Harrington Seminar on Optical Methods in Quantitative Bio-Imaging: Concept to Application

June 27-28, 2024
Gary L. Thomas Energy Engineering Building
UT Austin Campus

There is a $75 registration fee for all attendees. Please register at the link below by June 13, 2024.


If you are interested in showing at the poster session on Thursday, June 27th please submit your 200 word abstract using this form by May 22nd (deadline extended from May 15th). Final selections for poster presentation will be made by June 1st. Event registration is required to participate in the poster session.



Adela Ben-Yakar, The University of Texas
LEAD Fluorescence Microscopy Performing at 100’s kHz Frames Per Second for 3D-Imaging Flow Cytometry and Brain Imaging

Adela Ben Yakar

Adela Ben-Yakar is Harry Kent Endowed Professor in the Department of Mechanical Engineering at the University of Texas at Austin. She received her Ph.D. from Stanford University in Engineering and completed postdoctoral work at Stanford and Harvard Universities in Physics. Dr. Ben-Yakar is the Fellow of the SPIE, OSA, and AIMBE. She is the recipient of the Fulbright Scholarship, Zonta Amelia Earhart Award, NSF Career Award, Human Frontier Science Program Research Award, NIH Director’s Transformative Award, and Faculty Investment Initiative Program Fellowship. Her research focus is in the areas of ultrafast laser microsurgery, nonlinear imaging endoscopy, high-speed nonlinear microscopy for brain imaging, high-throughput optical and microfluidic systems for high-content screening of model organisms and organoids with application in the areas of nerve regeneration, spine surgery, cancer diagnostics, and neurodegenerative diseases.

Abstract | Three-dimensional, fluorescence imaging methods with 100’s kHz frame rates are needed for high-speed 3D imaging flow cytometry and volumetric imaging of neuronal activity. The frame rates of current fluorescence imaging methods are limited to kHz by the photon budget, slow camera readout, and/or slow laser beam scanners. I will present a new fluorescence imaging method called LEAD (line excitation array detection) microscopy and demonstrate its capability of providing 0.8 million frames per second. This method performs 0.8 MHz line-scanning of excitation laser beam using a chirped signal-driven longitudinal acousto-optic deflector to create a virtual light-sheet, and images the field-of-view with a linear photomultiplier tube array to generate a 66×14 pixel frame each scan cycle. I will present the first implementation of the LEAD microscopy as a blur-free 3D imaging flow cytometer for C. elegans moving at 1 m/s with 3.5-micron resolution and signal-to-background ratios >200. Signal-to-noise measurements indicate LEAD fluorescence microscopy can reach higher resolutions and pixels per frame without compromising frame rates. We are now expanding this method to implement it as two-photon LEAD microscopy (2p-LEAD), by incorporating line-scanning with temporal focusing for improved axial sectioning, and a fast piezo for fast axial scanning. I will present the main concept and results of the preliminary 2p-LEAD microscopy.

Ed Boyden*, Massachusetts Institute of Technology
Optical Tools for Analyzing and Repairing Biological Systems

Ed Boyden

Ed Boyden is Y. Eva Tan Professor in Neurotechnology at MIT, an investigator of the Howard Hughes Medical Institute and the MIT McGovern Institute, and professor of Brain and Cognitive Sciences, Media Arts and Sciences, and Biological Engineering at MIT. He leads the Synthetic Neurobiology Group, which develops tools for analyzing and repairing complex biological systems, such as the brain, and applies them systematically to reveal ground truth principles of biological function and to repair these systems. These inventions include optogenetic tools, which enable control of neural activity with light; expansion microscopy, which enables ordinary microscopes to do nanoimaging; new tools for high-speed imaging of living biological signals and networks; noninvasive brain stimulation strategies that may help with conditions ranging from Alzheimer’s to blindness; and new strategies for inexpensively creating 3-D nanotechnology. He co-directs the MIT Center for Neurobiological Engineering, which aims to develop new tools to accelerate neuroscience progress, and the K. Lisa Yang Center for Bionics, which pioneers transformational bionic interventions across a broad range of conditions affecting the body and mind. He is a faculty member of the MIT Center for Environmental Health Sciences, Computational & Systems Biology Initiative, and Koch Institute.

