School of Medicine
Showing 1,151-1,200 of 1,596 Results
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Moritz Schaefer
Postdoctoral Scholar, Immunology and Rheumatology
Current Research and Scholarly InterestsI build AI systems that can be asked a question about biomedical data in plain language and show their work well enough to be checked. CellWhisperer (Nature Biotechnology, 2025) links a million RNA-sequencing profiles to the text describing them, so single-cell data can be explored by asking rather than coding. SpatialWhisperer (ICML 2026) carries this into histopathology. I pair these models with AI agents reasoning across imaging, genomics and the clinic to explain why CAR T therapy fails.
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Rachel Schuck
Postdoctoral Scholar, Psychiatry
Current Research and Scholarly InterestsMy research interests center on improving support services for autistic individuals—particularly by incorporating feedback from the autistic/autism community—and increasing access to high quality supports. I am also interested in assessing attitudes toward neurodiversity and promoting understanding of neurodiversity amongst the general population in the hopes of improving quality of life for neurodivergent people and their families.
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Narayan Schutz
Postdoctoral Scholar, Psychiatry
Current Research and Scholarly InterestsI work on using digital health technologies to detect and monitor aging relevant health indicators and outcomes using cutting-edge machine and deep learning approaches, with the goal to make our healthcare system more personalised and proactive.
Current research topics include remote gait and mobility assessments, learning health representations from large-scale smartphone data, and using novel ambient intelligence approaches to foster independent living in older adults. -
Mojtaba Sedigh Fazli
Visiting Instructor/Lecturer, Cardiovascular Institute
Postdoctoral Scholar, Cardiovascular InstituteBioDr. Mojtaba Fazli is a leading artificial intelligence scientist and Lecturer at the Stanford Cardiovascular Institute and Stanford School of Medicine. His research connects machine learning, biomedical imaging, and cardiovascular physiology to address a central challenge in clinical AI: translating complex biomedical data into interpretable insights that can support better clinical decisions.
Working under the mentorship of François Haddad and Suzanne Tamang, Dr. Fazli develops AI approaches that integrate electrocardiography, echocardiography, invasive hemodynamic measurements, and clinical data. His current research spans pulmonary hypertension, right-heart function, and the estimation of cardiovascular pressures and function from noninvasive measurements. A defining focus of his work is explainability—understanding not only what a model predicts, but also how its predictions relate to clinically meaningful physiological patterns. Through this work, he investigates how AI can complement established cardiovascular assessment and support more informative, accessible approaches to disease evaluation.
Before his current appointment, Dr. Fazli held successive postdoctoral positions in Stanford’s Division of Immunology and Rheumatology and at the Cardiovascular Institute. Under the supervision of Suzanne Tamang and Rob Fairchild, his rheumatology research focused on AI-enabled ultrasound analysis, rheumatoid arthritis assessment, and the integration of multimodal clinical data. This experience helped shape his broader research approach: connecting imaging, quantitative measurements, and clinical context to address questions that matter in patient care.
His background spans academic medicine and pharmaceutical research, including postdoctoral training and senior research experience at the Harvard Ophthalmology Artificial Intelligence Lab and Harvard AI and Robotics Lab. He also served as a Senior Open Innovation Scholar and Gates Fundation Fellow at the Novartis Institutes for BioMedical Research, applying computational methods to biomedical research and drug discovery. Across these settings, his work has encompassed computer vision, 2D and 3D biomedical image analysis, computational disease modeling, and AI-driven analysis of complex biological data.
Dr. Fazli’s broader research interests include multimodal learning, computer vision, agentic AI, generative AI, and large language models for medical data analysis, integration of clinical knowledge, and clinical decision support. Across these areas, he emphasizes rigorous evaluation, transparent modeling, and close collaboration between computational scientists and clinicians.
He holds a PhD in Computer Science, with a minor in Mathematics, from the University of Georgia, a Doctorate in Business Administration, and master’s degrees in Economics and Management and in Artificial Intelligence and Robotics. This interdisciplinary foundation informs his approach to developing AI that is technically rigorous, clinically grounded, and responsive to the practical challenges of healthcare. -
Sourya Sengupta
Postdoctoral Scholar, Urology
Current Research and Scholarly InterestsMultimodal medical AI, vision language models, model interpretability, computational imaging science
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Shailja
Postdoctoral Scholar, Radiological Sciences Laboratory
BioShailja is an engineer and computational scientist interested in the modeling of the human brain to study neurological diseases and guide neurosurgeries. As a Wu Tsai Neuroscience Institute’s postdoctoral fellow with Prof. Jennifer A. McNab and Prof. Josef Parvizi, she investigates tractography-based neurosurgical targeting. She is interested in mapping the whole brain structural connectivity network from diffusion MRI to functional connectivity in the human brain. Shailja received her PhD in Electrical and Computer Engineering from the University of California, Santa Barbara and BS from Electrical Engineering Department, Indian Institute of Technology, Kharagpur. Her doctoral research is on Reeb graphs for modeling white matter fibers in the human brain, which was awarded the Winifred and Louis Lancaster Best PhD Dissertation at UC Santa Barbara.
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Tong Shan
Postdoctoral Scholar, Psychiatry
BioTong completed her Ph.D. at the University of Rochester. She also holds an M.S. in Biostatistics from Northwestern University and a B.S. in Medical Imaging from Sichuan University.
