Stanford University
Showing 2,281-2,300 of 37,050 Results
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James M Baxter
Associate Scientist, SLAC National Accelerator Laboratory
BioInterested in understanding small things that move quickly:
- Ultrafast crystallography for protein and small-molecule dynamics
- Ultrafast microscopy and spectroscopy of proteins and materials
- Quantum imaging and quantum X-ray science -
Mohsen Bayati
Carl and Marilynn Thoma Professor in the Graduate School of Business and Professor, by courtesy, of Electrical Engineering and of Radiation Oncology (Radiation Therapy)
Current Research and Scholarly Interests1) Healthcare management: I am interested in improving healthcare delivery using data-driven modeling and decision-making.
2) Network models and message-passing algorithms: I work on graphical modeling ideas motivated from statistical physics and their applications in statistical inference.
3) Personalized decision-making: I work on machine learning and statistical challenges of personalized decision-making. The problems that I have worked on are primarily motivated by healthcare applications. -
Tina Baykaner
Assistant Professor of Medicine (Cardiovascular Medicine)
BioTina Baykaner, MD, MPH is an Assistant Professor of Medicine in the Division of Cardiovascular Medicine and Cardiac Electrophysiology at Stanford University School of Medicine. She completed residency and fellowships in cardiovascular medicine and advanced heart failure at the University of California, San Diego, followed by fellowship training in cardiac electrophysiology at Stanford. She joined the Stanford faculty in 2018 and was promoted to Assistant Professor in 2023.
Dr. Baykaner’s research program focuses on atrial fibrillation (AF), cardio-oncology, and the integration of artificial intelligence and machine learning into cardiac electrophysiology. She is Principal Investigator of an NIH R01 investigating atrial fibrillation in patients with hematologic malignancies treated with tyrosine kinase inhibitors and previously led an NIH K23 award focused on personalizing AF management using machine learning. She also serves as co-investigator or consultant on multiple NIH-funded R01 projects in artificial intelligence, ventricular arrhythmias, and digital cardiovascular phenotyping. Her work spans AF mechanisms, ablation outcomes, digital health implementation, and equity in arrhythmia care.
She has authored over 200 peer-reviewed publications, book chapters, and abstracts, including more than 100 original research manuscripts, and has delivered over 100 invited lectures nationally and internationally. She served as a task force member for the 2024 EHRA/HRS/APHRS/LAHRS Expert Consensus Statement on Catheter and Surgical Ablation of Atrial Fibrillation and holds editorial leadership roles, including Associate Editor for the Journal of Interventional Cardiac Electrophysiology and editorial board positions with multiple electrophysiology journals.
Dr. Baykaner is Vice-Chair of the Heart Rhythm Society Digital Education Committee and serves on national program and grant review committees, including NIH/NHLBI study sections. She is actively engaged in mentorship across undergraduate, medical, graduate, and postdoctoral levels, with mentees who have received national awards and progressed to electrophysiology fellowship and faculty positions.
Her clinical practice focuses on catheter ablation of atrial and ventricular arrhythmias, supraventricular tachycardias, management of inappropriate sinus tachycardia, cardiac implantable electronic device implantation and extraction, and advanced rhythm management strategies in complex patient populations.
