PeopleofSuperintelligence

Researcher

Chintan Parmar

Chintan Parmar is a medical AI researcher whose work applies machine learning to radiology and digital pathology. He coauthored a 2015 study of radiomic classifiers for head and neck cancer, earned his PhD through Maastricht University, the Indian Statistical Institute, and Dana-Farber, Brigham and Women’s, and Harvard Medical School in 2017, and received a PLOS ONE Early Career Travel Award in 2018. In 2019, he was a postdoctoral fellow in the Dana-Farber Cancer Institute’s Department of Radiation Oncology; in 2024, he coauthored deep-learning work on cancer nuclear morphology at PathAI. As of October 2026, he is a Computational Pathology Lead at AstraZeneca in Waltham, working on AI-derived H&E biomarkers for metastatic lung cancer.

Works
84
Citations
23,643
h-index
30
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2015

    Radiomic classifiers for cancer prognosis

    In 2015, he coauthors a paper that evaluates machine-learning classifiers for predicting overall survival in head and neck cancer using radiomic features.

  2. 2017

    A PhD in 2017

    He earns his PhD in 2017 through Maastricht University, the Indian Statistical Institute, and Dana-Farber Cancer Institute/Brigham and Women’s Hospital/Harvard Medical School.

  3. 2018

    A PLOS ONE travel award

    He receives PLOS ONE’s Early Career Travel Award in 2018 in the Physics & Astronomy category. The award supports his travel to the 2018 AAPM annual meeting, where he presents “Medical Imaging and Deep Learning.”

  4. March 2019

    Postdoc at Dana-Farber

    In March 2019, he joins Harvard’s Assembly cohort while working as a postdoctoral fellow in the Department of Radiation Oncology at Dana-Farber Cancer Institute.

  5. 2024

    Deep learning for nuclear morphology

    In 2024, he works at PathAI and coauthors a study that uses a pan-tissue deep-learning pipeline to detect, segment, and classify nuclei in H&E-stained images. The team compares nuclear features with genomic instability, gene expression, and prognosis.

  6. As of October 2026

    Pathology lead at AstraZeneca

    As of October 2026, he is a Computational Pathology Lead at AstraZeneca in Waltham. In 2026, he presents a study using AI-derived H&E biomarkers to predict differential survival under immunotherapy and chemotherapy in metastatic non-small-cell lung cancer.

Career

  1. Since 2025AstraZenecaComputational Pathology Lead
  2. 2024–2026PathAI
  3. 2019–2021Dana-Farber Cancer InstitutePostdoctoral fellow

Education

  1. 2017Maastricht UniversityPhD
  2. 2017Indian Statistical InstitutePhD
  3. 2017Dana-Farber Cancer InstitutePhD
  4. 2017Mass General BrighamPhD
  5. 2017Harvard UniversityPhD

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

  1. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes AstraZeneca. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  2. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Harvard University. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  3. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Harvard University. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  4. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes Harvard University. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.

Colleagues

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

Sources and credits

Photo: We have no published photo of Chintan Parmar yet. Send us a free-licensed photo.

  1. Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer frontiersin.org. Checked 20 October 2026.
  2. Meet Chintan Parmar: The Physics & Astronomy Category Recipient of the PLOS ONE Early Career Travel Award ecrcommunity.plos.org. Checked 20 October 2026.
  3. AAPM VL-Deep Learning with Medical Images (Session 6 of the Certificate Series) aapm.org. Checked 20 October 2026.
  4. Announcing the 2019 Assembly cohort cyber.harvard.edu. Checked 20 October 2026.
  5. AI powered quantification of nuclear morphology in cancers enables prediction of genome instability and prognosis nature.com. Checked 20 October 2026.
  6. AI Agents & Revenue Operations for HCLS - Revenue Catalyst revenuecatalyst.io. Checked 20 October 2026.