About

Rebecca Richards-Kortum is the Malcolm Gillis University Professor and Professor of Bioengineering at Rice University, where she also serves as Co-Director of the Rice360 Institute for Global Health Technologies. Guided by the belief that all of the world’s people deserve access to health innovation, her research and teaching focus on developing low-cost, high-performance technologies for remote and low-resource settings. She is known for providing vulnerable populations with access to life-saving health technologies that address diseases and conditions with high morbidity and mortality, such as cervical and oral cancer, premature birth, sickle cell disease, and malaria. Her laboratory has concentrated on translating research that integrates nanotechnology, molecular imaging, and microfabrication technologies to create inexpensive, portable optical imaging systems capable of rapid point-of-care diagnosis, detection of molecular signatures of pre-cancer, assessment of tumor margins, and monitoring therapy response. Richards-Kortum has developed over 40 patents and authored a textbook titled 'Biomedical Engineering for Global Health.' Her work has led to numerous collaborations with institutions worldwide, including the University of Texas MD Anderson Cancer Center, Baylor College of Medicine, Northwestern University, and international partners in Malawi, Brazil, China, and other countries. Recognized for her leadership and innovation, she has received numerous awards, including the MacArthur 'Genius Grant,' and has been elected to prestigious organizations such as the National Academy of Sciences, the National Academy of Engineering, and the American Academy of Arts and Sciences. She also served as a U.S. Science Envoy for Health Security and has been instrumental in advancing global health technologies aimed at reducing preventable maternal and neonatal deaths.

Selected publications

• Dual-modality, deep-learning-enabled endomicroscope with large field-of-view and depth-of-field for real-time in vivo imaging of epithelial hallmarks of cancer

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-01-15 · 1 citations

  articleOpen accessSenior author

  Abstract In vivo microscopy (IVM) has shown great promise to improve early detection of epithelial precancer, but it suffers from fundamental trade-offs that limit the resolution, field-of-view (FOV) and depth-of-field (DOF). Here, we present PrecisionView, a compact, deep-learning-enabled endomicroscope that breaks these constrains and achieves 20 mm 2 FOV and 500 µm DOF with 4 µm resolution, representing approximately 5× increase in FOV and 8× larger DOF compared to conventional IVM with similar resolution. PrecisionView integrates a deep-learning optimized phase mask and real-time reconstruction, enabling rapid in vivo assessment of two key hallmarks of cancer: epithelial cell nuclear morphology and subsurface microvasculature through fluorescence and reflectance imaging. By imaging oral cavity of healthy volunteers and cervical specimens with precancerous lesions, PrecisionView generates large-scale (1-3 cm 2 ) co-registered maps of cellular and vascular structures, revealing distinct microscopic patterns associated with anatomic structures and precancerous lesions. Our results suggest the potential of this computational endomicroscope to address the unmet need for early cancer detection at the point-of-care.

  PublisherOA PDFDOI

• Mock Samples That Mimic Human Cervicovaginal Samples to Accelerate the Development and Evaluation of Assays for High‐Risk HPV for Cervical Cancer Screening

  Journal of Medical Virology · 2026-04-01

  articleOpen accessSenior authorCorresponding

  Nearly all cervical cancer cases are caused by high-risk human papillomavirus (hrHPV) infections. The World Health Organization recommends screening for hrHPV using nucleic acid amplification tests (NAATs) that detect hrHPV DNA or mRNA. Lack of access to affordable, point-of-care screening tests in resource-limited settings leads to women presenting with advanced-stage cervical cancer, with many dying of the disease. There is a significant need to develop point-of-care NAATs to improve screening and early detection. Because access to real clinical samples is limited, initial evaluation of NAATs is often performed using contrived samples created using some combination of extracted hrHPV DNA and/or cultured hrHPV-positive cells. When mock samples do not adequately recapitulate the contents of clinical cervicovaginal samples, it can delay clinical translation of potentially promising assays. To improve the value of contrived samples, we characterized the composition of 32 hrHPV DNA-positive cervicovaginal clinical samples. We also describe a simple method to generate contrived samples that mimic the diversity of clinical cervicovaginal samples, and test them using the methods used to characterize the clinical samples. Results show that the hrHPV DNA content of cervicovaginal samples varies by approximately eight orders of magnitude and spans from 100% linear integrated DNA to 100% circular non-integrated DNA, that the concentration of hrHPV mRNA also varies by nearly nine orders of magnitude between patient samples, and that the concentration of potential inhibitors such as hemoglobin varies by more than three orders of magnitude. hrHPV DNA and mRNA extracted from contrived samples exhibited expected patterns of DNA quantity, DNA conformation, and mRNA quantity. Altogether, the protocols described here to generate mock samples can help NAAT developers optimize test performance prior to clinical evaluation, potentially improving test performance and reducing time to deployment.