Abstract | Understanding and repairing complex biological systems, such as the brain, requires technologies for systematically observing and controlling these systems. We are discovering new molecular principles that enable such technologies. For example, we discovered that one can physically magnify biological specimens by synthesizing dense networks of swellable polymer throughout them, and then chemically processing the specimens to isotropically swell them. This method, which we call expansion microscopy, enables ordinary microscopes to do nanoimaging – important for mapping molecules throughout cells, and cells throughout brain circuits. Expansion of biomolecules away from each other also decrowds them, enabling previously invisible nanostructures to be labeled, and seen. As a second example, we discovered that microbial opsins, genetically expressed in neurons, could enable their electrical activities to be precisely controlled in response to light. These molecules, called optogenetic tools, enable causal assessment of how neurons contribute to behaviors and pathological states, and are yielding insights into new treatment strategies for brain diseases. They are also beginning to be used in human patients, in experimental clinical contexts like treating blindness. Finally, we are developing, using new strategies such as robotic directed evolution, fluorescent reporters that enable the precision measurement of signals such as voltage. In order to reveal relationships between different molecular signals within a cell, we are developing spatial and temporal multiplexing strategies that enable many such signals to be imaged at once in the same living cell, using ordinary microscopes, and requiring only fully genetically encoded constructs. We share all these tools freely, and aim to integrate the use of these tools so as to enable comprehensive understandings of neural circuits.

Hafeez Dhalla, Duke University
The Inevitable Convergence of Robotics and OCT


Hafeez Dhalla is an Assistant Research Professor in the Department of Biomedical Engineering at Duke University. He is also the Chief Executive Officer of Theia Imaging, and Vice President of Visualization Systems for Horizon Surgical. At Duke, his research focuses on the application of optical technologies for non-invasive, high-resolution imaging of biological tissues. In particular, his group develops optical coherence tomography (OCT), scanning laser ophthalmoscopy (SLO), light detection and ranging (LiDAR) and other optical imaging technologies for applications in the diagnosis and treatment of disease, particularly diseases of the eye. At Theia, Prof. Dhalla and colleagues are developing handheld OCT devices to bring state-of-the-art diagnostic imaging technologies to neonates, infants, children and other patients who are unable to cooperate for conventional tabletop imaging systems. At Horizon, Prof. Dhalla leads a team of scientists and engineers working to revolutionize ophthalmic microsurgery through advancements in robotics, medical imaging, and artificial intelligence.

Andrew Dunn, The University of Texas at Austin
In Vivo Microscopy of Microvasculature Following Brain Injury

Andrew Dunn

Dr. Dunn's research is focused on developing novel optical imaging techniques for imaging brain function. We seek to integrate innovative photonics and computational techniques and to apply them to research questions in areas such as stroke, migraine, functional mapping during neurosurgery, and Alzheimers disease. In addition we are developing imaging techniques that aid in furthering our understanding of basic neurophysiological mechanisms. One of the techniques we have developed is laser speckle contrast imaging of blood flow, which we have used to dynamically image the cerebral blood flow changes during stroke, migraine and normal brain activation. We collaborate closely with neuroscientists, neurologists and neurosurgeons in the application of these imaging techniques to various problems related to brain function.

Abstract | This talk will describe recent advances in real-time imaging of cerebral blood flow and microvasculature using laser speckle contrast imaging and multiphoton fluorescence microscopy. Technical developments in laser speckle imaging have enabled visualization of blood flow in humans during neurosurgery. In addition, new methods for three-dimensional visualization of microvasculature and neurons now enable longitudinal tracking of vascular morphology down to the single capillary level over several months in preclinical animal models of brain injury.

Elizabeth Hillman, Columbia University
Harnessing the Power of High-Speed 3D Microscopy for Diverse Biomedical Applications


Prof Elizabeth Hillman is a Herbert and Florence Irving Professor at the Zuckerman Mind Brain Behavior Institute, and Professor of Biomedical Engineering and Radiology at Columbia University. She received her undergraduate and PhD degrees in Physics, and Medical Physics and Bioengineering at University College London. She completed post-doctoral training at Massachusetts General Hospital, Harvard Medical School before moving to Columbia in 2006. Her research focuses on the development of optical imaging and microscopy tools, and their applications for studying neural structure and function in the brain across a wide range of species, from worms and flies, to rodents and humans.

