School of Medicine
Showing 21-30 of 71 Results
-
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.
-
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.
-
Akshay Paruchuri
Postdoctoral Scholar, Psychiatry
AI4ALL Graduate Mentor, Stanford Pre-Collegiate StudiesBioI'm a postdoctoral scholar at Stanford University, advised by Professor Ehsan Adeli. I'm affiliated with the Stanford Translational AI (STAI) Lab and the Stanford Vision and Learning (SVL) Lab. I earned my PhD in computer science at UNC Chapel Hill under the advisement of Professor Henry Fuchs. I build and evaluate multimodal AI systems, from general-purpose methods for interactive computing to applications in healthcare. Currently, I'm working toward a future where multimodal AI can safely and reliably integrate into healthcare systems in order to improve the entire patient journey, from advanced diagnostic imaging and surgical support to all-day health monitoring and management, with the aim 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 that benefit people everywhere, whether through foundational research, real-world products, or shaping how these systems are evaluated and deployed.
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.