School of Medicine
Showing 1-10 of 17 Results
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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
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. -
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.
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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.
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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.
