
Katsuo Kurabayashi
· Mechanical and Aerospace Engineering Department ChairVerifiedNew York University · Mechanical and Aerospace Engineering
Active 1997–2026
About
Katsuo Kurabayashi is a Professor of Mechanical and Aerospace Engineering at NYU Tandon School of Engineering. Prior to his appointment at NYU, he was a Professor of Mechanical Engineering and Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor. His research expertise includes micro/nanoscale biosensors, biochemical reactors, and analytical instrumentation utilizing nanofabrication technology, microfluidic devices, semiconductor processing for infectious disease screening, human-health environmental monitoring, and protein engineering. His recent work focuses on integrating scientific knowledge and engineering principles at a minuscule scale, approximately 1/1000-1/10,000th the size of a human hair diameter, with the goal of addressing healthcare and life sciences requirements through an interdisciplinary approach. His research group has pioneered a microfluidic biosensor platform that enables rapid diagnostics and treatment for critically ill children in the Pediatric Intensive Care Unit (PICU), particularly those experiencing life-threatening inflammatory reactions due to infection, injury, surgery, or cancer immunotherapy. Dr. Kurabayashi's research has been funded by various agencies including NSF, DoD, NIH, NASA, IARPA, EPA, and Cancer Research Institute, as well as industry grants from Ford Motor Company and Agilent Technologies. He holds a B.S. in Precision Engineering from the University of Tokyo and M.S. and Ph.D. degrees in Materials Science and Engineering from Stanford University. He has authored nearly 200 peer-reviewed papers, with several featured as high-quality or cover articles in prominent journals, and has delivered over 60 research talks as an invited or keynote speaker at leading academic and professional conferences. Dr. Kurabayashi has received numerous awards, including the NSF CAREER Award, the Robert Caddell Memorial Award, and the Wise-Najafi Prize for Engineering Excellence in the Miniature World, and is a Fellow of the Royal Society of Chemistry and the American Society of Mechanical Engineering.
Research topics
- Computer Science
- Artificial Intelligence
- Medicine
- Immunology
- Biology
- Computational biology
- Telecommunications
- Pathology
- Materials science
- Genetics
- Nanotechnology
Selected publications
Results in Materials · 2026-02-10 · 1 citations
articleOpen accessSenior authorConcrete is the second most consumed material globally, and Portland cement production contributes about 8% of CO 2 emissions, emphasizing the need for developing low-carbon binders for structural and additive manufacturing applications. This study proposes a standardized approach for evaluating geopolymer concrete (GPC) mix designs using a preset binder combined with industrial and agricultural waste.Crushed and uncalcined rice husk powder was incorporated to reduce embodied energy and density while assessing its effects on reactivity and performance. Compressive strength testing, Scanning electron Microscope (SEM) , and energy-dispersive X-ray spectroscopy (EDS) analyses were used on precursor and cured samples to examine mechanical behavior and microstructural features. The mixture containing Uncalcined Rice Husk, industrial waste, and water achieved the highest compressive strength (30.45 MPa). Results demonstrate that combining industrial waste with rice husk can produce high-strength, low-carbon GPC composites suitable for additive manufacturing and construction.
A Human Lymph node-on-a-Chip for Personalized Evaluation of Vaccine Immunogenicity
Research Square · 2026-03-30
preprintOpen accessCancer-on-a-chip for precision cancer medicine
Lab on a Chip · 2025-01-01 · 23 citations
reviewOpen accessMany cancer therapies fail in clinical trials despite showing potent efficacy in preclinical studies. One of the key reasons is the adopted preclinical models cannot recapitulate the complex tumor microenvironment (TME) and reflect the heterogeneity and patient specificity in human cancer. Cancer-on-a-chip (CoC) microphysiological systems can closely mimic the complex anatomical features and microenvironment interactions in an actual tumor, enabling more accurate disease modeling and therapy testing. This review article concisely summarizes and highlights the state-of-the-art progresses in CoC development for modeling critical TME compartments including the tumor vasculature, stromal and immune niche, as well as its applications in therapying screening. Current dilemma in cancer therapy development demonstrates that future preclinical models should reflect patient specific pathophysiology and heterogeneity with high accuracy and enable high-throughput screening for anticancer drug discovery and development. Therefore, CoC should be evolved as well. We explore future directions and discuss the pathway to develop the next generation of CoC models for precision cancer medicine, such as patient-derived chip, organoids-on-a-chip, and multi-organs-on-a-chip with high fidelity. We also discuss how the integration of sensors and microenvironmental control modules can provide a more comprehensive investigation of disease mechanisms and therapies. Next, we outline the roadmap of future standardization and translation of CoC technology toward real-world applications in pharmaceutical development and clinical settings for precision cancer medicine and the practical challenges and ethical concerns. Finally, we overview how applying advanced artificial intelligence tools and computational models could exploit CoC-derived data and augment the analytical ability of CoC.