  PublisherDOI

• Deep-learning endomicroscope with large field-of-view and depth-of-field for real-time in vivo imaging of epithelial cancer hallmarks

  Proceedings of the National Academy of Sciences · 2026-05-11

  articleOpen accessSenior authorCorresponding

  In vivo microscopy (IVM) has shown great promise to improve early detection of epithelial precancer, but it suffers from fundamental trade-offs that limit the resolution, field-of-view (FOV) and depth-of-field (DOF). Here, we present PrecisionView, a compact, deep learning-enabled endomicroscope that breaks these constraints and achieves 20 mm 2 FOV and 500 µm DOF with 4 µm resolution, representing approximately 5× increase in FOV and 8× larger DOF compared to conventional IVM with similar resolution. PrecisionView integrates a deep learning-optimized phase mask and real-time reconstruction, enabling rapid in vivo assessment of two key hallmarks of cancer: epithelial cell nuclear morphology and subsurface microvasculature through fluorescence and reflectance imaging. By imaging the oral cavity of healthy volunteers and cervical specimens with precancerous lesions, PrecisionView generates large-scale (1 to 3 cm 2 ) coregistered maps of cellular and vascular structures, revealing distinct microscopic patterns associated with anatomic structures and precancerous lesions. Our results suggest the potential of this computational endomicroscope to address the unmet need for early cancer detection at the point of care.

  PublisherDOI

• Mo2223 AI-BASED AUTOMATED DIAGNOSIS OF BARRETT'S ESOPHAGEAL NEOPLASIA ON HIGH-RESOLUTION MICROENDOSCOPY

  Gastroenterology · 2026-05-01

  article
  PublisherDOI

• Mo2223 AI-BASED AUTOMATED DIAGNOSIS OF BARRETT'S ESOPHAGEAL NEOPLASIA ON HIGH-RESOLUTION MICROENDOSCOPY

  Gastrointestinal Endoscopy · 2026-05-01

  article
  PublisherDOI

• Using implementation science to define the model and outcomes for improving quality in NEST360, a multicountry alliance for reducing newborn mortality in sub-Saharan Africa

  BMJ Quality & Safety · 2025-05-10 · 4 citations

  article

  Background Improving small and sick newborn care (SSNC) is crucial in resource-limited settings. Newborn Essential Solutions and Technologies (NEST360), a multicountry alliance, aims to reduce newborn mortality through evidence-based interventions. NEST360 developed a multipronged approach to improving quality. We use implementation research (IR) to describe this approach and report emerging implementation outcomes. Methods The implementation research logic model (IRLM) was applied to link contextual factors, implementation strategies, mechanisms and implementation outcomes, capturing successes and challenges of the improving quality approach. Data sources included programme data, peer-reviewed publications and team input. Contextual factors were organised by the NEST360-UNICEF SSNC implementation toolkit. Strategies were grouped by the Expert Recommendations for Implementation Change list, and implementation outcomes were measured using Proctor’s implementation outcomes. Results We developed an IRLM to describe the implementation of NEST360’s improving quality model. This IRLM included 33 contextual factors; 42% were barriers, 42% were facilitators, and 15% were both a barrier and facilitator. Additionally, we identified 10 implementation strategies that NEST360 used. The logic model also describes the connections between the contextual factors, the strategies that address them, and the preliminary implementation outcomes. Examples of the outcomes measured include Reach with 100% of units logging into the NEST360-Implementation Tracker (NEST-IT) at least once (October 2023 to March 2024), Adoption with 100% of units conducting a quality improvement (QI) project (April 2024 to June 2024), and Feasibility with 93% of units reporting NEST-IT data in their QI project documentation (April 2024 to June 2024). Finally, this study identified sustainability strategies as a critical need. Conclusions Integrating IR and QI enhances SSNC in resource-limited settings. Addressing barriers, leveraging facilitators and using structured IR frameworks advanced QI efforts, thereby improving intervention reach, adoption and feasibility while building scalable systems for high-quality healthcare.

