PeopleofSuperintelligence

Researcher

Dina Demner-Fushman

Also known as Dina Demner‐Fushman

Biomedical informatician Dina Demner-Fushman applies artificial intelligence and natural language processing to clinical and consumer health question answering. Trained in medicine at Kazan State Medical Institute in 1980 and Moscow Medical and Stomatological Institute in 1989, she earned computer science degrees at Hunter College in 2000 and the University of Maryland in 2003 and 2006. In 2011, she was elected a Fellow of the American College of Medical Informatics. At the National Library of Medicine, she worked on the Consumer Health Information and Question Answering project, coauthored the 2020 TREC-COVID search evaluation, and coauthored a 2023 Nature study on clinical knowledge in large language models. As of October 2026, she is a Senior Investigator in NLM's Computational Health Research Branch; in March 2026, she coauthored a TREC BioGen paper on grounding biomedical answers in PubMed.

Timeline

  1. 1980–1989

    Medical degrees in Kazan and Moscow

    Dina Demner-Fushman earns a doctor of medicine degree from Kazan State Medical Institute in 1980 and a clinical research doctorate in medical science from Moscow Medical and Stomatological Institute in 1989.

  2. 2000–2006

    Computer science at Hunter and UMD

    She earns a BA in computer science from Hunter College, CUNY in 2000 and an MS in computer science from the University of Maryland, College Park in 2003. In 2006, she graduates from the University of Maryland's Department of Computer Science with a PhD dissertation on complex question answering based on a semantic domain model of clinical medicine; Doug Oard is her advisor.

  3. 2011

    An ACMI fellowship

    In 2011, the American College of Medical Informatics elects her as a fellow; 21 new fellows are inducted at AMIA's 35th Annual Symposium on Biomedical and Health Informatics.

  4. May 2014

    Consumer health question answering

    Her Consumer Health Information and Question Answering (CHIQA) project classifies NLM customer requests and prepares answers with statistical methods and knowledge-based natural language processing. In May 2014, the pilot system enters the customer-service workflow.

  5. 2017

    Biomedical NLP at NLM

    In 2017, she is a staff scientist at NLM and works in biomedical natural language processing. Her work combines computer science, linguistics, and clinical knowledge to help parents find trustworthy health information through sources such as PubMed and MedlinePlus.

  6. 2020

    TREC-COVID search evaluation

    In 2020, she coauthors the TREC-COVID paper, an information-retrieval shared task to support clinicians and clinical research during the COVID-19 pandemic. The evaluation addresses search systems and a changing body of COVID-19 literature.

  7. 2023

    Clinical knowledge in language models

    In 2023, she coauthors Large language models encode clinical knowledge in Nature, which introduces the MultiMedQA benchmark and Med-PaLM for medical question answering. The study evaluates answers for accuracy, scientific grounding, harm, and bias.

  8. As of October 2026

    Senior Investigator at NLM

    In March 2026, she coauthors the overview of TREC 2025's BioGen track, which continues reference attribution and adds sentence-level grounding of biomedical answers in PubMed documents. As of October 2026, she is a Senior Investigator in NLM's Computational Health Research Branch, where her team uses AI, natural language processing, data mining, and multimodal information retrieval to answer health questions.

Career

  1. NowNational Library of MedicineStaff Scientist

Education

  1. 2006University of Maryland
  2. 2000Hunter CollegeBA in computer science
  3. 1989Moscow Medical and Stomatological InstituteClinical research doctorate in medical science
  4. 1980Kazan State Medical InstituteDoctor of Medicine

From the biography.

  1. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes National Library of Medicine. 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. People shaping AI work at a median of 3 organizations over a career: 3 for university starters and institute and lab starters, versus 2 for company startersIncludes University of Maryland. Across 6,853 people shaping AI with a dated work role, we estimate a median of 3 parent organizations over a career (mean 3.6), comparing role groups, starting sectors and starting decades from the 1950s to 2020–2026.
  3. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University of Maryland. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Maryland. 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.

Sources and credits

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  1. User:Dina - ACL Wiki aclweb.org. Checked 22 October 2026.
  2. Dina Demner-Fushman | UMD Department of Computer Science cs.umd.edu. Checked 22 October 2026.
  3. 21 Fellows inducted into American College of Medical Informatics eurekalert.org. Checked 22 October 2026.
  4. Consumer Health Question Answering lhncbc.nlm.nih.gov. Checked 22 October 2026.
  5. The Rise of Computational Linguistics Geeks nlmdirector.nlm.nih.gov. Checked 22 October 2026.
  6. TREC-COVID: Rationale and Structure of an Information Retrieval Shared Task for COVID-19 nist.gov. Checked 22 October 2026.
  7. Large language models encode clinical knowledge nature.com. Checked 22 October 2026.
  8. Overview of TREC 2025 Biomedical Generative Retrieval (BioGen) Track arxiv.org. Checked 22 October 2026.
  9. Dina Demner-Fushman, M.D., Ph.D. | Principal Investigators | NIH Intramural Research Program irp.nih.gov. Checked 22 October 2026.
  10. NLM Intramural Research Program - Dina Demner-Fushman, MD, PhD nlm.nih.gov. Checked 22 October 2026.