Piezo1-mediated mechano-energetics regulate CAR T cell function
Research Square · 2025-10-23 · 1 citations
preprintOpen accessbioRxiv (Cold Spring Harbor Laboratory) · 2025-05-15
preprintOpen accessSenior authorTime-course monitoring of blood biomarkers with rapid turnaround has the potential to revolutionize the diagnosis, stratification of phenotypes, and therapeutic/prognostic approaches for various acute inflammatory diseases in both clinical and preclinical studies. Current approaches, however, are hampered by slow turnaround times and large sample volume requirements, limiting the exploration of disease mechanisms and therapeutic strategies. Here, we developed a microfluidic digital ELISA platform prototype, combining single-molecule counting with whole blood assay capability for the first time from small animal models. This platform is automated and enables repeated, rapid biomarker monitoring with just 3.5 μL of whole blood collected from the tail. Our platform demonstrated high sensitivity and multiplexity, allowing real-time cytokine profiling within a 2-hour turnaround. Using a murine sepsis model, we achieved precise temporal monitoring of cytokine levels, demonstrating prognostic capability by correlating early-stage cytokine levels with a liver-injury biomarker. This microfluidic platform enables high temporal resolution and rapid monitoring of biomarker dynamics in a single mouse using freshly collected whole blood, significantly reducing the number of animals needed for preclinical studies. This technology has strong potential to transform ICU therapeutic strategies and preclinical research, enabling personalized treatment based on real-time biomarker profiles.
Advanced Science · 2025-05-01
articleOpen accessTherapy for PA‐Induced Acute Lung Injury In article number 2413253, Xin Yu, Yujing Song, Katsuo Kurabayashi, Yongqing Li, and co‐workers discover a new chemical modification site catalyzed by an enzyme called PAD2 on the intracellular protein, NF‐κB p65, which modulates immune cell (macrophage) functions. Using nanoparticle therapy to block PAD2 significantly reduced inflammation and improved outcomes in acute lung injury during bacterial infections. [Image: see text]
bioRxiv (Cold Spring Harbor Laboratory) · 2025-05-22
preprintOpen accessSenior authorAbstract Protein secretion underpins diverse physiological processes in cell-to-cell communication, tissue homeostasis, and the onset of diseases. Mapping the secretomes from paired cells provides avenues for understanding their interactions. However, prevailing approaches yield only semi-quantitative endpoint data, lacking real-time and quantitative information. Here, we present real time spatiotemporal imaging of extracellular secretions from individual cells via a high-throughput integrative biosensing nanoplasmonic array (iBNA) with a microfluidic chamber. The self-assembled iBNA, composed of precisely arranged gold nanostructures and functionalized with aptamer receptors, enhances plasmonic resonance and significantly improves the spatiotemporal resolution and specificity of interleukin-6 (IL-6) imaging, surpassing gold-standard techniques. The molecular recognition of iBNA, and sensing mechanism exploits biomolecular surface binding-induced localized plasmonic resonance shifts, correlating with cytokine concentration and enabling optoelectronic detection of the transmitted light. Using this approach, we achieve spatiotemporally resolved visualization of IL-6 secretion dynamics at the single-cell level and unveil the temporal and polarized variation of cell-cell communications. This transformative platform holds significant potential to advance immunological research, cellular biology, and diagnostic applications for infectious diseases by enabling unprecedented insights into the spatiotemporal patterns of protein secretion in individual cells.
