Faculty Affiliates

Ryan Broderick is an Associate Professor of Clinical Surgery in the Division of Minimally Invasive Surgery and serves as the Interim Director of the Center for the Future of Surgery. He and his research team are focused on the use of spatial computing in surgery and surgical education.

As Vice Chair of Perioperative Informatics in the Department of Anesthesiology, Dr. Gabriel oversees research efforts related to data science and AI initiatives related to perioperative medicine across all specialty divisions within the department.

Dr. Sitapati serves as a national leader who innovates in applied health informatics with expertise in registries (co-PI of the California Integrated Vital Records System), precision medicine (MPI for NIH All of Us at UCSD), artificial intelligence (risk models, machine learning, LLM), and quality informatics that advances health equity.

Dr. Ming Tai-Seale is a professor and health services researcher whose expertise lies in patient-physician communication, health policy, and the impact of artificial intelligence, information technology and financial incentives on clinical and economic outcomes, patient experience, and physician well-being.

Dr. Jaffe is the Chief Executive Officer of HL7 International and a Visiting Scholar in Biomedical Informatics at UC San Diego. HL7 recently released their strategic approach to AI, which has 4 pillars: standards, global leadership and partnerships, an AI innovation lab, and community excellence.

Dr. Ustun develops methods to promote the adoption and responsible use of machine learning in healthcare, focusing on challenges such as safety, interpretability, personalization, and fairness.

Dr. Ammar Mandvi is a family physician and clinical informaticist specializing in the implementation of AI and data-driven technologies to improve primary care delivery, education, and research.

Dr. Baxter conducts research at the nexus of ophthalmology and biomedical informatics and has specific interests in health information technology integration, multimodal AI models of eye disease, and research training and education programs.

Dr. Clay has served 12 years of service as Chief Medical Information Officer at UC San Diego Health. He is currently associate program director for the clinical informatics fellowship. As associate CMO, his work focuses on patient flow and hospital capacity, and leverages EHR-based tools, clinical decision support, and analytics to standardize workflows and improve metrics in this space.

Dr. Gabriel Wardi is an associate professor and emergency medicine physician cross-trained in critical care medicine who is Chief of the Division of Critical Care in the Department of Emergency Medicine. He is an NIH-funded researcher who focuses on implementation and optimization of machine-learning models to improve care of sepsis patients.

The core focus of Aaron Boussina's research is the development and implementation of predictive and generative systems in healthcare settings.

Dr. Ramsis' work consists of validating algorithms for remote cardiovascular disease detection, leveraging artificial intelligence to predict disease using electronic health record data, and developing digital biomarkers.

Dr. Ross specializes in applying artificial intelligence, implementation science, and outcomes research to improve early detection and equitable management of vascular diseases.

Implementation of telehealth solutions that streamline patient navigation and advance quality improvement across the care continuum.

Pengtao Xie 's work mainly focuses on LLM reasoning and foundation models for biomedical applications.

The main focus of his research is at the intersection of image analysis (computer vision and medical image computing), machine learning and data science.

Dr. Chan's research interests include ED crowding and efficiency, informatics in health care and tactical, disaster and prehospital medicine.

Nemati's research team is broadly interested in developing computational tools and machine learning algorithms for analysis of medical data, with the goal of phenotyping patients, tracking patients' trajectory, predicting impending events and optimizing treatment strategies to avoid/mitigate adverse outcomes.

Expertise: Tissue specific, neurophysiological and psychosocial contributions to the development and maintenance of spine pain and pathology using clinical, biological, physiological and imaging-based approaches.