Rate My Professor Antonio Porras

Antonio Porras, PhD, serves as Assistant Professor with Tenure in the Department of Biostatistics and Informatics at the Colorado School of Public Health, University of Colorado Anschutz Medical Campus, a position he has held since 2020. He is also Director of Research in the Department of Pediatric Plastic and Reconstructive Surgery at Children’s Hospital Colorado and holds secondary faculty appointments in the Departments of Biomedical Informatics, Pediatrics, and Surgery within the School of Medicine. Porras obtained his PhD in Medical Image Computing from Pompeu Fabra University in Barcelona, Spain, in 2015, earning summa cum laude and the International Quality Award from the Spanish Government. He holds an MSc in Biomedical Engineering from the University of Barcelona and Polytechnic University of Catalonia in 2010, a BSc in Computer Engineering from the University of Cordoba in 2008, and a BSc in Technical Engineering in Computer Systems from the same institution in 2006. Before joining CU Anschutz, he was a Staff Scientist from 2016 to 2020 and Postdoctoral Research Fellow from 2015 to 2016 at the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children’s National Hospital in Washington, DC. Earlier roles include instructor and research assistant at Pompeu Fabra University from 2011 to 2015 and research positions at Chalmers University of Technology in Sweden and the University of Barcelona in Spain.

Porras’ research focuses on developing computational methods and machine learning tools for medical image analysis to enhance the understanding, diagnosis, and treatment of pediatric pathologies, particularly craniofacial anomalies like craniosynostosis and genetic syndromes. Notable publications include “Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study” in The Lancet Digital Health in 2021, demonstrating 88% screening accuracy across diverse populations; “Cranial bone thickness and density anomalies quantified from CT images can identify chronic increased intracranial pressure” in Neuroradiology in 2024; and “Predictive statistical model of early cranial development” in IEEE Transactions on Biomedical Engineering in 2021, featured as a highlighted paper. His work has garnered numerous accolades, such as the Best Paper Award at the MICCAI Workshop on Clinical Image-based Procedures in 2016, induction into the Delta Omega National Honors Society for Public Health in 2022, multiple journal covers in the American Journal of Medical Genetics – Part A from 2017 to 2018, and top cited article recognitions. Porras teaches machine learning and biomedical image analysis courses, directs the Medical Imaging and Machine Intelligence lab, and has mentored award-winning students. His contributions have advanced early detection of genetic syndromes and personalized surgical planning.