holograms of
a sample at various illumination angles, from which a 3D RI distribution of the
sample is reconstructed by inversely solving the wave equation.
By combining label-free and quantitative 3D imaging
capabilities of HT with machine learning approaches, there is potential to
provide synergistic capabilities in bioimaging and clinical diagnosis. In this
presentation, we will discuss the potential benefits and challenges of
combining QPI and artificial intelligence (AI) for various aspects of imaging
and analysis, including segmentation, classification, and imaging inference3-6.
We will also highlight recent advances in this field and provide insights on future
research directions. Overall, the combination of QPI and AI holds great promise
for advancing biomedical imaging and diagnostics.
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About the Speaker:
YongKeun (Paul) Park is Endowed Chair Professor of
Physics at KAIST. He earned a Ph.D. in Medical Science and Medical Engineering
from Harvard-MIT Health Science and Technology. Dr. Park’s area of research is
optics, holography, and biophysics. He has published +160 peer-reviewed papers
with +11K citations, including 4 Nat Photon, 4 Nat Comm, 4 PRL, 6 PNAS papers.
He is a Fellow of the Optical Society of America (OSA) and the Society of Photo-Optical
Instrumentation Engineers (SPIE). He received the Medal of Honour in Science and Technology (President of South Korea) and the JinkiHong Creative Award. Two
start-up companies with +60 employees have been created from his research
(Tomocube, The.Wave.Talk).
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Prof.
Aydogan
Ozcan Electrical and Computer
Engineering Department, Bioengineering Department, California NanoSystems
Institute , UCLA, University of California,
Los Angeles, CA
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Speech Title:
Programming Light Diffraction for Information
Processing and Computational Imaging
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Abstract:
I
will discuss the integration of programmable diffraction with digital neural
networks. Diffractive optical networks are designed by deep learning to
all-optically implement various complex functions as the input light diffracts
through spatially engineered surfaces. These diffractive processors integrated
with digital neural networks have various applications, e.g., image analysis,
feature detection, object classification, computational imaging and seeing
through diffusers, also enabling task-specific camera designs and new optical
components for spatial, spectral and temporal beam shaping and
spatially-controlled wavelength division multiplexing. These deep
learning-designed diffractive systems can broadly impact (1) optical
statistical inference engines, (2) computational camera and microscope designs
and (3) inverse design of optical systems that are task-specific. In this talk,
I will give examples of each group, enabling transformative capabilities for
various applications of interest in e.g., autonomous systems, defense/security,
telecommunications as well as biomedical imaging and sensing.
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About the Speaker:
Dr. Aydogan Ozcan is the Chancellor’s Professor and
the Volgenau Chair for Engineering Innovation at UCLA and an HHMI Professor
with the Howard Hughes Medical Institute. He is also the Associate Director of
the California NanoSystems Institute. Dr. Ozcan is elected a Member of the
National Academy of Engineering (NAE) and a Fellow of the National Academy of
Inventors (NAI) and holds >85 issued/granted patents in microscopy,
holography, computational imaging, sensing, mobile diagnostics, nonlinear optics
and fiber-optics, and is also the author of one book and the co-author of
>1200 peer-reviewed publications in leading scientific journals/conferences.
Dr. Ozcan received major awards, including the Presidential Early Career Award
for Scientists and Engineers (PECASE), International Commission for Optics ICO
Prize, Dennis Gabor Award (SPIE), Joseph Fraunhofer Award & Robert M.
Burley Prize (Optica), Keith Terasaki Innovation Award, SPIE Biophotonics
Technology Innovator Award, Rahmi Koc Science Medal, SPIE Early Career
Achievement Award, Army Young Investigator Award, NSF CAREER Award, NIH
Director’s New Innovator Award, Navy Young Investigator Award, IEEE Photonics
Society Young Investigator Award and Distinguished Lecturer Award, National
Geographic Emerging Explorer Award, National Academy of Engineering The
Grainger Foundation Frontiers of Engineering Award and MIT’s TR35 Award for his
seminal contributions to computational imaging, sensing and diagnostics. Dr.
Ozcan is elected Fellow of Optica, AAAS, SPIE, IEEE, AIMBE, RSC, APS and the
Guggenheim Foundation, and is a Lifetime Fellow Member of Optica, NAI, AAAS,
SPIE and APS. Dr. Ozcan is also listed as a Highly Cited Researcher by Web of
Science, Clarivate.
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