School of Medicine
Showing 961-980 of 1,556 Results
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Junyoung Park
Postdoctoral Scholar, Neurology and Neurological Sciences
BioDr. Jun Young graduated from the Department of Biostatistics at the School of Public Health, Seoul National University, Korea. His major field of study is biostatistics, with a specific focus on the application of machine learning and statistical analysis to medical imaging and genetic data. During his doctoral studies, he concentrated on two primary research areas. Firstly, he dedicated himself to the development of deep learning models for medical images, primarily centered on T1-MRI and cognitive function test images related to Alzheimer's Disease. Secondly, he engaged in extensive genome-wide association analyses of medical images associated with Alzheimer's Disease, using statistical algorithms to uncover novel insights into the genetic factors contributing to this complex condition. Currently, as a postdoctoral fellow at the Greicius Lab at Stanford, he aims to develop statistical methods to discover novel structural variants and model polygenetic risk scores using long-read sequencing data.
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Namu Park
Postdoctoral Scholar, Biomedical Informatics
BioDr. Park is a Postdoctoral Scholar at the Division of Computational Medicine at Stanford University, where he is co-advised by Dr. Tina Hernandez-Boussard and Dr. Yair Bannet. He received his PhD in Biomedical and Health Informatics from the University of Washington.
His research focuses on clinical natural language processing and large language models for healthcare. He develops clinically grounded information extraction methods and evaluation frameworks that reflect real-world clinical workflows. His work examines how large language models can be aligned with clinical reasoning and rigorously evaluated for safe and effective deployment in health systems.
Through interdisciplinary collaboration, Dr. Park aims to bridge advances in foundation models with measurable clinical impact, emphasizing reliability, transparency, and scalability in AI-driven healthcare applications. -
Preethy Parthiban
Postdoctoral Scholar, Neonatal and Developmental Medicine
BioMy research centers on how the innate immune system shapes tissue remodeling in health and disease. During my PhD, I uncovered a key role for resident macrophages in driving cardiac fibrosis, identifying a macrophage-derived chemokine that directly activates cardiac fibroblasts. Building on this foundation, my postdoctoral work at Stanford focuses on neutrophil–macrophage crosstalk in disrupted alveolarization in neonatal mice and patients. By integrating cellular, molecular, and translational approaches, I aim to define how innate immune pathways orchestrate extracellular matrix remodeling. Ultimately, my goal is to identify critical therapeutic targets that improve outcomes in ECM-related diseases.
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Akshay Paruchuri
Postdoctoral Scholar, Psychiatry
BioI'm currently a postdoctoral scholar in the Stanford Translational AI (STAI) lab led by Professor Ehsan Adeli. I earned my PhD in computer science at UNC Chapel Hill under the advisement of Professor Henry Fuchs. My research interests are at the intersection of health AI, computer vision, and machine learning. Currently, I'm working toward a future where next-generation healthcare systems improve the entire patient journey, from advanced diagnostic imaging and surgical support to all-day health monitoring and management, to achieve better therapeutic outcomes for cancer and aging-related diseases. I'm generally interested in opportunities that would allow me to continue to deepen my research expertise while leading and working on projects with meaningful, positive real-world impact, especially with respect to areas such as healthcare and environmental sustainability.
Previously, I was a visiting researcher at IDSIA USI-SUPSI working with Professor Piotr Didyk on the interpretability of multimodal language models (MLMs) with respect to capabilities such as visual perception. I've published in leading venues on topics such as remote health sensing (WACV, NeurIPS), 3D reconstruction (ECCV, MICCAI), LLM-based conversational agents for personal health (EMNLP, Nature Communications), and energy-efficient operation of smart glasses (ISMAR). I've done internships at Google AR/VR, Google Consumer Health Research, and Kitware. -
Magdalini Paschali
Postdoctoral Scholar, Radiology
Current Research and Scholarly InterestsMy research focuses on utilizing machine learning models to enhance the understanding, diagnosis, and treatment of clinical disorders. I am interested in multi-modal learning, combining imaging data like MRI and CT scans with non-imaging data such as electronic health records, creating more holistic and accurate diagnostic models. I am also interested in the robustness of deep neural networks under domain shifts, investigating how models perform when faced with changes in input data distributions.
Finally, I am interested in early biomarker identification using AI model interpretability, to enable the early detection and targeted treatment of chronic disorders. -
Debarun Patra
Postdoctoral Scholar, Cardiovascular Institute
BioDebarun Patra is a postdoctoral researcher at Stanford Medicine, with a background in inflammation research. His research focuses on metabolic disease modeling and identifying novel therapeutic targets. His current work integrates inflammatory and metabolic diseases (IBD, MASH, and diabetes), using patient-derived iPS cells and primary cells, and employs advanced multi-omics.
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Suraj Pavagada
Postdoctoral Scholar, Radiology
BioSuraj Pavagada is a postdoctoral scholar at the Department of Radiology at Stanford University. His research focuses on exploiting magnetic levitation and optoelectronic techniques for applications in medical diagnostics.
Suraj received his PhD in Oncology from the University of Cambridge (24’), where he developed a new bioelectronic cell enrichment platform utilizing altered glycosylation patterns for the early detection of esophageal cancer. With a background in electrochemistry, surface functionalization, liquid biopsy, and molecular diagnostics, he is passionate about developing portable sensor technologies that can be translated into the clinic to facilitate timely diagnosis and monitoring. -
Andrea Pedroza Tobias
Instructor, Pediatrics - General Pediatrics
BioDr. Andrea Pedroza is an instructor in the Department of Pediatrics in the Partnerships for Research in Child Health Lab. She earned a Ph.D. in Global Health from the University of California, San Francisco (UCSF) and a Master of Science in Nutrition from the National Institute of Public Health in Mexico (INSP). Her research focuses on generating evidence for interventions and policy recommendations aimed at improving the dietary quality of children to impact their health and development. Currently, she is employing a community-engaged approach to design nutrition interventions and policy recommendations that aim to reduce the consumption of ultra-processed foods among low-income children to narrow the gap in health disparities.