In her research, Tong has explored topics such as subcortical and cortical neural responses to naturalistic speech and music, neural mechanisms underlying musical perception, and the impact of visual cues on speech-in-noise comprehension.
Currently, Tong is involved in the Speaker-Listener projects, where she investigates brain activities related to natural communication. She is excited to deepen her understanding of auditory processing of speech during communication and its implications for improving quality of life, particularly in clinical populations such as individuals with ASD, AD, etc.
Outside of her research, Tong is a music producer, creating original songs and soundtracks for video games. She has a passion for exploring the intersection of art and technology. -
Kat Adams Shannon
Basic Life Research Scientist, Pediatrics - General Pediatrics
BioKat studies how young children adapt their attention and learning behaviors to best match different early environments, with particular focus on understanding variability and strengths in contexts of early adversity. A key aim of her research is to create and collaborate on innovative uses of technology and statistical methods to support health, education, and developmental science.
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Saurabh Sharma
Postdoctoral Scholar, General and Vascular Surgery
Current Research and Scholarly InterestsWe develop strategies to transport immunotherapeutic molecules across the blood-brain barrier for imaging and treating brain metastatic cancer. Currently, under the mentorship of Dr. Amanda Kirane, I have continued my work in cancer-targeted nanotechnology for the treatment of melanoma brain metastases. Immunotherapy of small peptides, small molecules.
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Tanya Sharma
Postdoctoral Scholar, Pathology
BioTanya's interests span across studying G-Protein Coupled Receptors and the biochemistry of membrane proteins. During her doctoral studies, she worked as a visiting researcher at the National Research Council of Canada, Ottawa (Sussex laboratories) from 2019-2023 uncovering the role of an ancient mating receptor Ste3 in microbial pathogenesis and chemotropism. During her current position at Butcher lab, she is using High Performance Computing (HPC) platforms to guide her search for interesting ligand-receptor interactions. This involves using a combination of computation tools, cell based and analytical chemistry techniques for discovery and validation phase respectively.
Outside of science, she is an avid musician and a singer. -
Junming Seraphina Shi
Postdoctoral Scholar, Radiation Biology
BioI am a postdoctoral fellow at Stanford University, jointly mentored by Dr. Mohammad Shahrokh Esfahani and Dr. Md Tauhidul Islam. My research focuses on developing robust statistical machine learning methods for noninvasive, cost-effective cancer diagnostics, with applications in early detection, treatment monitoring, and precision oncology.
I received my Ph.D. from UC Berkeley, where my dissertation centered on advancing biostatistical machine learning approaches for complex biomedical challenges. My work addressed causal inference for continuous treatments, bias and measurement patterns in ICU electronic health records, and deep learning–based biclustering and prediction of cancer-drug responses. Across these projects, I developed interpretable and scalable tools for analyzing high-dimensional, multimodal clinical data.
At Stanford, I continue to build novel statistical learning frameworks tailored to real-world clinical needs—particularly through the analysis of liquid biopsy (cell-free DNA) and cancer imaging data. My current work aims to improve cancer detection and monitoring, with a focus on noninvasive, accessible, and clinically meaningful solutions to pressing challenges in oncology. I enjoy interdisciplinary collaborations and working across fields to drive innovation in biomedical research. Deeply committed to cancer research, I aim to bridge rigorous computational methodology with patient-centered impact by designing tools that are scalable, equitable, and translational. -
Palca Shibale
Postdoctoral Scholar, Plastic and Reconstructive Surgery
BioShibale, Palca is a post-doctoral fellow in the Hagey Laboratory under mentorship of Dr. Derrick Wan and Michael Longaker. She earned her BS in Molecular and Cellular Biology at the University of Washington (UW), her MS in Medical Physiology and Biophysics at Case Western University and her MD from UW. She has previously conducted translational research on drug efficacy and clinical research in trauma and vascular surgery. Her current works focus on understanding the mechanisms of tissue regeneration and fibrosis with nano materials and as well, the roles of fibroblast subpopulations in the foreign body response model
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Siddu Shivanagoudra
Postdoctoral Scholar, Gastroenterology
BioSiddu Shivanagoudra is a postdoctoral scholar in the Spencer Lab investigating how gut microbiota-derived metabolites modulate intestinal immune signaling and barrier function. He holds an MS in Horticultural Sciences and a PhD in Biomedical Engineering from Texas A&M University. His work spans tryptophan metabolite biology, AHR/GPR35 signaling, and defined bacterial consortia, integrating cellular, transcriptomic, and metabolomic approaches. Siddu aims to translate these mechanistic insights into microbiome-targeted therapeutic strategies for inflammatory gut diseases.
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Mahasish Shome
Postdoctoral Scholar, Genetics
BioMy research interest revolves around understanding the underlying mechanism of disease progression. I utilize multi-omics profiling to identify biomarkers relevant to the disease. I study autoantibodies, metabolomics and proteomics to decipher the connection of disease with biomarkers. For studying these, I use protein microarrays and mass spectrometry. Connecting various omics provide a holistic overview of the disease profile and can help in early diagnosis, understanding disease state and drug/vaccine effectiveness.
