PeopleofSuperintelligence

Researcher

María Díaz de León Derby

Also known as Maria Diaz de Leon Derby

María Díaz de León Derby is a bioengineer whose research connects machine learning with portable diagnostics for infectious diseases. In 2021, she co-led a study on an amplification-free CRISPR-Cas13a mobile-phone test for SARS-CoV-2. She earned a bioengineering PhD from UC Berkeley in 2024 and joined Vector Institute as a postdoctoral researcher in 2025. Her 2025 machine-learning study improved schistosomiasis diagnosis with brightfield and darkfield images, and in 2026 she helped develop NTDscope, a portable microscope that automates parasite detection at the point of care. As of October 2026, she is a Distinguished Postdoctoral Fellow at Vector Institute.

Timeline

  1. 2021

    A mobile-phone COVID test

    In 2021, she is a doctoral candidate in the UC Berkeley-UCSF joint Bioengineering program and a co-lead author of the Cell study on an amplification-free CRISPR-Cas13a assay for SARS-CoV-2 that uses mobile-phone microscopy.

  2. 2022

    Mobile microscopy in Côte d’Ivoire

    In 2022, she coauthors a community study of mobile-phone microscopy in Azaguié, Côte d’Ivoire. It reports 85.7% sensitivity and 93.3% specificity for Schistosoma haematobium identification against conventional light microscopy.

  3. 2024

    A bioengineering PhD

    At UC Berkeley, she completes a bioengineering PhD in Dan Fletcher’s laboratory in 2024.

  4. 2025

    A Vector postdoc and ML study

    In 2025, she joins Vector Institute as a postdoctoral researcher. A study she coauthors trains machine-learning models on brightfield and darkfield images from the SchistoScope; darkfield models and almost all combined models perform better than brightfield-only models.

  5. 2026

    The NTDscope microscope

    In 2026, she coauthors a paper introducing NTDscope, a portable microscope for point-of-care imaging and automated detection of parasites and other pathogens. She leads an interdisciplinary collaboration of industrial and academic partners to develop, test and deploy the device, which combines brightfield, darkfield and fluorescence imaging and can quantify molecular assays such as CRISPR-Cas13a.

  6. As of October 2026

    Distinguished Postdoctoral Fellow

    As of October 2026, she is a Distinguished Postdoctoral Fellow at Vector Institute, where she works with Rahul Krishnan and Michael Brudno.

Career

  1. Since 2025Vector InstituteDistinguished Postdoctoral Fellow

Education

  1. 2024University of California, BerkeleyBioengineering PhD

From the biography.

  1. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Vector Institute. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.
  2. Nonprofit roles are 2.3 times as common in AI safetyIncludes Vector Institute. We estimate where people focused on safety, alignment and evaluation work. Nonprofit roles appear for 25.1% of safety people with known affiliations, compared with 11.0% in other areas.
  3. Universities (31%) and startups and other companies (25%) employ the largest shares of 2020–2026 entrantsIncludes Vector Institute. Among 819 people whose first recorded role started in 2020–2026 and who have a known current organization, 60% work in commercial sectors (25% at startups and other companies, 23% at frontier labs and 13% at big tech, with 9 in two), and 31% work at universities, compared with 66% for earlier entrants.
  4. The United States employs an estimated 48% of people shaping AIIncludes Vector Institute. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. The health lab in your pocket engineering.berkeley.edu. Checked 21 October 2026.
  2. High Sensitivity of Mobile Phone Microscopy Screening for Schistosoma haematobium in Azaguié, Côte d’Ivoire pmc.ncbi.nlm.nih.gov. Checked 21 October 2026.
  3. Alumni fletchlab.berkeley.edu. Checked 21 October 2026.
  4. Maria Diaz de Leon Derby - Vector Institute for Artificial Intelligence vectorinstitute.ai. Checked 21 October 2026.
  5. Multi-contrast machine learning improves schistosomiasis diagnostic performance journals.plos.org. Checked 21 October 2026.
  6. NTDscope: A multi-contrast portable microscope for disease diagnosis journals.plos.org. Checked 21 October 2026.