Charles Lin*, Massachusetts General Hospital and Harvard University
Imaging the Hematopoietic System: From Blood Stem Cells to Mature Leukocytes

Charles Lin

Dr. Lin has been a faculty member at the Wellman Center for Photomedicine since 1994. He was trained as a spectroscopist and received his PhD in physical chemistry in 1986 from the University of Chicago. Following postdoctoral research at Princeton University, he came to the Massachusetts Eye and Ear Infirmary and later the Tufts/New England Eye Center, where he worked on ophthalmic laser microsurgery, laser eye injury, and also participated in the early development of optical coherence tomography for eye imaging. Dr. Lin continues to have a small research program in ophthalmic imaging and laser microsurgery, but his primary research interest is now focused on developing optical techniques for cell tracking and molecular imaging in live animal models of human diseases. Specifically he and his team members are developing in vivo microscopy and in vivo flow cytometry methods for tracking immune cells, stem cells, and cancer cells, with the goal of improving transplantation, stem cell therapy, and cancer therapy, by understanding cell biologyin vivo. Dr. Lin is also a member of the Center for Systems Biology at Massachusetts General Hospital and an affiliated faculty member at the Harvard Stem Cell Institute and the Harvard/MIT Division of Health Sciences and Technology. He is a fellow of the Optical Society of America.

Abstract | The hematopoietic system is an amazing cell factory that continuously outputs billions of blood cells every hour throughout life. The bone marrow is the primary site of blood cell production (hematopoiesis), and the hematopoietic stem cells (HSCs) are the "eternal" source from which all blood cells are derived. We have developed methods for intravital imaging through the intact bone to track individual HSCs and characterize the bone marrow microenvironment. We have also developed a new spatial transcriptomic technique, called Image-seq (Haase et al, Nat Meth 2022), that enables targeted cell capturing from defined microanatomic locations in the bone marrow under two-photon image guidance for single cell RNA-sequencing. Image-seq thus integrates the spatial and temporal information provided by intravital microscopy with the molecular information provided by single cell sequencing. At the end of the hematopoietic production line, mature blood cells are released from the bone marrow into the circulation. In vivo flow cytometry is a technique originally invented in my laboratory for noninvasive monitoring of fluorescent cells in the circulation. We have now developed a label-free approach for the detection and enumeration of white blood cells in the human microcirculation without the need drawing blood samples, moving the in vivo flow cytometry from preclinical investigation toward clinical translation.

Shalin Mehta, Chan Zuckerberg Biohub San Francisco
Mapping Cellular Dynamics of Viral Infection with Computational Microscopy and Deep Learning

Shalin Mehta

Shalin Mehta developed signal processing algorithms for radars, before earning a Ph.D. in optics at the National University of Singapore from Colin Sheppard’s lab. His Ph.D. research led to elegant mathematical models and new label-free imaging technologies. He then worked at the intersection of technology development and quantitative biology at the Marine Biological Laboratory in Woods Hole as a Human Frontier Science Program (HFSP) Fellow. His postdoctoral research led to novel computational imaging methods to measure the molecular order of the cytoskeleton beyond the resolution limit. At CZ Biohub SF, Mehta leads the Computational Microscopy platform; he and his team integrate optics, inverse algorithms, and machine learning to build computational microscopy platforms that measure the biological architecture and activity with increasing accuracy, precision, and throughput. These technologies are developed and deployed to discover biological mechanisms and therapeutic opportunities in close collaboration with projects, platforms, and partners at CZ Biohub SF.

Abstract | Visualizing the human biology in action requires gentle and scalable approaches of imaging and analyzing the interactions among organelles and cells. One such open problem is mapping and analyzing the remodeling of cells and organelles during viral infection. The key challenge has been that imaging multiple structures in live cell imposes trade-offs among spatial resolution, temporal resolution, number of channels, number of perturbations, and the duration of imaging. I will share our collaborative work on developing correlative microscopy and deep learning methods to resolve these trade-offs and map the dynamics of viral infection.

