PeopleofSuperintelligence

Researcher

Martin Styner

Also known as Martin Andreas Styner

Martin Styner works in medical image computing, with deep-learning registration and machine-learning analysis of newborn brain scans among his research. He earned an MS in computer science at ETH Zürich in 1997 and a PhD at UNC Chapel Hill in 2001, then held research leadership posts at Duke and the University of Bern before joining UNC in 2004. His work includes medial models for brain anatomy, SPHARM-PDM for 3D shape analysis, and Quicksilver for deformable image registration. In 2019, he coauthored a UNC study that used machine learning on newborn MRI to predict cognitive development at age two with 95 percent accuracy. Clarivate recognized him as a Highly Cited Researcher in 2020 and 2023; UNC promoted him to full professor in 2023, and since 2025 he has shared research between UNC and Basel.

Now at
University of North Carolina at Chapel Hill, University of Basel and Department of Biomedical Engineering
Badges

Timeline

  1. 1997–2001

    ETH MS and UNC PhD

    He earns an MS in computer science at ETH Zürich in 1997 and completes a computer science PhD at UNC Chapel Hill in 2001.

  2. 2003–2012

    Medial models and UNC faculty

    In a 2003 paper with Guido Gerig and others, he presents a medial model for describing anatomical shape variation and applies it to lateral-ventricle differences in twin groups. After short-term research leadership positions at Duke University and the University of Bern, he joins UNC as assistant professor in 2004 and receives tenure as associate professor in 2012.

  3. 2015

    SPHARM-PDM shape-analysis software

    In June 2015, he posts a SPHARM-PDM v1.4 release to NITRC. The tool computes corresponding point models for 3D structural shape analysis and is available through 3D Slicer and SlicerSALT.

  4. 2017

    Quicksilver for image registration

    In 2017, he coauthors Quicksilver, a fast deformable image-registration method that predicts a deformation model from image appearance using a deep encoder-decoder network.

  5. 2019

    Machine learning from newborn MRI

    In March 2019, he coauthors a UNC study that uses machine learning on newborn brain MRI to predict cognitive development at age two with 95 percent accuracy. He directs UNC's Neuro Image Research and Analysis Laboratory.

  6. 2020–2023

    Highly Cited Researcher

    Clarivate recognizes him as a Highly Cited Researcher in 2020 and 2023.

  7. 2023

    Full professor at UNC

    UNC promotes him to full professor in 2023.

  8. Since 2025

    Research associate at Basel

    In 2025, he joins the University of Basel part-time and shares his research activities between Basel and UNC. At Basel, he is a research associate in the Department of Biomedical Engineering and leads the NeuroImaging Analysis Group, which develops methods and open-source software for structural and diffusion MRI.

Career

  1. Since 2025University of BaselResearch Associate
  2. Since 2025Department of Biomedical EngineeringGroup Lead
  3. NowUniversity of North Carolina at Chapel HillAssistant Professor

Education

  1. 2001University of North Carolina at Chapel HillPhD
  2. 1997ETH ZurichMS

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University of Basel. 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.
  2. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of North Carolina at Chapel Hill. 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 company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of North Carolina at Chapel Hill. 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.
  4. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of North Carolina at Chapel Hill. 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.

Colleagues

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

Sources and credits

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  1. Styner Martin | Department of Biomedical Engineering | University of Basel dbe.unibas.ch. Checked 20 October 2026.
  2. Statistical shape analysis of neuroanatomical structures based on medial models pure.johnshopkins.edu. Checked 20 October 2026.
  3. NITRC: SPHARM-PDM Toolbox: Tool/Resource Info nitrc.org. Checked 20 October 2026.
  4. SPHARM-PDM User Tutorial — SlicerSALT Documentation documentation slicersalt.readthedocs.io. Checked 20 October 2026.
  5. Quicksilver: Fast Predictive Image Registration - a Deep Learning Approach arxiv.org. Checked 20 October 2026.
  6. AI and MRIs at birth can predict cognitive development at age 2, UNC study finds news.unchealthcare.org. Checked 20 October 2026.