Stanford University
Showing 1,661-1,680 of 2,678 Results
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Lamprini Papargyri
Postdoctoral Scholar, Earth System Science
BioLamprini Papargyri is a postdoctoral scholar at Stanford University co-advised by Professor Steve Davis and Dr. Ken Caldeira. She earned her PhD in Civil and Environmental Engineering from the University of Cyprus, where she worked under the guidance of Professor Panos Papanastasiou to optimize the durability of materials used in photovoltaic systems. Her doctoral research employed advanced computational modeling using 3D finite element methods and XFEM to simulate stress, cracking, and degradation mechanisms in photovoltaic materials.
At Stanford, Lamprini’s research lies at the intersection of climate policy, economics, and equity. Her current work explores how economies with income inequality can optimally allocate resources between income redistribution and emissions abatement. Beyond research, she has led and contributed to multi-million-euro research initiatives across Europe and remains deeply interested in the societal and ethical dimensions of emerging technologies. Broadly, she is interested in developing integrated models that inform equitable and sustainable pathways for climate mitigation and economic development. -
Sara Pardej
Postdoctoral Scholar, Psychiatry
BioSara Pardej earned her BA in Psychology and BS in Cognitive Science at Marquette University. Afterwards, she attended the Clinical Psychology Doctoral Program at the University of Wisconsin-Milwaukee under the mentorship of Dr. Bonita P. Klein-Tasman, where she earned both her MS and PhD in Clinical Psychology. There, she worked on several studies focusing on youth with neurofibromatosis type 1 (NF1), including behavioral phenotyping work, psychometric studies, and a social skills intervention study. Her dissertation study, which was funded by a Young Investigator Award from the Children's Tumor Foundation, focused on examining event related potentials using EEG by comparing children with NF1 to children with idiopathic ADHD and unaffected children. She completed her Doctoral Internship in Clinical Psychology at Penn State Health in Hershey, Pennsylvania. While at Penn State, she also worked on research examining safety and psychopathology in youth with ADHD and/or autism. Her clinical interest is neuropsychology, and her research interests include issues of psychometrics, behavioral phenotyping, and the neuropsychological development (and subsequent areas of intervention) of individuals with NF1 across the lifespan.
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Anna Parenteau
Postdoctoral Scholar, Education
BioPostdoctoral Fellow at the Stanford Center on Early Childhood
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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.
