Lab Members

Kwan performs research in clinical and translational multimodality cardiac imaging, with a focus in cardiac MRI and coronary CT. He attended the University of Washington School of Medicine, with a fellowship year at the National Institutes of Health, and completed his internal medicine residency at Johns Hopkins Hospital.  

Waseem obtained his MD and completed his internal medicine residency at McMaster University in Hamilton, Ontario. He completed his cardiology fellowship at the University of Calgary in Alberta. Waseem has an interest in the application of multi-modal imaging in complex cardiovascular disease and the use of artificial intelligence to guide risk prediction and image optimization.

Naga earned his MD from Keck School of Medicine, University of Southern California. He completed his internal medicine residency and general cardiology fellowship at the University of Wisconsin-Madison. He is currently pursuing further clinical expertise and research in multimodal cardiac imaging at Cedars-Sinai hoping to contribute significantly to the prognostic ability of non-invasive imaging in cardiology.

Sevan earned her MD and from the University of Manitoba, Canada, and completed her internal medicine residency and general cardiology fellowship at Sourasky Medical Center, Israel. She then went on to complete a fellowship in electrophysiology at the University of Calgary, Canada.  She’s currently pursuing further clinical and research expertise in multimodal cardiac imaging at Cedars-Sinai.

Kyehwan earned his MD and PhD from Gyeongsang National University, where he also completed his internal medicine residency and cardiology fellowship. He has a strong interest in multimodal imaging and his goal is to enhance patient care and contribute to research through advanced cardiovascular imaging.

Tomasino received her MD from the University of El Salvador School of Medicine. She started as a clinical research associate before promoting to a postdoctoral scientist, working closely with the Dey Lab. At Cedars-Sinai, she implements AutoPlaque, an AI-enabled software which characterizes plaque from coronary CT angiography images.

Han earned his MD from Yeungnam University College of Medicine, South Korea, and his fellowship at the Dalio Institute of Cardiovascular Imaging at Weill Cornell Medicine. After training, he was an assistant clinical research professor at Yonsei Cardiovascular Center. Han is currently an IM Resident at Cedars-Sinai and his goal is to become a physician-scientist.

Park earned her psychology degree from UCSD and her master of public health in global health from Liberty University. Previously, Park was the lead coordinator of clinical trials that lead to the FDA approval of Otiprio®. She has also participated/led worldwide mission trips, focusing on children’s programs/health promotion.

Asebiomo earned her BS in physiological science from UCLA, with aspirations towards a career as a physician. Her past research projects were mainly conducted in the UCLA department of neurosurgery, with a focus on Traumatic Brain Injury and stress. Additionally, she’s gained clinical experience through an internship with UCLA’s Sports Medicine Department.

Divyani trained in Medicine at Government Medical College, Amritsar. She completed her postdoctoral fellowship at Yale School of Medicine where she developed machine learning methods to improve the diagnosis of cardiac amyloidosis and microvascular CAD. Her research interests include the development of methods to improve imaging modalities in cardiology and characterizing the gray areas between imaging and real-world patient populations.

Hyun received his education and clinical training from Los Angeles County + USC Medical Center Department of Radiology and Nuclear Medicine Technology. Upon graduation, Hyun was a staff and research technologist at Cedars-Sinai, then promoted to a lead technologist, responsible for supervising technical activities at Tower Nuclear/Cardiac and Vascular Lab.  

Killekar earned his engineering degree from the University of Southern California and worked there as a research programmer implementing deep learning-based methods for detecting deepfake face manipulations. Currently at Cedars-Sinai, Killekar works on developing a deep learning-based real-time detection and segmentation of COVID-19 lesions on noncontrast chest CT.

Manral earned his masters degree in electrical engineering from the University of Southern California. He specializes in machine-learning, deep-learning and data-mining technologies and is currently working on the applications of deep learning for plaque segmentation using CTA images. Prior to Cedars-Sinai, Nipun worked as a systems engineer in Germany and India.