Stanford University
Showing 14,951-15,000 of 36,312 Results
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Andrei Kanavalau
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
BioPhD candidate in Electrical Engineering at Stanford working across LLMs/Transformers, constrained optimization, and control.
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Beverley Kane
Adjunct Clinical Assistant Professor, Medicine - Primary Care and Population Health
BioBeverley Kane, MD, was Board Certified in Family Medicine, then completed fellowships in Ob-Gyn (San Francisco Children's Hosptial) and Sports Medicine (London Univeristy). She has worked in the private practice of sports medicine; in medical informatics, specializing in doctor-patient communication (WebMD); and in stress management with her private practice, Horsensei Equine-Assisted Learning & THerapy (HEALTH). Her latest book, "Equine-imity--Stress Reduction and Emotional Self-Regulation in the Company of Horses," published 27 March 2021, can be seen at http://equine-imity.com/
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Peter William Earl Kane
Affiliate, Genetics
BioPeter leads GENE240: Multiomic Patient Cases, and Research to the People, a program for open patient-partnered research in oncology and rare disease.
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Guson Kang
Clinical Assistant Professor, Medicine - Cardiovascular Medicine
BioDr. Kang is an interventional cardiologist who specializes in the treatment of structural heart disease. He is an expert in complex coronary interventions, transcatheter aortic, mitral, and tricuspid valve replacements, transcatheter mitral and tricuspid valve repair, left atrial appendage occlusion, PFO/septal defect closure, alcohol septal ablation, paravalvular leak closure, balloon pulmonary angioplasty, and pulmonary vein stenting.
A Bay Area native, he graduated from Stanford University and obtained his medical degree at Yale University. He came back to Stanford to train in internal medicine, cardiology, and interventional cardiology before completing an advanced structural interventions fellowship at Ford Hospital. -
Hangoo Kang
Masters Student in Computer Science, admitted Autumn 2025
BioHangoo Kang is a computer science MS student at Stanford University with a strong interest in building trustworthy and efficient AI systems. He earned his B.S. in Computer Science from the University of Illinois Urbana-Champaign (UIUC). His academic and research pursuits span reinforcement learning (RL), reinforcement learning from human feedback (RLHF), agentic AI, large language models (LLMs), and multi-modal models.
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Hyunmin Kang
Affiliate, Center for Sustainable Development and Global Competitiveness
BioHyunmin Kang is an Assistant Professor in the Department of Psychology at Daegu Univeristy in South Korea. He received his Ph.D. in Cognitive Engineering at Yonsei University. He conducts research within the Human-Urban Interaction pillar, examining the interactions between humans, cities, culture, transportation, technology, and services based on psychological and human factors theories. His research particularly utilizes quantitative and qualitative analysis, big data analytics, and metaverse technologies. His goal is to conduct research that contributes to improving the lives of people living in urban environments by deepening the understanding of human behavior.
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Hyunseok Kang
Professor of Medicine (Oncology)
Current Research and Scholarly InterestsMy research interest lies in development of precision oncology based approaches and novel therapeutics for rare cancers of head and neck, including adenoid cystic cancers, salivary duct cancers, sinonasal cancers and thyroid cancers.
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Jennifer Kang
Academic Prog Prof 2, Pediatrics - Infectious Diseases
Current Role at StanfordProgram Manager, Global Child Health Program
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Xiaojian Kang
Affiliate, Rad/Veterans Affairs
BioDr Kang received his PhD in Physics and MS in Computer Science from Indiana University Bloomington in September of 1998. Then he joined Diagnostic Imaging Science Center at University of Washington in Seattle for postdoctoral research.
In September of 2000, he worked as an MR Physicist in the Human Cognitive Neurophysiology Laboratory in Department of Neurology at University of Californian at Davis. His tasks were to maintain and modify the sequences for MR research on a 3 T Siemens Verio scanner and a 1.5 T Philips Eclipse scanner, and develop new procedures for MR data analysis, statistics and visualization. He has published 40+ papers to introduce the innovative methods for MR data analysis, which including the local landmark method, high-resolution space method, and cortical surface projection mapping method, and automated method to detect brain abnormalities. All of the methods have been applied successfully to the MR researches in the lab.
In September of 2017, he joined as an MR Physicist in Palo Alto Veterans Institute for Research (PAVIR) at VA Palo Alto and the Adamson Brain Stimulation Lab in the Department of Neurosurgery at Stanford University.His main tasks are to participate in the research projects using GE and Siemens MR scanners funded by Department of Veterans Affairs and Department of Defense, and administration of windows and linux servers for neuroimaging studies.
Professional Education
•PhD in Physics, Indiana University Bloomington (1998).
•MS in Computer Science, Indiana University Bloomington (1998).
•MS in Electronic Engineering, Xi’an Jiaotong University, P. R. China (1987).
•BS in Electronic Engineering, Xi’an Jiaotong University, P. R. China (1984).
