Stanford University
Showing 1-20 of 175 Results
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Amirsaman Ashtari
Postdoctoral Scholar, Radiation Biology
BioI am a postdoctoral researcher at Stanford University, jointly supervised by Ash Alizadeh MD/PhD and Mohammad Shahrokh Esfahani PhD. I developed several AI solutions for the Computer Vision and Computer Graphic domains during my PhD studies at KAIST and ETH Zurich. My PhD research outcome was recognized by winning the Young Researcher Award, and I was eager to apply all those AI techniques to biological data for cancer therapy. In the Alizadeh and Esfahani labs, I will develop AI solutions and computational tools to better understand the tumor microenvironment. Outside of my research, I enjoy loving my family, playing the piano, and listening to music.
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Laura Attardi
Catharine and Howard Avery Professor of the School of Medicine and Professor of Genetics
Current Research and Scholarly InterestsOur research is aimed at defining the pathways of p53-mediated apoptosis and tumor suppression, using a combination of biochemical, cell biological, and mouse genetic approaches. Our strategy is to start by generating hypotheses about p53 mechanisms of action using primary mouse embryo fibroblasts (MEFs), and then to test them using gene targeting technology in the mouse.
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Mohsen Bayati
Carl and Marilynn Thoma Professor in the Graduate School of Business and Professor, by courtesy, of Electrical Engineering and of Radiation Oncology (Radiation Therapy)
Current Research and Scholarly Interests1) Healthcare management: I am interested in improving healthcare delivery using data-driven modeling and decision-making.
2) Network models and message-passing algorithms: I work on graphical modeling ideas motivated from statistical physics and their applications in statistical inference.
3) Personalized decision-making: I work on machine learning and statistical challenges of personalized decision-making. The problems that I have worked on are primarily motivated by healthcare applications. -
Michael S Binkley, MD, MS
Assistant Professor of Radiation Oncology (Radiation Therapy)
BioDr. Binkley is a radiation oncologist specializing in lymphoma treatment and an assistant professor in the Stanford University School of Medicine Department of Radiation Oncology.
His clinical expertise includes stereotactic ablative radiotherapy (SABR), total lymphoid and total body irradiation, and intensity modulated radiation therapy (IMRT).
For each patient, Dr. Binkley develops a personalized, comprehensive, and compassionate care plan. His goals are to improve both health and quality of life.
Dr. Binkley has conducted extensive research to advance cancer treatment. In his post-doctoral fellowship at Stanford, he studied the use of genomic signatures to predict response to radiotherapy. His current clinical and laboratory research seek to identify prognostic and predictive clinical, radiographic, and genomic factors to inform individualized treatment strategies.
He has co-authored articles on his research discoveries published in Journal of Clinical Oncology, Cancer Discovery, Blood, the International Journal of Radiation Oncology*Biology*Physics, and elsewhere. Topics have included innovations in the treatment of lymphoma and lung cancer.
He also has made invited presentations to colleagues at national and international conferences. He has presented the latest findings on radiation therapy for lung cancer and lymphoma at meetings of the American Society of Clinical Oncology (ASCO), American Society for Radiation Oncology (ASTRO), and International Conference on Malignant Lymphoma (ICML).
Honors for Dr. Binkley include the Malcolm A. Bagshaw Award for leadership and outstanding scientific achievement. This award is named for a pioneer in radiation therapy and former chair of the Departments of Radiology and Radiation Oncology at Stanford University School of Medicine.
Dr. Binkley is a member of the American Society of Clinical Oncology, American Society for Radiation Oncology, and American Association for Cancer Research. He is a founding member of the Global nLPHL One Working (GLOW) Working Group, an international collaboration studying nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) in children and adults. -
Martin Brown
Professor of Radiation Oncology, Emeritus
Current Research and Scholarly InterestsWe seek to understand the mechanisms responsible for the resistance of cancers to treatment and to develop strategies to overcome these resistances. We are using molecular and cellular techniques and mouse models to potentiate the activity of radiation on tumors by inhibiting the bone marrow rescue of the tumor vasculature following therapy.
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Santino S. Butler, MD
Clinical Assistant Professor, Radiation Oncology - Radiation Therapy
BioSantino Butler, MD, is a radiation oncologist who treats a broad range of malignancies, with a particular clinical focus in high-dose-rate brachytherapy for gynecologic cancers. He has published more than 30 peer-reviewed research articles, including first-author publications in several highly-cited medical journals such as the New England Journal of Medicine (NEJM), the Journal of the American Medical Association (JAMA), the Journal of the American Medical Association–Oncology (JAMA Oncology), and the Journal of the American College of Cardiology–CardioOncology (JACC CardioOncol); He has presented his work at several major medical conferences throughout the country.
