Marius George Linguraru

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Marius George Linguraru
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CitizenshipAmerican
Alma materUniversity of Oxford
OccupationScientist

Marius George Linguraru DPhil, MA, MSc, is an American scientist specialized in artificial intelligence (AI) for healthcare, rare diseases, medical imaging, and global health. He is the Connor Family Professor and Endowed Chair in Research and Innovation at Children’s National Hospital in Washington, D.C., and a Professor of Radiology and Pediatrics at the George Washington University.[1] In 2021, he was elected to the board of directors of the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society and was appointed President in 2025.[2][3] He has spoken and advised about the ethical use of AI technology in healthcare.[4]

Education

Linguraru earned his DPhil (PhD) in Engineering Science and Medical Image Analysis from the University of Oxford in 2004, where he was a member of Keble College and received a Scatcherd European and Overseas Research Scholarship.[5]

His postdoctoral training included research fellowships at the French Institute for Research in Computer Science and Automation (INRIA) and Harvard University.[6][7]

Career

Academic

Linguraru is the Connor Family Professor and Endowed Chair in Research and Innovation at Children's National Hospital in Washington, D.C.. He is a principal investigator and the founder of the Pediatric Accelerated Intelligence (PAI) Group at the Sheikh Zayed Institute for Pediatric Surgical Innovation.[8] He holds appointments as Professor of Radiology and Pediatrics at the George Washington University, School of Medicine and Health Sciences.[9]

He previously worked as a scientist at the National Institutes of Health (NIH).[10]

Industry

Linguraru co-founded PediaMetrix Inc., a U.S.-based company that develops AI technologies for pediatric healthcare. The company's SoftSpot digital app was approved by the FDA for cranial measurements.[11]

He created mGene, an AI-based smartphone app for screening for genetic diseases.[12] The mGene algorithm was licensed to MGeneRx Inc., a U.S.-based company that specializes in non-invasive genetic screening.[13]

Scientific contributions

Linguraru's research interests include:

  • AI algorithms for cancer diagnostics and tumor measurement in pediatric clinical trials.[14][15][16]
  • Multi-organ image analysis, non-parametric shape modeling, and quantitative analysis of complex anatomical structures.[17][18][19]
  • Deep learning applications for global health, including AI-based newborn genetic screening,[20][21] diagnostics for rheumatic heart disease,[22] and improved ultra-low field MRI quality and capacity.[23][24]

Leadership in scientific societies

Linguraru became president of the Medical Image Computing and Computer Assisted Intervention Society|Medical Image Computing and Computer Assisted Intervention (MICCAI) Society board of directors in 2025[25], and has served in leadership roles in the IEEE Engineering in Medicine and Biology Society (EMBS), IEEE Signal Processing Society, and the International Society of Medical Information Processing and Analysis (SIPAIM).[26]

He led the creation of the MICCAI Society Mentorship Program, a program that supports mentorship for early-career scientists worldwide.[27]

He has served as Chair and co-organizer of international conferences and events, including MICCAI 2022[28], MICCAI 2023[29], MICCAI 2024[30], IEEE-ISBI 2021[31], IEEE-ISBI 2023[32], and the first AFRICAI Summer School (2023)[33]. His work has included initiatives supporting mentorship and global research capacity-building.

Policy and global impact

Linguraru has contributed to global health AI policy through participation in World Bank and science diplomacy events,[34][35] and by co-authoring the first consensus guidelines for trustworthy AI implementation in healthcare, known as the FUTURE-AI framework, published in The BMJ.[36] He also contributed to one of the largest federated learning studies, published in Nature Medicine, that demonstrated how distributed AI models can protect privacy and improve access to data from smaller or vulnerable populations.[37]

Awards and honors

  • MICCAI Fellow (2025)[38]
  • Distinguished Service Award, IEEE EMBS (2025)[39]
  • Distinguished Lecturer, IEEE EMBS (2016–2018)[40]
  • First Prize, International Pediatric Brain Tumor Segmentation Challenge – BraTS-PEDS (2023)[41]
  • First Prize, International Brain Tumor Segmentation Challenge on Sub-Saharan Africa Glioma – BraTS-Africa (2024)[42]

Personal life

Linguraru was born in 1973 and has lived and worked in Romania, the United Kingdom, France, and the United States.

