School of Medicine


Showing 1-43 of 43 Results

  • Amirsaman Ashtari

    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.

  • Sijie Chen

    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.

  • Wenting Chen

    Wenting Chen

    Postdoctoral Scholar, Radiation Physics

    BioI am currently a Postdoc Fellow in the Department of Radiation Oncology of Stanford University, advised by Prof. Lei Xing. Before joining Stanford, I obtained my Ph.D degree in the Department of Electrical Engineering, City University of Hong Kong, supervised by Prof. Yixuan YUAN, Prof. W.S Tommy Chow, and Prof. L.H. Leanne Chan. I visited Massachusetts General Hospital and Harvard Medical School, supervised by Prof. Xiang Li and Prof. Quanzheng Li. Before that, I received the B. Eng and M. Eng degree from College of Computer Science and Software Engineering in Shenzhen University of China in 2017 and 2020, supervised by Prof. Linlin Shen. From Dec. 2019 to Nov. 2020, I had interned in Tencent Jarvis Lab, supervised by Dr. Shuang Yu and Prof. Yefeng Zheng.

    My research interests lie in vision-language model, multi-modal large language model, generative AI, computer vision and their applications on medical AI, with a focus on report generation, medical image synthesis, endoscopy super-resolution, retinal image segmentation, multi-modality diagnosis, etc.

  • Sofia Ferreira

    Sofia Ferreira

    Postdoctoral Scholar, Radiation Biology

    BioCancer Biology Scientist focused on improving treatment options on refractory tumors, primarily pancreatic cancer. My research focuses on uncovering innovative strategies to enhance the responsiveness of pancreatic cancer to existing treatments through fundamental research and preclinical approaches:

    1.Investigate key molecular pathways in pancreatic cancer using in vivo, organelle-specific omics to identify new therapeutic targets

    2.Identify unique drivers and tumor-stroma crosstalk across distinct pancreatic cancer subtypes

    3.Exploit tumor cell innate immunity pathways to enhance pancreatic cancer responses to immunotherapy

  • Marina Francis

    Marina Francis

    Postdoctoral Scholar, Radiation Therapy

    BioDr. Francis is a Postdoctoral Scholar in Dr. Everett Moding’s lab at the Department of Radiation Oncology. She uses genomic analysis of patient samples and preclinical models to identify new targets that sensitize sarcoma to treatments like radiation and immunotherapy. Before joining Stanford University, she completed her PhD in Biomedical Sciences at the American University of Beirut, where she worked in Dr. Youssef Zeidan’s lab investigating the role of the sphingolipid-modifying enzyme SMPDL3b in radiation nephropathy. Her research interests revolve around improving cancer treatment outcomes and patients’ quality of life by optimizing radiation therapy, combined treatment strategies, personalized precision oncology, and mitigating collateral treatment-associated toxicities.

  • Lu Ji

    Lu Ji

    Postdoctoral Scholar, Radiation Biology

    BioDriven by the enthusiasm and curiosity about life science and human disease, I have been working on cancer research for more than 5 years. I focus on developing novel therapeutic targets from tumor microenvironment and uncovering mechanisms of tumor progression, especially with expertise in gastrointestinal tumor biology and tumor microenvironment analysis. Now I'm digging into a field about finding a way to empower immunotherapy by appropriately utilizing radiation therapy.

  • Zhongxiao Li

    Zhongxiao Li

    Postdoctoral Scholar, Radiation Physics

    BioZhongxiao Li is a postdoctoral researcher in Professor Ruijiang Li's lab at Stanford Medicine. His research focuses on computational biology and bioinformatics, particularly the development of deep learning methods for computational pathology and spatial transcriptomics/proteomics. Previously, his work has included developing machine learning models for histopathological image analysis, understanding gene regulation, and analyzing biological sequences.

  • Xiangde Luo

    Xiangde Luo

    Postdoctoral Scholar, Radiation Physics

    BioXiangde Luo is a postdoctoral researcher in Professor Ruijiang Li’s lab at Stanford Medicine, where he specializes in computational pathology. His work centers on developing AI‑driven methods for imaging biomarker discovery and precision oncology. Previously, he has developed some deep learning models to enable annotation‑efficient learning and advance biomedical image analysis. For a comprehensive overview of my research, please visit my Google Scholar profile: https://scholar.google.com/citations?hl=en&user=dD4HLS4AAAAJ. If you’d like to learn more or discuss potential collaborations, please don’t hesitate to get in touch.

