Rate My Professor Fabien Scalzo

Dr. Scalzo's research specializes in building computational models for neuroimaging and has pioneered the use of machine learning in stroke analysis. He has published over 200 research papers, including highly influential works such as 'Ischemia-reperfusion injury in stroke' (Interventional Neurology, 2013), 'Deep learning for hemorrhagic lesion detection and segmentation on brain CT images' (IEEE Journal of Biomedical and Health Informatics, 2020), 'Morphological clustering and analysis of continuous intracranial pressure' (IEEE Transactions on Biomedical Engineering, 2008), 'Reducing backward masking through action game training' (Journal of Vision, 2010), and 'A machine learning approach for classifying ischemic stroke onset time from imaging' (IEEE Transactions on Medical Imaging, 2019). Recent contributions include 'Peak detection in intracranial pressure signal waveforms: a comparative study' (2024), 'Mask R-CNN assisted 2.5D object detection pipeline of 68 Ga-PSMA-11 PET/CT-positive metastatic pelvic lymph node after radical prostatectomy from solely CT imaging' (2022), and 'Historical Perspectives in Volatility Forecasting Methods with Machine Learning' (2025). As principal investigator, he has secured funding from the National Institutes of Health (NIH), National Science Foundation (NSF), American Heart Association (AHA), and Defense Advanced Research Projects Agency (DARPA) for neuroscience projects. Dr. Scalzo is Associate Editor for Frontiers in Neurology and recipient of the NSF China Young Scholar award and BAEF fellowship. His scholarship significantly impacts clinical diagnostics, advancing AI-driven solutions for neurological disorders and medical imaging.