Media coverage

Linguraru's work has been featured by The Economist[43], The Washington Post[44], The Times (London)[45], PBS[46], and Voice of America[47]

Selected publications

  • Lekadir K, Frangi AF, Porras AR, et al. FUTURE-AI: International Consensus Guideline for Trustworthy and Deployable Artificial Intelligence in Healthcare. BMJ. 2025;388:e081554. doi:10.1136/bmj-2024-081554
  • Fathi Kazerooni A, Khalili N, Liu X, et al. BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023. Machine Learning for Biomedical Imaging. 2025;3:72–87. doi:10.59275/j.melba.2025-f6fg
  • Linguraru MG, Bakas S, Aboian M, et al. Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts. Radiol Artif Intell. 2024;6(4):e240225. doi:10.1148/ryai.240225
  • Brown K, Roshanitabrizi P, Rwebembera J, et al. Using Artificial Intelligence for Rheumatic Heart Disease Detection by Echocardiography: Focus on Mitral Regurgitation. J Am Heart Assoc. 2024;13(2):e031257. doi:10.1161/JAHA.123.031257
  • Dayan I, Roth HR, Zhong A, et al. Federated Learning for Predicting Clinical Outcomes in Patients with COVID-19. Nat Med. 2021;27(10):1735–1743. doi:10.1038/s41591-021-01506-3
  • Porras AR, Rosenbaum K, Tor-Diez C, Summar M, Linguraru MG. Development and Evaluation of a Machine Learning-based Point-of-care Screening Tool for Genetic Syndromes in Children: A Multinational Retrospective Study. Lancet Digit Health. 2021;3(10):e635–e643. doi:10.1016/S2589-7500(21)00137-0
  • Cerrolaza JJ, Picazo ML, Humbert L, et al. Computational Anatomy for Multi-organ Analysis in Medical Imaging: A Review. Med Image Anal. 2019;56:44–67. doi:10.1016/j.media.2019.04.002

