Dermatology


Showing 81-90 of 146 Results

  • Chaw Ning Lee

    Chaw Ning Lee

    Clinical Instructor, Dermatology

    BioDr. Chaw-Ning Lee is a dermatologist and completed her dermatology education at National Cheng Kung University and Hospital and is a member of Taiwan Dermatology Association and Taiwanese Society for Investigative Dermatology. She earned her Ph.D. in pharmacoepidemiology and has experience in real-world evidence and Phase IV post-marketing studies using large databases. Since November 2023, Dr. Lee has been a visiting scholar in Program in Epithelial Biology and Pediatric Dermatology, Department of Dermatology at Stanford University. Her areas of special interest include skin cancer, pharmacoepidemiology, psoriasis, pediatric dermatology and drug eruptions.

  • Jinwoo Lee, MD, PhD, FAAD

    Jinwoo Lee, MD, PhD, FAAD

    Instructor, Dermatology

    BioJinwoo Lee, M.D., Ph.D. is a board-certified dermatologist and clinical faculty in the Department of Dermatology. Dr. Lee completed his residency in dermatology at Stanford University, where he joined the Investigative Training Track to conduct basic science research in autoimmunity and inflammation. Dr. Lee’s scientific research focuses on identifying the mechanisms underlying the onset and progression of autoimmune diseases. His clinical interests include medical management of complex dermatologic conditions, autoimmune skin diseases, as well as general dermatology.

    Dr. Lee is currently only seeing patients on Monday afternoons at the Stanford Medicine Outpatient Center in Redwood City.

  • Ramrada Lekwuttikarn MD

    Ramrada Lekwuttikarn MD

    Clinical Instructor, Dermatology

    BioRamrada Lekwuttikarn, MD is a pediatric dermatologist and clinical investigator in the Division of Pediatric Dermatology at Stanford University School of Medicine and Lucile Packard Children’s Hospital. She serves as a Research Scientist and Clinical Instructor with expertise in vascular anomalies, genetic skin diseases, and inflammatory skin disorders.

    Dr. Lekwuttikarn received her medical degree and pediatric training at Ramathibodi Hospital, Mahidol University, Thailand, and completed subspecialty training in pediatric dermatology at King Chulalongkorn Memorial Hospital in Thailand. She subsequently completed clinical research fellowships at the Children’s Hospital of Philadelphia and Stanford University. Prior to joining Stanford, she served as Chief of Pediatric Dermatology and Assistant Professor at Ramathibodi Hospital.

    Her work focuses on translational research and clinical trials developing targeted therapies for complex pediatric skin diseases.

  • Matt Lewis, MD, MPH

    Matt Lewis, MD, MPH

    Clinical Associate Professor, Dermatology

    BioDr. Lewis specializes in autoimmune skin diseases. He completed medical school at The George Washington University School of Medicine and dermatology residency at The University of Rochester, where he was chief resident. He also completed a Master’s of Public Health at Johns Hopkins and a fellowship in autoimmune connective tissue diseases at Stanford University.

    He believes multidisciplinary care is key to treat patients with systemic inflammatory diseases. He holds a rheumatology-dermatology clinic with a rheumatologist, Dr. Janice Lin, as well as a dermatology-ophthalmology clinic with an ophthalmologist, Dr. Christopher Ta, and is the dermatologist for the sarcoidosis program, all with this primary goal of providing high quality, collaborative, patient-centered care.

  • Dayan J. Li, MD, PhD

    Dayan J. Li, MD, PhD

    Clinical Scholar, Dermatology
    Postdoctoral Scholar, Pediatric Surgery

    Current Research and Scholarly InterestsWound healing, cutaneous fibrosis

  • Matthias Christian Lutz

    Matthias Christian Lutz

    Graduate, Medicine, Dermatology

    BioI am a medical student at the Technical University of Munich and a Student Researcher at the Stanford Mussallem Center for Biodesign, where I conduct my doctoral research under the supervision of Dr. Paul Schmiedmayer. My work is centered at the intersection of artificial intelligence and medicine, with a strong focus on translating advanced machine learning approaches into clinically meaningful applications.
    At Stanford, my research focuses on cardiovascular medicine, where I develop personalized, multimodal large language model (LLM)-based systems to detect early progression of Cardio-Kidney-Metabolic (CKM) disease and support more precise, data-driven clinical decision-making. By integrating electronic health record data, wearable time-series signals and patient communication, my work aims to create explainable, guideline-aligned AI systems that deliver personalized feedback and smart nudges. The overarching goal is to strengthen health literacy, improve patient activation and enable earlier, more effective prevention of cardiometabolic disease progression.
    I ranked among the top 1% nationwide in Germany’s first written medical licensing examination and gained over two years of experience at Brainlab in Clinical Affairs, where I contributed to international clinical trials and regulatory processes in the MedTech sector. These experiences shaped my interest in translational research at the interface of clinical practice, technology development, and implementation.
    Beyond my research I am the co-founder and previous chair of OneAIM (one-aim.org), a student-led MedTech initiative that has grown into the largest organization of its kind in Germany, connecting over 500 students across medicine, engineering and computer science through interdisciplinary innovation programs. In parallel, I am actively involved in shaping medical education: As the only student member of the curriculum commission at the Technical University of Munich, I play a leading role in integrating digital medicine into the medical curriculum. I also served as the instructor for the elective course “Neural Networks - AI in Medicine” at LMU Munich, introducing students to the intersection of clinical medicine and artificial intelligence.
    My broader goal is to advance clinically grounded, explainable AI systems that not only improve decision-making but also empower patients and physicians, bridging the gap between technological innovation and real-world healthcare impact.