Overview
As a physician scientist focused on artificial intelligence (AI) applications for neurologic disease, my ongoing career goal is to combine clinical excellence in neuroradiology with cutting-edge AI research. My primary research interest lies in the use of innovative AI techniques to help extract clinically useful information from multimodal health data with a focus on neuroimaging. Modern neuroimaging studies, most notably multi-sequence MRI, are amongst the largest and most complex types of health data that are routinely acquired for patients with neurologic disorders. I believe that modern AI tools have enormous potential to help extract new, clinically useful information from complex neuroimaging studies, and through integration with other types of health data, will ultimately improve diagnosis, management, and treatment monitoring for patients with neurologic disease.
Current Appointments & Affiliations
Recent Publications
Machine learning-based prognostic subgrouping of glioblastoma: A multicenter study.
Journal Article Neuro Oncol · May 15, 2025 BACKGROUND: Glioblastoma (GBM) is the most aggressive adult primary brain cancer, characterized by significant heterogeneity, posing challenges for patient management, treatment planning, and clinical trial stratification. METHODS: We developed a highly re ... Full text Link to item CiteDevelopment and Evaluation of Automated Artificial Intelligence-Based Brain Tumor Response Assessment in Patients with Glioblastoma.
Journal Article AJNR Am J Neuroradiol · May 2, 2025 This project aimed to develop and evaluate an automated, AI-based, volumetric brain tumor MRI response assessment algorithm on a large cohort of patients treated at a high-volume brain tumor center. We retrospectively analyzed data from 634 patients treate ... Full text Link to item CiteOpen-Weight Language Models and Retrieval-Augmented Generation for Automated Structured Data Extraction from Diagnostic Reports: Assessment of Approaches and Parameters.
Journal Article Radiol Artif Intell · May 2025 Purpose To develop and evaluate an automated system for extracting structured clinical information from unstructured radiology and pathology reports using open-weight language models (LMs) and retrieval-augmented generation (RAG) and to assess the effects ... Full text Link to item CiteRecent Grants
Building and implementing a TBI prognostic model featuring real-time analysis of brain CT images
ResearchCo Investigator · Awarded by National Institutes of Health · 2022 - 2027Federated Learning for Postoperative Segmentation of Treated Glioblastoma (FL-PoST)
ResearchPrincipal Investigator · Awarded by American Roentgen Ray Society · 2024 - 2026Prospective Evaluation of Automated Pre- and Postoperative Tumor Segmentation for Patients with Glioblastoma
ResearchPrincipal Investigator · Awarded by Neuroradiology Education and Reserach Foundation (formerly Foundation of the ASNR) · 2022 - 2024View All Grants