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Mark Buyyounouski, MD, MS, FASTRO
Professor of Radiation Oncology (Radiation Therapy)
Current Research and Scholarly InterestsPatient-centered and artificial intelligence-augmented medical decision making
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Rishabh Chaudhari, MD
Clinical Assistant Professor, Radiation Oncology - Radiation Therapy
BioDr. Chaudhari is a radiation oncologist with the Stanford Medicine Cancer Center and a clinical assistant professor in the Department of Radiation Oncology at Stanford University School of Medicine.
In every case, he develops a comprehensive, compassionate care plan personalized to the unique needs of each patient. His goal is always to deliver innovative, compassionate care of the highest quality to help each patient achieve the best possible outcome.
Dr. Chaudhari conducts research into leading-edge treatments, allowing him to offer the most advanced care options. He has investigated stereotactic body radiation therapy for non-small cell lung cancer and for pancreatic adenocarcinoma. He has also studied the effects of radiotherapy on breast cancer stem cells and extramedullary plasmacytomas. He also is currently studying the use of proton beam therapy on recurrent head and neck cancers.
Dr. Chaudhari has presented his research findings at meetings of the Radiation Research Society, Society for Thermal Medicine, American Society for Radiation Oncology, and World Congress of Brachytherapy. He has published articles on radiotherapy for non-small cell lung cancer in the journal Lung Cancer: Targets and Therapy. He also co-authored the chapter “Renal and Adrenal Vasculature: Anatomy and Imaging” in the textbook Image-Guided Interventions. He has served as a reviewer for Cancer Medicine.
In previous positions, Dr. Chaudhari served on committees dedicated to care quality assurance and to the monitoring of cancer care protocols. Other areas of interest include radiation oncology department operations and advising radiation oncology residents.
Dr. Chaudhari is a member of the American Society for Radiation Oncology. -
Sijie Chen
Postdoctoral Scholar, Radiation Physics
BioI am a postdoctoral fellow working with Dr. Lei Xing at Stanford University, where I develop trustworthy autonomous AI agents and foundational informatics systems for single-cell biology. My long-term vision is to build auditable computational infrastructure and virtual cell models that transform massive single-cell atlases into reliable, steerable systems for mechanistic discovery across tissues, diseases, and species. My doctoral work with Prof. Xuegong Zhang established my foundation in single-cell bioinformatics and atlas-scale integration, which I have since extended into large-scale representation modeling, AI agent workflows, and LLM-driven scientific discovery. My current work focuses on developing governed, agentic lifecycles for continuous single-cell data curation and foundation model evaluation, while applying these autonomous systems to power cross-organ virtual cell retrieval and simulate immune-tolerance breakdown.
My ongoing efforts build directly upon my prior work in atlas integration and algorithmic development. As the first author of hECA (Chen et al., 2022), I built a unified human cell atlas integrating one million high-quality cells across 38 organs with a logic-expression query interface. This experience exposed the central bottlenecks—such as heterogeneous formats and ontology grounding—that I now address using LLM-powered agents to enable autonomous metadata harmonization and iterative quality control. I am converting manual curation into an autonomous, agent-driven paradigm where new datasets are continuously ingested and versioned in a traceable manner. Furthermore, my co-development of TorchGW for cell state alignment, TFcomb for perturbation prediction, and TransMap for cross-species alignment provides the algorithmic foundation for next-generation cell foundation models and virtual cell simulation.
By integrating these components into trustworthy, benchmarked, and human-in-the-loop AI infrastructure, my research bridges scalable scientific computing with complex biomedical questions. Through close collaboration with Prof. Edgar Engleman, I am utilizing immune-tolerance breakdown—specifically focusing on a tolerogenic dendritic cell program—as a mechanistic testbed to validate our virtual cell simulations. A core focus of my work is ensuring that every agent-generated hypothesis and retrieved state remains bound to the exact data and model checkpoints that produced it, making findings fully re-derivable as the biological knowledge base evolves. Ultimately, I aim to advance the frontier of trustworthy autonomous single-cell informatics, bridging AI agents, virtual cell engineering, and biological discovery.