Amit Meller, Technion -Israel Institute of Technology
Electro-optical sensing of single protein biomarkers in nanopores and nanochannels: towards digital proteomics

Amit Meller

Since 1998 Prof. Meller contributed to the development of nanopore-based DNA sequencing and made key discoveries for its transformation from a theoretical concept to a working technology. Meller’s lab contributions to this field are documented in highly cited research papers, nearly 20 patents, and a dozen review articles in this field. He published some of the early papers in this field (i.e. Meller et. al. PNAS (2000) >1300 citations; Meller et al. PRL (2001) >1100 citations; Wanunu et al. Nat. Nanotechnol (2010) >800 citations, and Reviews (Branton et. al. Nat. Biotechnol. (2010) >3100 citations. In the two decades, Meller’s lab has developed novel materials and methodologies to address fundamental biological processes and for clinical sensing at the single-molecule level. Recently, he developed single molecule mRNA counting method and applied it for early cancer metastasis quantification. This method surpasses the accuracy of the “gold-standard” RT-qPCR opening up new biomedical avenues for cancer diagnosis at early stages. Moreover, the lab showed that this ultra-sensitive single RNA counting approach can provide fast and accurate SARS-Cov-2 diagnostic in compact device, bypassing the need for error-prone PCR amplification. Dr. Meller is also committed to take part in transforming the proteomics field to the single cell level. For this, he has recently been awarded the highly competitive Advanced ERC proposal to develop novel nanopore and nanochannel plasmonics towards single-protein whole proteome profiling. In parallel, last year he was awarded the competitive ISF Precision Medicine award to work on single protein profiling in Age related Macular Degeneration (AMD), as well as early sensing of pancreatic cancer and primary mitochondrial diseases based on liquid biopsies.

Abstract | Nanopores are single molecule biosensors that utilize electrokinetic forces to focus, linearize and detect individual biopolymers, such as DNA and proteins.1 Solid-state nanopores are mechanically robust, versatile sensors, that lend themselves for integration in sophisticated devices designed to processes and detect biological samples. Our lab is pursuing this technology to advance wide range of biomedical needs. Here I will provide several recent examples, including: (i) Threading and imaging of an extremely long genomic DNA (~0.5 Mbp) into solid-state nanopores and engineering the Electro Osmotic Forces (EOF) to facilitate the sensing of extremely short DNA (<50 bp) in sub 5 nm pores. (ii) An amplification-free mRNA quantification sensors to replace RT-qPCR for SARS-CoV-2 and for quantification of the early-stage Colorectal cancer marker MACC1. (iii) On-chip focusing of sub pM nucleic acid samples using Isotacophoresis (ITP) for an efficient single molecule counting. Moving beyond nucleic acids, I will discuss our latest efforts towards the use of electrophoretic single protein molecule separation by mass/charge ratio in sub-wavelength, nanometric channels.2,3 Two color sensing and dynamical tracking of dually labelled proteins enable proteins identification using 4D information. This antibody-free sensing methodology permits discrete quantification of a cytokine panel, for the discrimination among viral versus bacterial infections host’s response. Moreover, we show that this method allows identification of close VEGF protein isoforms, with diverse biological role, but can evade immuno sensing. This method can be integrated upstream of the many other single molecule methods including nanopore sensors and fluorosequencing for enhanced, high-throughput proteome profiling.

Seemantini Nadkarni, Massachusetts General Hospital and Harvard University
Wideband Micromechanical Mapping of the Extra-Cellular Matrix Landscape

Seemantini Nadkarni

Seemantini is an Associate Professor at Harvard Medical School, and directs her laboratory at the Wellman Center for Photomedicine at Massachusetts General Hospital. She received her PhD in Medical Biophysics from the University of Western Ontario, Canada. Her doctoral research focused on three-dimensional ultrasound approaches with applications in echocardiography and intracoronary imaging. Following her doctoral work, she completed her post-doctoral fellowship as an NSERC scholar at the Wellman Center for Photomedicine, where she continued her research on intracoronary imaging, and focused on exploring optical strategies to evaluate tissue biomechanics and microstructure.

Francisco Robles, Georgia Institute of Technology
Accessible Optical Imaging Tools for Label-Free Molecular Imaging and 3D Microscopy

Francisco Robles

Dr. Robles is an as an associate professor at the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech & Emory University. His lab focuses on advancing label-free optical imaging technologies to help improve our understanding of biological processes and our ability to identify disease. He earned his doctorate in medical physics at Duke University with Prof. Wax and completed his postdoctoral training in the Department of Chemistry also at Duke with Prof. Warren.

