Carlos Cano Espinosa is a postdoctoral research fellow in the Applied Chest Imaging Laboratory (ACIL) at Brigham and Women's Hospital, Harvard Medical School. He obtained his Bachelor's degree in Computer Science and Master's degree in Robotics from the University of Alicante in Spain in 2014 and 2015, respectively. In 2019, he earned his international Ph.D. in Computer Science from the same university, focusing on medical image analysis. Prior to joining ACIL, Dr. Carlos worked with the FISABIO Foundation in Spain, where he contributed to the development of a tool for the diagnosis and prognosis of COVID-19 patients.

Dr. Carlos is currently developing generative models to simulate PET metabolic signals directly from CT scans. By utilizing deep learning techniques, these models are able to identify previously unseen patterns and relationships in the data, potentially providing new insights into disease causes and progression.
Throughout his career, Dr. Carlos has demonstrated a strong commitment to advancing the field of healthcare through innovative research. He has authored several publications in high-impact peer-reviewed journals and presented his work at various national and international conferences.
As a member of the ACIL team, Dr. Carlos collaborates with healthcare professionals and researchers to translate cutting-edge technologies into improved patient outcomes. He is dedicated to using his expertise to make a positive impact on the lives of patients.