Antonio R. Porras, PhD is Associate Professor of Neurological Surgery at the University of Chicago, where he directs the Neural Image Computing (NIC) Lab and serves as Scientific Director of the Section of Computational Neurosurgery. His research focuses on developing artificial intelligence and medical image computing methods that transform biomedical images and multimodal health data into actionable insights for healthcare. Leading interdisciplinary teams of engineers, data scientists, and clinicians, his work advances precision diagnosis, treatment planning, and predictive modeling across neurosurgery, radiology, pediatrics, genetics, and other medical specialties.
Dr. Porras earned degrees in Computer Engineering and Biomedical Engineering in Spain before completing a PhD in Computational Imaging at Pompeu Fabra University in Barcelona. Following his doctoral training, he pursued extensive postdoctoral and research training at Children's National Hospital and within the NIH research environment, broadening his expertise in developmental disorders, human genetics, and pediatric neurosurgery. This interdisciplinary training helped shape his approach to combining methodological innovation with clinically meaningful applications.
Before joining the University of Chicago, Dr. Porras was a faculty member at the University of Colorado, where he established an internationally recognized research program in medical image computing and artificial intelligence with applications spanning craniofacial disorders, pediatrics, genetics, and surgery. His research has contributed to advances in AI-driven disease diagnosis, image-based phenotyping, surgical planning, and predictive modeling and has been supported by the National Institutes of Health. At Colorado, he was awarded tenure and developed educational and mentoring programs for students, trainees, and early-career investigators while teaching learners across disciplines spanning engineering, data science, and medicine.
Dr. Porras is an active leader in the international medical image computing community. He co-founded the MICCAI Mentorship Program in 2018, has led federal awards supporting participation in MICCAI by U.S.-based students and early-career investigators, serves on the MICCAI Board of Directors, and chairs the MICCAI Career Advancement Working Group. Through these and other initiatives, he has helped expand access to mentorship, professional development, entrepreneurship, and career-building opportunities across the MICCAI community.
Children's National Hospital
USA (DC)
Postdoctoral - Quantitative Imaging, Pediatric Neurosurgery
2020
Foundation for Advanced Education in the Sciences, National Institutes of Health
USA (MD)
Postdoctoral - Medical Genetics, Developmental Biology
2019
Pompeu Fabra University
Spain
PhD - Medical Image Computing
2015
University of Barcelona
Spain
MSc - Biomedical Engineering
2010
University of Cordoba
Spain
Eng - Computer Engineering
2008
University of Cordoba
Spain
BSc - Technical Engineering in Computer Systems
2006
The impact of dedicated surgical teams on patient outcomes and healthcare cost and delivery: A scoping review with a focus on plastic and reconstructive surgery.
The impact of dedicated surgical teams on patient outcomes and healthcare cost and delivery: A scoping review with a focus on plastic and reconstructive surgery. J Healthc Risk Manag. 2026 Aug 26.
PMID: 42644375
Unsupervised adaptive sampling graph autoencoder for 3D surface encoding and mesh representation transfer.
Unsupervised adaptive sampling graph autoencoder for 3D surface encoding and mesh representation transfer. Med Image Anal. 2026 Nov; 114:104228.
PMID: 42520537
Data-driven personalized surgical treatment selection for metopic and sagittal craniosynostosis.
Data-driven personalized surgical treatment selection for metopic and sagittal craniosynostosis. J Neurosurg Pediatr. 2026 May 29; 38(2):195-204.
PMID: 42214106
Impact of Nasal Stents on Three-Dimensional Morphologic Outcomes Following Primary Cleft Rhinoplasty in Unilateral Cleft Lip.
Impact of Nasal Stents on Three-Dimensional Morphologic Outcomes Following Primary Cleft Rhinoplasty in Unilateral Cleft Lip. J Craniofac Surg. 2026 Jul-Aug 01; 37(7-8):1972-1975.
PMID: 41945322
Cleft Lip Repair: Trends of Nasoalveolar Molding, Concomitant Tip Rhinoplasty and/or Septoplasty, and Revisions Using a National Database Study.
Cleft Lip Repair: Trends of Nasoalveolar Molding, Concomitant Tip Rhinoplasty and/or Septoplasty, and Revisions Using a National Database Study. J Craniofac Surg. 2026 Jul-Aug 01; 37(7-8):1870-1873.
PMID: 41871296
Unlocking 3D baby face photogrammetry: Multi-view BabyMorph reconstruction from uncalibrated photographs.
Unlocking 3D baby face photogrammetry: Multi-view BabyMorph reconstruction from uncalibrated photographs. Expert Syst Appl. 2026 Jun 10; 315.
PMID: 42344860
Craniometrics in Metopic Craniosynostosis: A Review of Craniometric Parameters and the Emergence of Machine Learning Models.
Craniometrics in Metopic Craniosynostosis: A Review of Craniometric Parameters and the Emergence of Machine Learning Models. J Craniofac Surg. 2026 05 01; 37(5):1024-1031.
PMID: 41528319
Sociodemographic Predictors of County-Level Mammography Screening Rates in the United States.
Sociodemographic Predictors of County-Level Mammography Screening Rates in the United States. Radiol Imaging Cancer. 2025 11; 7(6):e240433.
PMID: 41134138
Population-Driven Synthesis of Personalized Cranial Development From Cross-Sectional Pediatric CT Images.
Population-Driven Synthesis of Personalized Cranial Development From Cross-Sectional Pediatric CT Images. IEEE Trans Biomed Eng. 2025 09; 72(9):2732-2741.
PMID: 40100672
Secondary Cranioplasty After Fronto-Orbital Advancement: Analysis of a National Database.
Secondary Cranioplasty After Fronto-Orbital Advancement: Analysis of a National Database. J Craniofac Surg. 2025 Sep 01.
PMID: 40888846