Biotechnology Advances · 2025-05-03 · 7 citations
reviewOpen accessbioRxiv (Cold Spring Harbor Laboratory) · 2025-09-17
preprintOpen accessSenior authorAbstract Maintaining blood glucose within a physiologically safe range is critical for people with diabetes, as deviations can lead to acute or chronic complications. Hypoglycemia, in particular, represents an immediate threat and requires prioritized mitigation in autonomous insulin delivery systems. This paper introduces a risk-aware hybrid nonlinear model predictive control (NMPC) framework that combines data-driven uncertainty quantification with formal safety assurance through control barrier functions (CBFs). To account for key uncertainties, such as physiological time delays, unannounced meals, and stress-induced glucose variability, Gaussian processes (GPs) are employed as probabilistic estimators. The proposed method dynamically monitors glucose and regulates insulin injection to enforce safe glucose level control by preventing hypoglycemia. The proposed framework is evaluated using validated physiological simulators for various realistic scenarios. The results show a robust performance in maintaining safety under high uncertainty, preparing a foundation for translation into next phase of our research as safe autonomous diabetes management systems.
American Journal of Respiratory and Critical Care Medicine · 2025-05-01
articleSenior authorAbstract Rationale: The trajectory and stability of inflammatory subphenotypes in critically ill patients are poorly understood. Current measurement technologies face significant limitations for performing high frequency, low sample volume, reproducible and near-to-patient quantification of immune molecules. Digital ELISA technology promises to overcome many of these barriers, but current commercial and laboratory-based systems incur significant costs related to stringent demands for manufacturing and reagent handling. These costs are largely related to the need for microwell structures that allow physical confinement and detection of individual antigen/antibody binding. Replacing physical methods with chemical methods of confinement and amplification would greatly improve digital immunoassay manufacturability, cost, and accessibility. Methods: We have developed a multiplex digital immunosensor that employs linkage of capture antibodies to a planar substrate, followed by antigen and detection antibody incubation and visualization of sandwich immunocomplexes using tyramide-conjugated fluorophores. The assay is implemented in a semi-automated flow cell format. The output image is read using an epifluorescence microscope. We conducted a proof-of concept and feasibility demonstration with twice daily measurements of 5 cytokines in whole capillary blood following influenza and COVID-19 vaccination from a single subject. Results: The tyramide based immunosensor produces a digital immunoassay result, in which the number of immunoreactive puncta, but not their fluorescent intensity, is log-linearly correlated to analyte concentration with a 4 order of magnitude dynamic range. In a multiplex panel including IL-6, IL-8, sTNFR1, CCL11 and NGAL, less than 10% cross reactivity was observed. Immunosensors were manufactured and preserved using standard protein microarray preservation techniques, allowing on-demand use for serial measurements. In our proof-of-concept demonstration, 8 measurements were made in real time from whole capillary blood over 4 days, with a 2 hour sample to answer time. We observed marked elevations of IL-6, IL-8, and CCL-11 following immunization. These elevations did not occur simultaneously, however, and each were only present at a single time point in our measurements. Conclusions: Tyramide based immunocomplex detection can be leveraged to produce a digital immunosensor that overcomes barriers in manufacturability and cost that limit access to digital immunoassay technology in acute care research. Our proof of concept demonstration showed that cytokine expression is highly dynamic, and that single timepoint sampling is inadequate to capture the response to an immune challenge. We are initiating a pilot study of serial cytokine analysis from capillary blood in ICU patients.
Recent grants
NSF · $360k · 2010–2013
NSF · $349k · 2013–2016
NSF · $240k · 2006–2010
Microfabricated Thermal Modulator for Comprehensive Two-Dimensional Gas Chromatography
NSF · $250k · 2013–2016
RAPID: Plasmonic Optoelectronic Immunosensing for Point-Of-Care Virus Infection Screening
NSF · $200k · 2020–2021
Frequent coauthors
- 36 shared
Michael A. Teitell
University of California, Los Angeles
- 36 shared
Hiroshi Toshiyoshi
The University of Tokyo
- 36 shared
Dean Ho
National University of Singapore
- 36 shared
Ting‐Hsuan Chen
City University of Hong Kong
- 36 shared
Sing Tak
Stanford University
- 36 shared
Dino Di Carlo
- 36 shared
Jeff Wang
National University of Singapore
- 36 shared
R. Langer
Massachusetts Institute of Technology
Awards & honors
- NSF Early Faculty Career Development (CAREER) Award (2001)
- Robert Caddell Memorial Award (2005)
- Pi Tau Sigma Outstanding Professor Award (2007)
- University of Michigan Mechanical Engineering Outstanding Ac…
- Ted Kennedy Award (2015)
- Resume-aware match score
- Save to shortlist
- AI-drafted outreach
See your match with Katsuo Kurabayashi
PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.
- Free to start
- No credit card
- 30-second signup