Abstract | Label-free molecular contrast and 3D tomographic imaging capabilities with subcellular spatial resolution are invaluable for many biomedical applications. However, technologies with either of these capabilities are typically complex and expensive, which hinders their widespread use, particularly in clinical settings. Here I will first discuss our recent efforts to enable low-cost and highly sensitive molecular imaging using deep-UV microscopy. Its application to hematology and pathology will be described. Second, I will present quantitative oblique back-illumination microscopy (qOBM), which enables epi-illumination tomographic, quantitative phase imaging in thick scattering samples with nanometer scale sensitivity. QOBM’s unique ability to image thick scattering samples quantitatively, with high speed, low-cost and ease-of-use provides unique advantages for biomedical imaging. Results highlighting this technology’s unique capabilities in areas ranging from regenerative medicine to surgical guidance will be presented.

Melissa Skala, University of Wisconsin-Madison
Autofluorescence Imaging of Immune Cell Metabolism

Melissa Skala

Melissa Skala is the Carol Skornicka Chair at the Morgridge Institute for Research, the Retina Research Foundation Daniel M. Albert Chair and Professor of Biomedical Engineering and Medical Physics at the University of Wisconsin - Madison. She is a fellow of the Professional Society for Optics and Photonics Technology (SPIE), Optica, and the American Institute for Medical and Biological Engineering (AIMBE). Her lab develops biomedical optical imaging technologies for cancer research, cell therapy, and immunology with support from the National Institutes of Health and the National Science Foundation. She serves as an editorial board member at Cancer Research and the Journal of Biomedical Optics. Inventions from her lab are undergoing commercialization through SeLight, LLC. She received her BS from Washington State University, MS from the University of Wisconsin – Madison, and PhD from Duke University.

Abstract | My lab develops non-invasive optical imaging approaches to unravel dynamic relationships between immune cell function and metabolism at a single cell level within living samples. Immune cell function is closely coupled to cell metabolism, and significant heterogeneity exists between individual immune cells. However, current techniques to measure metabolism in single immune cells require sample destruction or the introduction of reporters that may alter the native context. Fluorescence lifetime imaging microscopy of the endogenous metabolic co-enzymes NAD(P)H and FAD, or optical metabolic imaging (OMI), provides intrinsic sources of metabolic contrast within single cells, which can be used to monitor metabolic features of immunity within living systems. I will discuss applications of OMI and machine learning models in T cell manufacturing for adoptive cell transfer therapy in cancer patients. Here, single cell metabolic imaging with OMI provides unique insights into cell subpopulations and manufacturing conditions that improve outcomes for solid tumors.

Tomasz Tkaczyk, Rice University
Technology for Integrated Optical Systems for Biomedical Diagnostics

Tomasz Tkaczyk

Tomasz Tkaczyk specializes in the engineering of high-performance miniature optics and imaging systems for biomedical and life science applications. His projects combine advanced technologies in optics, opto-mechanics, electronics, and software design. For two decades the Tkaczyk lab has focused on developing a wide range of imaging modalities to comprehensively detect, gage and monitor disease at varying tissue depths. These technologies are engineered for performance, portability, and cost-effectiveness to support biomedical and global health needs. Medical imaging modalities have focused on the development of integrated multimodal imaging systems, hyperspectral imaging, and micro and miniature-sized optical components, such as custom 3-D printed lenses, ultra-thin micro-optics for point-of-care diagnostics, and varying styles of objectives to guide microsurgical procedures and small-gage needle biopsies.

James Tunnell, The University of Texas at Austin
Implantable SERS Biosensor for Monitoring Cancer Treatment Response

James Tunnell

James W. Tunnell is a Professor in the Department of Biomedical Engineering at the University of Texas at Austin. He earned a BS in electrical engineering from the University of Texas at Austin and a Ph.D. in bioengineering from Rice University. He received a National Research Service Award from the NIH to support his postdoctoral fellowship at the Massachusetts Institute of Technology. Dr. Tunnell’s research focuses on the broad field of biomedical optics and imaging. He has engaged in projects at the interface of optical instrument development and clinical translation including the areas of laser induced photothermal therapy, laser surgery, optical spectroscopy for noninvasive diagnosis (light scattering, laser induced fluorescence, and Raman spectroscopy), intravital imaging (confocal and multiphoton), molecularly targeted nanomaterials for theranostics, and structured illumination approaches. He is a fellow of the American Institute of Medical and Biological Engineers (AIMBE) and has served in leadership roles for BMES, ASLMS, CLEO, Optica, and SPIE. He has published over 150 refereed journal articles, proceedings papers, and book chapters.