  • Vivek Maradia

    Vivek Maradia

    Postdoctoral Scholar, Radiation Therapy

    Current Research and Scholarly InterestsI research ultra-high dose rate delivery using proton, x-ray, and electron beams for FLASH preclinical studies, aiming to understand efficacy and safety mechanisms. My work aims to transform cancer therapy and enhance patient outcomes. Leveraging insights from PSI's PROScan facility, I design a compact cyclotron-based proton therapy infrastructure for various radiation therapy setups.

  • Sakib Mostafa

    Sakib Mostafa

    Postdoctoral Scholar, Radiation Physics

    BioI am a Postdoctoral Research Fellow at Stanford University with a background in computational genomics and deep learning. My research focuses on developing AI-powered tools for genomic analysis, with a particular interest in cancer classification, pangenomes, and genotype imputation. Previously, I worked as a Research Officer at the National Research Council of Canada, contributing to large-scale sequencing projects and machine learning interfaces for biologists. I am passionate about bridging domain biology with cutting-edge computational methods to solve complex biological questions and drive innovation in precision agriculture and healthcare.

  • Rohollah Nasiri

    Rohollah Nasiri

    Postdoctoral Scholar, Radiation Physics

    Current Research and Scholarly InterestsMy current research focuses on developing tumor-on-a-chip models for preclinical radiation therapy research.

  • Junming Seraphina Shi

    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.

  • Ziwei Wang

    Ziwei Wang

    Postdoctoral Scholar, Radiation Therapy

    Current Research and Scholarly InterestsMy current work focuses on establishing preclinical platforms to rapidly validate the functional impact of genetic alterations in tumors using both cell and genetically engineered mouse models. We hope this system can accelerate the discovery and translation of novel cancer therapies to patients.

  • Jinxi Xiang

    Jinxi Xiang

    Postdoctoral Scholar, Radiation Physics

    Current Research and Scholarly InterestsI develop machine leanring methods to autonomate the digital pathology.

  • Kai Zhang

    Kai Zhang

    Postdoctoral Scholar, Radiation Physics

    Current Research and Scholarly InterestsMy research develops AI systems for biomedicine, with a focus on multimodal learning, foundation models, and self-improving AI. I study how models can integrate medical images, clinical text, EHRs, and biomedical knowledge to support diagnosis, clinical workflows, and scientific discovery, while improving through feedback, evaluation, and human-AI interaction.

  • Man Zhao

    Man Zhao

    Postdoctoral Scholar, Radiation Biology

    BioMy research primarily focuses on the molecular mechanisms, signaling pathways, and therapeutic targets underlying cancer metabolism, particularly the m6A demethylase FTO. I am also actively exploring the interplay between tumor metabolism and tumor immunity, with the goal of identifying novel metabolic vulnerabilities for cancer treatment.

  • Tianyu Zhao

    Tianyu Zhao

    Postdoctoral Scholar, Radiation Biology

    Current Research and Scholarly InterestsHow p53 affects the tissue homeostasis in lung cancer and injury.

  • Xiaoxu Zhong

    Xiaoxu Zhong

    Postdoctoral Scholar, Radiation Physics

    BioI am a Postdoctoral Fellow in the Guillem Pratx Lab, with an expertise in predictive modeling, algorithm development, and data science. I earned my Bachelor of Science and Master of Science degrees in Ocean Engineering from Shanghai Jiao Tong University. I then received a Ph.D. in Mechanical Engineering from Purdue University, where I focused on developing mathematical models and applying machine learning. My work uncovered the mechanisms behind autoinjectors, drug delivery, and cavitation bubbles, with applications in tumor treatment and the design of medical devices. Currently, I am combining computational modeling and experimental approaches to positron emission tomography imaging, aiming to improve tumor diagnosis and treatment. I am also investigating how ionizing radiation nucleates nano-sized bubbles.