  PublisherDOI

• From warehouse to ward: applying implementation research methods to the device identification, qualification, distribution, and management process within the Newborn Essential Solutions and Technologies (NEST360) alliance

  BMC Global and Public Health · 2025-08-01 · 1 citations

  articleOpen access

  BACKGROUND: Preventing newborn deaths requires the right medical devices. However, in many countries, devices for small and sick newborn care (SSNC) are unavailable, not fit for the environment, or broken. Newborn Essential Solutions and Technologies (NEST360) is a multicountry alliance aimed at decreasing neonatal mortality in Kenya, Malawi, Nigeria, and Tanzania. The technology qualification, distribution, and management teams in NEST360 work to ensure appropriate devices are available and functional at facilities, by identifying needed technologies, sourcing suitable devices, testing them under varied conditions, establishing reliable supply chains, training staff, and maintaining the devices once installed through trained biomedical technicians. We applied implementation research (IR) to understand context, describe strategy selection, and implementation outcomes of the work designed to ensure the consistent availability of functional SSNC devices. METHODS: Between March and July 2024, we conducted 12 in-depth interviews with NEST360 team members via Zoom, and reviewed quantitative programmatic data, including device functionality reports. We applied deductive content analysis for interviews and descriptive statistics for quantitative data. Results were used to develop an implementation research logic model (IRLM) using NEST360 and United Nations Children's Fund SSNC Implementation Toolkit for contextual factors and the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework for implementation outcomes. RESULTS: We identified 40 contextual factors, 78% being barriers. Twenty-one strategies were implemented to address barriers to device qualification, distribution, and management efforts, including engaging stakeholders and conducting ongoing trainings. Notable implementation outcomes included reach with 29 devices in 12 product categories qualified, and all 66 facilities received NEST-qualified devices, effectiveness, in 2024, an average of 87% of all newborn care devices were functional, including those provided by NEST360 and those sourced through existing channels, adoption with over 2476 devices installed at NEST360 sites in 2023. Acceptability was also high with country-level biomedical technicians reporting positive facility-level experiences using the devices. CONCLUSIONS: The NEST360 approach to ensuring appropriate and functioning equipment for SSNC was successful through multiple strategies to address multilevel barriers. The use of IR facilitated understanding of how strategies addressed context and where change is needed. These results will be used in plans for scale-up and dissemination.

  PublisherOA PDFDOI

• Recombinase polymerase amplification for single nucleotide polymorphism-specific detection of βC variant in sickle cell disease

  Analytical Biochemistry · 2025-06-01 · 2 citations

  articleSenior author
  PublisherDOI

• TRIAL IN PROGRESS: A RANDOMIZED CLINICAL TRIAL TO ASSESS THERMAL ABLATION VS LOOP ELECTROSURGICAL EXCISION PROCEDURE IN WOMEN LIVING WITH HIV IN MOZAMBIQUE

  International Journal of Gynecological Cancer · 2025-11-01

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  PublisherDOI

• The SimpleSilo: An Effective and Affordable Solution for Gastroschisis Management in Low-Resource Settings

  Journal of Pediatric Surgery · 2025-05-17

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  PublisherDOI

Awards & honors

• U.S. Science Envoy, U.S. State Department (2018)
• Finalist, MacArthur Foundation 100&Change Competition (2017)
• Pierre Galletti Award, American Institute for Medical and Bi…
• George R. Brown Award for Superior Teaching, Rice University…
• Michael S. Feld Biophotonics Award, Optical Society of Ameri…