School of Medicine
Showing 61-70 of 102 Results
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Lu,Guolan
Assistant Professor of Urology
Current Research and Scholarly InterestsThe Lu Lab develops spatial omics and AI technologies to measure, model, and predict how cells, tissues, and therapeutic agents interact in their native spatial context, and how these interactions drive disease progression and treatment response.
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Alan C. Pao
Associate Professor of Medicine (Nephrology) and, by courtesy, of Urology
Current Research and Scholarly InterestsWe are broadly interested in how the kidneys control salt, water, and electrolyte homeostasis in the body. Our disease focus is on kidney stone disease. We use cultured kidney cells, transgenic mice, human plasma/urine samples, and electronic health record data to study the pathogenesis of kidney stone disease. Our therapeutic focus is on the development of small molecule compounds that can be used for kidney stone prevention.
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Christopher K. Payne, MD
Professor of Urology at the Stanford University Medical Center, Emeritus
Current Research and Scholarly InterestsObstetric Fistula Projects:
1. Preoperative ultrasound evaluation to detect ureteric involvement in vesicovaginal fistulas
2. Patient narrative study to identify key medical, social and economic factors that lead to fistula formation
3. Study of urinary continence after fistula repair
Pelvic pain: investigation into role of pelvic floor in chronic pelvic pain -
Donna Peehl, PhD
Professor (Research) of Urology, Emerita
Current Research and Scholarly InterestsMy research focuses on the molecular and cellular biology of the human prostate. Developing realistic experimental models is a major goal, and primary cultures of prostatic epithelial and stromal cells are my main model system. Our discoveries are relevant to prevention, detection, diagnosis and treatment of benign and malignant prostatic diseases.
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Tanmoy Sarkar Pias
Postdoctoral Scholar, Urology
BioI am currently working on multimodal, multi-task foundation models to detect cancer and improve surgery. I am exploring image segmentation models, foundation models, and reinforcement learning with agents. My previous work spans a range of directions, including knowledge-guided machine learning models, systematic evaluation of high-risk models, mitigation of deficiencies and biases, automatic generation of gradient-based test cases, decision boundary estimation and analysis of deep learning models, and developing approaches to make machine learning models more fair and reliable.
