Stanford University
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Sarah Sorice, MD
Clinical Associate Professor, Surgery - Plastic & Reconstructive Surgery
BioDr. Sorice-Virk is a board-certified, fellowship-trained plastic and reconstructive surgeon with the Stanford Health Care Cancer Center and a clinical assistant professor in the Department of Surgery, Division of Plastic & Reconstructive Surgery. She is medical director of the Stanford Health Care Breast Reconstruction Program in the East Bay. Dr. Sorice-Virk completed her medical degree at New York University School of Medicine. She then went on to do her residency in Plastic Surgery and fellowship in Advanced Wound Care at Stanford University School of Medicine. Finally, this was followed by a fellowship in Advanced Reconstructive Microsurgery at the University of Pennsylvania.
Dr. Sorice-Virk’s clinical interests include complex reconstruction after cancer and trauma while keeping optimal aesthetic outcomes as a top priority. She performs a wide range of procedures, including breast reconstruction and other cancer reconstruction such as gynecologic, colorectal and orthopedic among others, breast-conserving surgery, cosmetic plastic surgery, reconstructive plastic surgery, and body contouring. Patients of Dr. Sorice-Virk benefit from a personalized and compassionate care approach. In addition to offering the entire gamut of standard reconstructive modalities, she uses cutting edge surgical techniques, such as perforator flaps (i.e. DIEP flap), hybrid breast reconstruction (i.e. the combination of free flap transfer and implant placement), and breast neurotization to restore breast sensation and in conjunction with the breast surgeons, expanding indications for nipple sparing mastectomies to improve aesthetic outcomes for more patients.
Research interests of Dr. Sorice-Virk include plastic surgery/breast reconstruction outcomes and integrative medicine in plastic surgery. She serves as the principal investigator for multiple research projects and has received grant funding from several organizations.
Her published work includes numerous papers, book chapters, and abstracts, and she has presented her findings at national and international conferences. Additionally, Dr. Sorice-Virk is an ad hoc peer reviewer for Annals of Plastic Surgery and Microsurgery.
Dr. Sorice-Virk is a member of the American Society of Plastic Surgeons and the American Society for Reconstructive Microsurgery. -
Tatiana Sorokina
Senior Associate Director, Industrial Contracts Office, Office of Technology Licensing (OTL)
Current Role at StanfordSenior Contracts Officer, Industrial Contracts Office
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Siamak Sorooshyari
Postdoctoral Scholar, Statistics
BioMy research lies at the intersection of AI/ML, statistics, biology, and engineering. I was initially trained as an electrical engineer, with a focus on signal processing and statistical algorithms. I then pursued my PhD in a neuroscience laboratory studying stress and the blood-brain barrier, where I gained experience with biological systems, experimental design, instrumentation, and data collection. My current work brings these perspectives together as I develop computational and statistical methods to better understand and predict biological processes.
A major focus of my research is understanding how aging affects the brain and how these changes are reflected across biological scales and measurement modalities. I have studied signals recorded from individual brain regions, communication between brain networks, and changes in functional connectivity across the lifespan. An important question in this work is whether quantitative properties of biological signals, such as monotonicity, exhibit consistent relationships with age. I am particularly interested in determining how different modalities capture changes associated with aging in both healthy and diseased systems, and what these measurements reveal about the underlying biological processes. This perspective can also provide insight into the reliability and interpretability of different recording modalities as measures of biological aging. I have recently begun extending these questions beyond the brain to the brain-gut-heart axis in healthy humans. By examining relationships and coordinated changes among measurements from multiple organs, I aim to develop a more integrated understanding of healthy aging and, ultimately, of how these relationships are altered in disease, specifically neurodegeneration. This work represents a broader effort to study aging as a multidimensional biological process rather than as a phenomenon confined to a single organ or measurement modality.
In parallel, I develop statistical methods for assessing the reliability and reproducibility of unsupervised learning results. In particular, I am interested in understanding how methodological choices - including the clustering algorithm, model parameters, and the number of clusters - can affect the conclusions drawn from noisy, high-dimensional datasets. This work has led to ERICA (evaluating replicability via iterative clustering assignments), a framework for evaluating whether clustering structure can be reproduced under repeated analyses without requiring a predefined ground truth. I am applying this framework to biological datasets, including cancer and neurodegenerative diseases, where clustering is frequently used to identify molecular or phenotypic subgroups. More broadly, this work seeks to develop rigorous statistical tools that can help distinguish reproducible structure from patterns that may depend strongly on methodological choices.