Abstract | Current methods to monitor cancer treatment response largely depend on conventional imaging and/or tumor biopsy, which can be expensive, infrequent, and delayed. In an effort to provide an assessment of treatment response at the earliest timepoint, we have developed a minimally invasive, implantable biosensor that measures biomolecular profiles. The biosensor consists of an injectable hydrogel containing gold nanostars that forms a solid after injection. The hydrogel acts to immobilize the nanostars just below the skin surface where they are exposed to biomolecules within the interstitial fluid. A handheld fiber optic probe placed on the skin surface is used to acquire surface enhanced Raman spectra (SERS) from the biosensor. Machine learning is used to interpret the SERS signals and indicate treatment response. Biosensor performance was tested using in vitro samples (cancerous and healthy prostate cancer cell lines), preclinical blood serum samples (healthy and prostate cancer bearing mice), and clinical human blood plasma samples (healthy and prostate cancer patients). Machine learning models trained on the biosensor SERS signals were able to discriminate healthy and cancerous samples with high accuracy. In vivo performance of the biosensor was validated in a preclinical model of prostate cancer. The biosensor forms a solid spheroid of about 0.5 cm in diameter under the skin where it persists for at least 90 days. The SERS signal can be measured through the skin surface, and early timepoints can discriminate mice with disease from those without with high accuracy. Confounding factors were observed in measuring the SERS signals through the skin which inform future designs. This approach shows promise for providing a minimally invasive approach to monitor patients for disease recurrence after treatment.

Laura Waller*, University of California, Berkeley
Computational Microscopy with Dynamic Samples

Laura Waller

Laura Waller leads the Computational Imaging Lab, which develops new methods for optical imaging, with optics and computational algorithms designed jointly. She holds the Ted Van Duzer Endowed Professorship and is a Senior Fellow at the Berkeley Institute of Data Science (BIDS), with affiliations in Bioengineering and Applied Sciences & Technology. Laura was a Postdoctoral Researcher and Lecturer of Physics at Princeton University from 2010-2012 and received BS, MEng and PhD degrees from MIT in 2004, 2005 and 2010, respectively. She is a Moore Foundation Data-Driven Investigator, Bakar fellow, Distinguished Graduate Student Mentoring awardee, NSF CAREER awardee, Chan-Zuckerberg Biohub Investigator, SPIE Early Career Achievement Awardee and Packard Fellow.

Abstract | Computational imaging involves the joint design of imaging system hardware and software, optimizing across the entire pipeline from acquisition to reconstruction. This talk will describe new microscopes and space-time algorithms that enable 3D or super-resolution fluorescence microscopy and phase measurement with high resolution on dynamic samples. Traditional model-based image reconstruction algorithms work together with neural networks to optimize the inverse problem solver and the data capture strategy in order to account for sample motion during the capture time of a multi-shot computational imaging method.

Alexandra Walsh, Texas A&M University
Machine Learning to Enhance Metabolic Specificity of Autofluorescence Lifetime Imaging

Alexandra Walsh

Alex Walsh is an assistant professor in the Biomedical Engineering Department at Texas A&M University. She received her MS and PhD degrees in Biomedical Engineering from Vanderbilt University where she received education and training in biophotonics, multiphoton microscopy, label-free microscopy, quantitative image analysis, and laser tissue interactions. She completed her post-doctoral training at the Air Force Research Lab studying the biophysical effects of infrared light. Currently, her lab seeks to improve human health through the development and application of label-free optical technologies. Her work is supported by the NIH NIGMS through a Maximizing Investigator’s Research Access (MIRA, R35) award, the Air Force Office of Scientific Research, the Cancer Prevention and Research Institute of Texas, and the Chan Zuckerberg Initiative.

Abstract | Cellular metabolism, the process by which cells generate energy, is dysregulated in many diseases and pathologies including cancer, neurodegeneration, and diabetes. Current biochemical assays for metabolism are limited to either cell-destructive protocols, such as mRNA analysis, or measure readouts from collective cell populations, such as oxygen consumption assays. Yet metabolic measurements with high resolution of live cells are important since cellular heterogeneity is known to drive disease progression, cancer metastasis, and resistance to therapies. Fluorescence lifetime imaging of the metabolic coenzymes, reduced nicotinamide adenine (phosphate) dinucleotide (NAD(P)H) and oxidized flavin adenine dinucleotide (FAD), provides a label-free method to interrogate cellular metabolism. Both coenzymes, NAD(P)H and FAD, exist in either a free or protein-bound configuration, each of which has a distinct fluorescence lifetime. However, correlations between lifetime measurements and metabolic phenotypes have remained elusive. We are creating and testing machine learning models that can identify metabolic phenotypes of individual cells from fluorescence lifetime metrics and images. Additionally, we are increasing the accessibility of fluorescence lifetime imaging by creating improved analysis tools and automated methods for single-cell segmentation of autofluorescence images.

