Dr. Mingyao Li joined the Biostatistics faculty in 2006. She is also a faculty member of the Genomics and Computational Biology graduate program. Her main research area is statistical genetics and genomics. The central theme of her current research is to use statistical and machine learning approaches to understand cellular heterogeneity in human disease relevant tissues, to characterize gene expression diversity across cell types, and to study the patterns of cell state transition and crosstalk of various cells using data generated from single-cell transcriptomics studies. In addition to methods development, Dr. Li is also interested in collaborating with researchers seeking to identify complex disease susceptibility genes. Her collaborative research includes cardiometabolic diseases, age-related macular degeneration, Alzheimer's disease, chronic kidney disease, type 1 diabetes, and cancer. Findings from her research will seed cell-specific functional studies, in vivo modeling, and precision therapeutic targeting of human diseases. Dr. Li actively serves in the scientific community. She is an Associate Editor of Statistics in Biosciences, and was a regular member of the Genomics, Computational Biology and Technology study section and a member of the review committee of the Center for Inherited Disease Research of the NIH.

We are a computational systems immunology lab. Our research focuses on the development and use of novel systems approaches to analyze high-dimensional immunological datasets, and elucidate molecular mechanisms of immunological disorders. Our past work has utilized systems approaches to analyze Mendelian mutations in the context of three-dimensional protein-protein interaction networks, to understand molecular mechanisms of corresponding disorders. We have also developed network analyses frameworks to characterize the evolutionary dynamics of these protein networks. Another key dimension of our past work has been the use of statistical and machine-learning approaches for the analyses of high-dimensional antibody-omic to elucidate correlates of vaccine-mediated and natural immunity in HIV, tuberculosis and malaria.

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We are currently working on using network systems and functional genomic approaches to perform multi-scale integration of genomic and epigenomic datasets with biological networks to identify molecular phenotypes underlying these immunological disorders, with an emphasis on autoimmune and alloimmune diseases. We also use high-dimensional statistical and machine-learning techniques to integrate multi-omic datasets (genomic, transcriptomic, proteomic, metabolomic and antibody-omic) and elucidate molecular mechanisms of immune regulation and dysregulation.

​My research focuses on AI/ML innovation and its application to medicine, with topics including vision-language foundation model for pathology (Nature Medicine'23 cover article), human-AI collaboration (Nature BME'24 cover article), neurodegenerative diseases (Nature Communications'23), optimizing LLMs (Nature'25), etc. My research has drawn wide public attention (including the New York Times, Stanford Magazine, and Stanford Scope) and has resulted in translational innovations. In 2022, my postdoc mentors and I co-founded nuclei.io — a human-in-the-loop AI platform for digital pathology.

I am an assistant professor in the Department of Surgery - Division of Surgical Oncology at The Ohio State University and a member of the Translational Therapeutics Program at the OSUCCC - James. I am focused on better understanding the immune response during carcinogenesis and why the immune system has failed to control solid tumors. My research is primarily centered on pancreatic ductal adenocarcinoma (PDAC), a notoriously immunotherapy resistant malignancy.

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My lab team is specifically investigating how B lymphocytes regulate and support innate and adaptive tumor immunity during malignant progression and response to therapy. We deploy preclinical models of cancer that most closely align with the human disease and validate these findings with patient tissue samples. We seek to understand the mechanistic underpinnings of novel cellular pathways and develop strategies for clinical translation. This approach intersects with experimental methods in cell biology, molecular biology, bioinformatics and clinical medicine.

My work has been published in multiple peer-reviewed journals, including Nature Communications, Cancer Discovery, Cancer Cell, Oncoimmunology, and Lancet Oncology. Much of this research has been presented at national and international biomedical and clinical conferences and has translated into multiple clinical trial protocols. I have also been honored with awards from organizations such as the American Society of Radiation Oncology and engaged in various industry sponsored research agreements. I am a member of and active in the Society for the Immunotherapy of Cancer which has long supported immunotherapy as a curative option for cancer patients.