References

  1. ↑ "Research Profile - Marius George Linguraru". People. Childrens National. 2025. Retrieved 2025-07-05.
  2. ↑ "Board of Directors". About MICCAI. MICCAI. 2025.
  3. ↑ "News". miccai.org. Retrieved 2025-10-29.
  4. ↑ "Equitable AI for Children's Health and Rare Diseases". Center for Virtual Clinical Trial. Duke University. 2025. Retrieved 2025-07-05.
  5. ↑ "Marius George Linguraru". School of Medicine and Health Sciences. George Washington University. Retrieved 2025-07-05.
  6. ↑ "Epidaure Project Marius George Linguraru". Epidaure. INRIA. Retrieved 2025-07-05.
  7. ↑ "People". Harvard Biorobotics Lab. Harvard University. 2025.
  8. ↑ "Research Profile - Marius George Linguraru". People. Childrens National. 2025. Retrieved 2025-07-05.
  9. ↑ "Marius George Linguraru". School of Medicine and Health Sciences. George Washington University. Retrieved 2025-07-05.
  10. ↑ "Research Profile - Marius George Linguraru". People. Childrens National. 2025. Retrieved 2025-07-05.
  11. ↑ "Team". PediaMetrix. 2025. Retrieved 2025-07-05.
  12. ↑ Porras, Antonio (2021-09-01). "Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study". Lancet Digital Health. 3 (10): e635–e643. doi:10.1016/S2589-7500(21)00137-0. PMID 34481768.
  13. ↑ "About us". Holdings. MGeneRx. 2025. Retrieved 2025-07-05.
  14. ↑ Fathi Kazerooni, Anahita (2025-06-26). "BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023". Machine Learning for Biomedical Imaging. 3 (6) 2025:005: 72–87. doi:10.59275/j.melba.2025-f6fg.
  15. ↑ Liu, Xinyang (2024-06-28). "Early prognostication of overall survival for pediatric diffuse midline gliomas using MRI radiomics and machine learning: A two-center study". Neurooncology Advances. 6 (1): 1–11.
  16. ↑ Avery, Robert (2016-11-04). "Optic pathway glioma volume predicts retinal axon degeneration in neurofibromatosis type 1". Neurology. 87 (23): 2403–2407. doi:10.1212/WNL.0000000000003402. PMC 5177678. PMID 27815398.
  17. ↑ Cerrolaza, Juan (2019-08-01). "Computational anatomy for multi-organ analysis in medical imaging: A review". Medical Image Analysis. 56: 44–67. doi:10.1016/j.media.2019.04.002. PMID 31181343.
  18. ↑ Cerrolaza, Juan (2015-04-15). "Automatic multi-resolution shape modeling of multi-organ structures". Medical Image Analysis. 25 (1): 11–21. doi:10.1016/j.media.2015.04.003. PMC 5526337. PMID 25977156.
  19. ↑ Linguraru, Marius George (2012-02-11). "Statistical 4D graphs for multi-organ abdominal segmentation from multiphase CT". Medical Image Analysis. 16 (4): 904–914. doi:10.1016/j.media.2012.02.001. PMC 3322299. PMID 22377657.
  20. ↑ Porras, Antonio (2021-09-01). "Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study". Lancet Digital Health. 3 (10): e635–e643. doi:10.1016/S2589-7500(21)00137-0. PMID 34481768.
  21. ↑ Kruszka, Paul (2017-03-22). "22q11.2 deletion syndrome in diverse populations". American Journal of Medical Genetics Part A. 173 (4): 904–914. doi:10.1002/ajmg.a.38199.
  22. ↑ Brown, Kelsey (2024-01-16). "Using Artificial Intelligence for Rheumatic Heart Disease Detection by Echocardiography: Focus on Mitral Regurgitation". Journal of the American Heart Association. 13 (2) e031257: 031257. doi:10.1161/JAHA.123.031257.
  23. ↑ Abate, F (2024-05-31). "UNITY: A low-field magnetic resonance neuroimaging initiative to characterize neurodevelopment in low and middle-income settings". Developmental Cognitive Neuroscience. 69 101397. doi:10.1016/j.dcn.2024.101397.
  24. ↑ Tapp, Austin (2024-10-03). "Super-Field MRI Synthesis for Infant Brains Enhanced by Dual Channel Latent Diffusion". Medical Image Computing and Computer Assisted Intervention. Lecture Notes in Computer Science. Vol. 15003. pp. 444–454. doi:10.1007/978-3-031-72384-1_42. ISBN 978-3-031-72383-4.
  25. ↑ "News". miccai.org. Retrieved 2025-10-29.
  26. ↑ "Board of Directors". About MICCAI. MICCAI. 2025.
  27. ↑ "MICCAI Society Mentorship Program". MICCAI. 2025. Retrieved 2025-07-05.
  28. ↑ "ORGANIZING COMMITTEE". conferences.miccai.org. Retrieved 2025-10-29.
  29. ↑ "ORGANIZING COMMITTEE". conferences.miccai.org. Retrieved 2025-10-29.
  30. ↑ "ORGANIZING COMMITTEE". conferences.miccai.org. Retrieved 2025-10-29.
  31. ↑ "ISBI 2021 Committee | ISBI 2021". biomedicalimaging.org. Retrieved 2025-10-29.
  32. ↑ "IEEE - ISBI 2023 - International Symposium on Biomedical Imaging". biomedicalimaging.org. Retrieved 2025-10-29.
  33. ↑ "Summer School 2023 – AFRICAI". Retrieved 2025-10-29.
  34. ↑ "Johns Hopkins Science Diplomacy Summit 2024". LinkedIn. Retrieved 2025-07-05.
  35. ↑ "AI in Action Event Series". Events. World Bank Group. 2025. Retrieved 2025-07-05.
  36. ↑ Lekadir, Karim (2025-02-17). "FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare". BMJ. 388: e081554. doi:10.1136/bmj-2024-081554.
  37. ↑ Dayan, Ittai (2021-09-15). "Federated learning for predicting clinical outcomes in patients with COVID-19". Nature Medicine. 27 (10): 1735–1743. doi:10.1038/s41591-021-01506-3. PMC 9157510. PMID 34526699.
  38. ↑ "News". miccai.org. Retrieved 2025-10-29.
  39. ↑ "We are thrilled to announce the outstanding recipients of the 2025 EMBS Awards!". LinkedIn. 2025-07-03.
  40. ↑ "EMB Newsletter". EMBS. IEEE. 2017. Retrieved 2025-07-05.
  41. ↑ Fathi Kazerooni, Anahita (2025-06-26). "BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023". Machine Learning for Biomedical Imaging. 3 (6) 2025:005: 72–87. doi:10.59275/j.melba.2025-f6fg.
  42. ↑ "AI for good: Children's National wins global competitions for measuring brain tumors". Innovation District. Childrens National. 2025-01-10.
  43. ↑ "Researchers produce images of people's faces from their genomes". The Economist. London. 2017-09-17.
  44. ↑ Johnson, Mark (2024-01-16). "How doctors are using AI to diagnose a hidden heart condition in kids". The Washington Post.
  45. ↑ Bridge, Mark (2017-04-17). "Face app helps to spot rare diseases". The Times. London.
  46. ↑ Snow, Jackie (2019-03-06). "The Algorithm Will See You Now: How AI is Helping Doctors Diagnose and Treat Patients". PBS. PBS.
  47. ↑ Putic, George (2014-04-24). "Mobile Phone App Could Help Detect Down Syndrome". VOA. VOA.

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