Junjie Yao, Duke University
From Technology to Discovery: Deeper, Faster, and Colorful Photoacoustic Imaging in Life Sciences

Junjie Yao

Dr. Junjie Yao is an Associate Professor of Biomedical Engineering at Duke University, with a secondary appointment at Duke Neurology. He is also affiliated with the Duke Cancer Institute, Duke Institute of Brain Sciences, and Fitzpatrick Institute for Photonics. Dr. Yao earned his B.S. (2006) and M.S. (2008) degrees in Biomedical Engineering from Tsinghua University in Beijing, China. He further pursued his Ph.D. in Biomedical Engineering at Washington University in St. Louis, and completed his doctoral studies in 2013 and postdoctoral training in 2016, both under the mentorship of Dr. Lihong V. Wang. Since joining Duke University in 2016, Dr. Yao's research has focused on the development of photoacoustic tomography (PAT), ultrasound imaging, and ultrasound bioprinting technologies for applications in the life sciences. His pioneering work involves the integration of light and sound to enable high-speed functional brain imaging, deep-tissue molecular imaging, early-stage cancer detection, and through-tissue ultrasound printing. Dr. Yao’s research have been supported by grants from organizations such as the National Institutes of Health (NIH), National Science Foundation (NSF), American Heart Association (AHA), and Chan Zuckerberg Initiative (CZI). Dr. Yao's contributions to the field of biomedical engineering have been recognized with several notable awards, including the 2019 IEEE Photonic Society Young Investigator Award, the 2021 National Jewish Fund Faculty Fellowship, the 2022 NSF CAREER Award, and the 2023 Rising Stars of Light Award. In 2023, Dr. Yao was elected as a Fellow of OPTICA (formerly OSA) and senior member of SPIE ‘for breaking the limits of photoacoustic imaging in resolution, speed, and functionality, and translating the technical innovations to theragnostic impacts’.

Abstract | Photoacoustic imaging (PAI) is an increasingly powerful technique for multi-scale anatomical, functional, and molecular imaging by acoustically detecting the optical absorption contrast in biological tissues. In PAI, a short-pulsed laser beam is used to illuminate the tissue, generating a tiny but rapid temperature rise and resulting in the emission of ultrasonic waves through thermoelastic expansion. The wideband ultrasonic waves are then detected to create high-resolution tomographic images that map the tissue's optical absorption. In my talk, I will focus on several technological advancements in PAI that have collectively enabled fast, deep, and high-sensitivity biomedical applications and discoveries in life sciences, such as functional stroke imaging, drug testing, cancer detection, and interventional therapy. First, PAI has overcome the penetration limit by utilizing advanced internal light delivery techniques, allowing for super-deep (>10 cm) imaging. This breakthrough has extended the applicability of PAI to internal organ imaging in large animal models and humans. Second, innovative scanning technologies and deep-learning models have significantly accelerated PAI, enabling imaging speeds that are more than 1000 times faster while maintaining a large field of view and high spatial resolution. This enhancement facilitates the monitoring of highly dynamic biological processes at the microscopic scale, such as functional brain activities and glassfrog transparency. Third, through the use of novel fabrication technologies in optics and acoustics, miniaturized PAI systems have been developed. These handheld, wearable, and head-mounted imaging devices offer high spatial-temporal resolutions and high throughput, providing greater flexibility and accessibility in imaging applications. Lastly, PAI has greatly benefited from the genetically-encoded switchable or tunable near-infrared photoacoustic-specific probes. By incorporating these probes, the sensitivity and specificity of PAI have been improved by more than 1000 times, enabling highly sensitive detection of malignant cancer, tissue hypoxia, and neuronal activities. By highlighting these technological advancements, my talk aims to update the recent progress made in PAI and its potential for a wide range of biomedical applications in life sciences.

