PeopleofSuperintelligence

Researcher

Daria Pavliuk

Daria Pavliuk is a researcher whose work applies machine learning to multimodal biological and medical data. She studied applied physics and mathematics at Moscow Institute of Physics and Technology, earning a BSc in 2018 and an MSc in 2020. In July 2025, she coauthored a review of visible neural networks for multi-omics that analyzed 86 papers. In March 2026, she coauthored reports on AI science, atherothrombotic biomarker research and knowledge graphs; as of October 2026, she is a PhD student in DFKI’s Data Science and its Applications group.

Timeline

  1. 2014–2018

    A BSc in applied physics

    From 2014 to 2018, she studies for a BSc in applied physics and mathematics at Moscow Institute of Physics and Technology.

  2. 2018–2020

    An MSc in applied physics

    From 2018 to 2020, she studies for an MSc in applied physics and mathematics at Moscow Institute of Physics and Technology.

  3. July 2025

    An 86-paper review

    In July 2025, she coauthors “Visible neural networks for multi-omics integration: a critical review” in Frontiers in Artificial Intelligence. The review analyzes 86 recent papers on biologically informed or visible neural networks, comparing model architecture, data sources and evaluation methods.

  4. March 2026

    curAIscid on AI science

    In March 2026, she coauthors the report “curAIscid - curATime AI science & development” with David Selby, Adriano Lucieri, Markus Junker, Kathan Pandya, Niloofar Maani, Kevin George, Gerrit Großmann and Sebastian Vollmer.

  5. March 2026

    A curATime biomarker report

    The March 2026 report “biosignATure - curATime: Systemorientierte, Multi-Omics-Identifikation von Biomarkersignaturen für die Detektion, Quantifizierung und Behandlung von Atherothrombose” covers multi-omics biomarker signatures for atherothrombosis. She coauthors it with David Selby, Kathan Pandya, Kevin George, Niloofar Maani, Gerrit Großmann and Sebastian Vollmer.

  6. March 2026

    curAIknow on knowledge graphs

    With David Selby, Yujing Ke, Kevin George, Gerrit Großmann and Sebastian Vollmer, she coauthors “curAIknow - curATime knowledge graphs” in March 2026.

  7. As of October 2026

    PhD research at DFKI

    As of October 2026, she is a PhD student in DFKI’s Data Science and its Applications group. Her research applies machine learning to multimodal biological and medical data, with interests in knowledge graphs, explainable algorithms and representation learning.

Career

Education

  1. 2020Moscow Institute of Physics and TechnologyMSc
  2. 2018Moscow Institute of Physics and TechnologyBSc
  3. DFKIPhD

From the biography.

  1. Nonprofit roles are 2.3 times as common in AI safetyIncludes DFKI. 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.
  2. The top 10 organizations employed 22% of people shaping AI in 2025: 51% of company researchers and 21% of university researchersIncludes DFKI. We estimate the share of people shaping AI who worked at the top 10 organizations each year from 1955 to 2025, comparing concentration across companies, universities, and institutes and labs.
  3. The United States employs an estimated 48% of people shaping AIIncludes DFKI. 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.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Moscow Institute of Physics and Technology. 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.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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

  1. Daria Pavliuk — Data Science and its Applications dsa.dfki.de. Checked 22 October 2026.
  2. Frontiers | Visible neural networks for multi-omics integration: a critical review frontiersin.org. Checked 22 October 2026.
  3. Visible neural networks for multi-omics integration: a critical review | Sciety sciety.org. Checked 22 October 2026.
  4. curAIscid - curATime AI science & development oa.tib.eu. Checked 22 October 2026.
  5. biosignATure - curATime: Systemorientierte, Multi-Omics-Identifikation von Biomarkersignaturen für die Detektion, Quantifizierung und Behandlung von Atherothrombose oa.tib.eu. Checked 22 October 2026.
  6. curAIknow - curATime knowledge graphs oa.tib.eu. Checked 22 October 2026.
  7. Team — Data Science and its Applications dsa.dfki.de. Checked 22 October 2026.