Principal investigator

Dr. Aalami is a Clinical Professor of Vascular & Endovascular Surgery at Stanford University and the Palo Alto VA and serves as the Director of Stanford’s Biodesign for Digital Health. He is the course director for Biodesign for Digital Health, Building for Digital Health and co-founder of the open-source project, CardinalKit, developed to support sensor-based mobile research projects. His primary research focuses on clinically validating the sensors in smartphones and smartwatches in patients with cardiovascular disease and translation of digital health solutions.

Developer of AutoABI

Adrit is a 15-year-old high school student conducting research at Stanford University. His primary research interests include the development of novel artificial intelligence algorithms to solve healthcare problems, accessible innovations which can be deployed at the point-of-care, and interpretability of medical computer vision algorithms. He is leading various research efforts and has authored several research publications. Adrit has presented his work at various international conferences and prestigious societies. He is an iOS app developer with 4 apps published on the App Store and the CEO of a non-profit, Aretech Inc., which aims to solve real-world problems. His notable accomplishments include being a WWDC Scholar ('20, '21), ISEF Grand Awardee ('22), and being inducted into Sigma Xi and named a Top Presenter ('22).

Technical advisor

Dr. Chaudhari is an Assistant Professor in the Department of Radiology and (by courtesy) in the Department of Biomedical Data Science. He leads the Machine Intelligence in Medical Imaging research group at Stanford and has a primary research interest that lies at the intersection of artificial intelligence and medical imaging. Dr. Chaudhari is interested in the application of artificial intelligence techniques to all aspects of medical imaging, including automated schedule and reading prioritization, image reconstruction, quantitative analysis, and prediction of patient outcomes. His interests range from developing novel data-efficient machine learning algorithms to clinical deployment and validation of patient outcomes, both for medical imaging acquisition and subsequent analysis. He also conducts research in combining imaging with clinical, natural language, and time series data.

Data acquisition and clinical validation

Kevin Battenfield is a Senior Vascular Technologist in Cardiovascular Diagnostic Testing Lab in Emeryville, CA for Stanford Medicine. He works with Vascular Surgeons Dr. Kasirajan and Dr. Avise and provides accurate diagnostic ultrasound studies. Kevin is interested in assisting in research to improve accuracy of ultrasound imaging and diagnostics for better patient outcomes and treatment. He enjoys sharing his clinical experience with research and development to advance medical imaging.

Data acquisition

Arash is a Vascular Surgery resident at Stanford University, training to care for patients with complex vascular disease while also pursuing innovations that improve the clinical care of patients and the education of trainees. Arash has published numerous manuscripts and presented at many national surgery conferences on topics in vascular biology and clinical outcomes using large databases. His new research focus is the use of new imaging and radiologic advances in vascular surgery.