Dvir Yelin, Technion - Israel Institute of Technology
Toward Noninvasive Blood Count

Dvir Yelin

Dvir Yelin is an Associate Professor at the Department of Biomedical Engineering and the Lorry Lokey Interdisciplinary Center for Life Sciences and Engineering at the Technion – Israel Institute of Technology. He received his B.Sc. in physics from the Hebrew University in Jerusalem, Israel, and his M.Sc. and Ph.D. in physics from the Weizmann Institute of Science, Israel. Following successful completion of his Ph.D. studies, Yelin joined the Wellman Center for Photomedicine as a postdoctoral fellow and an Instructor at the Harvard Medical School. Concurrently, Yelin was a Research Fellow at Massachusetts General Hospital in Boston. Since arriving at the Technion in 2007, the Yelin’s group employs novel optical systems as tools for addressing problems in medicine and biology.

Abstract | Measuring the composition of a patient blood is often the first step in clinical diagnosis, and is commonly performed by extracting blood samples for laboratory analysis. This procedure is invasive and painful, which is often problematic for chronic patients, kid and infants, and even for people with needle phobia. Moreover, in remote areas with poor sanitary conditions, blood tests may cause infections and require long waits for the results. To address these challenges, we have recently developed a novel approach for high-speed microscopy, termed spectrally encoded flow cytometry (SEFC), that allows noninvasive confocal microscopy of individual blood cells flowing within small blood vessels in patients. We have recently demonstrated the feasibility of this technology to image and count both red and white blood cells in vivo, and we are currently developing this approach, aiming to offer a commercial system that performs noninvasive, pain-free blood tests at the point of care.

*Participating as part of the Texas ECE O'Donnell Endowment Lecture Series


This one and a half day symposium is made possible by the Donald D. Harrington Fellows Program. The theme of the symposium is applications in bio-imaging that include a significant portion of optical innovation. Immerse yourself in an informal yet intellectually stimulating atmosphere designed to encourage vibrant discussions and research opportunities. Our single-track meeting will consist of 17 distinguished invited speakers, as well as students, postdocs, and researchers. Additionally, we will have an engaging poster session, to enable young scientists to present their work and add further depth to the exchange of ideas and insights.

This event is generously supported by the University of Texas at Austin’s Harrington Fellows Program, as well as the Walker Department of Mechanical Engineering, the Chandra Family Department of Electrical and Computer Engineering, and the Department of Biomedical Engineering.


Yoav Shechtman, Technion - Israel Institute of Technology and The University of Texas at Austin

Yoav Shechtman

Yoav Shechtman is currently a Harrington faculty fellow in the Walker Department of Mechanical Engineering at the University of Texas at Austin, TX. He is an Associate Professor of Biomedical Engineering at the Technion, Israel Institute of Technology, and he holds a B.Sc. in Electrical Engineering and Physics (2007) and a Ph.D (2013), all from the Technion. During 2013-2016 he was a postdoctoral scholar at Stanford University. Yoav’s interdisciplinary group focuses on method-development mostly motivated by observing life on the nanoscale, with research topics ranging from optical design through machine learning to molecular biology. Recent awards and recognition include the 2018 Early Career Award of the International Association for Medical and Biological Engineering (IAMBE), the 2018 ERC starting grant, the 2019 Uzi and Michal Halevy Award for Innovative Applied Engineering ,the 2020 International Union for Pure and Applied Biophysics (IUPAB) Young Investigator Prize and Medal, the 2020 Morton and Beverley Rechler Prize for Excellence in Research, the 2021 Krill Prize for Excellence in Scientific Research, and the 2024 Hershel Rich Innovation award.

Shwetadwip Chowdhury, The University of Texas at Austin

Chowdhury Shwetadwip

Shwetadwip Chowdhury is an Assistant Professor and Fellow of the Jack Kilby/Texas Instruments Endowed Faculty Fellowship in Computer Engineering in the Department of Electrical and Computer Engineering at the University of Texas at Austin. His research interests are in developing next generation optical imaging technologies for applications in science and medicine. A key emphasis in his work is the joint design of novel optical imaging systems and advanced computational frameworks. This co-design of hardware and software enables imaging capabilities not possible in traditional optical imaging systems.

Previously, he was a NIH Ruth L. Kirschstein NRSA Postdoctoral Fellow at University of California Berkeley, in the Department of Electrical Engineering and Computer Sciences. Before that, he received his Ph.D. and B.S. degrees from the Department of Biomedical Engineering at Duke University.