Machine learning for Biomedical Imaging analysis and multi-omics integration

In imAIgene-lab, we utilize diverse artificial intelligence tools spanning computer vision, single-cell technologies, and data analytics to extract biologically significant insights from microscopy data. Our research encompasses two main areas. Firstly, we delve into understanding the intricate behaviors and functions of cells within two critical areas of oncology: (1) deciphering the mode of action and heterogeneity in tumor response to immunotherapy, and (2) investigating the complex dynamics of tumor invasion. Secondly, our work involves a technical component centered on software development to allow this investigation. This effort is also geared towards facilitating the advancement and widespread adoption of imaging-based assays, which will serve a dual purpose: (1) a high-throughput drug screening platform in preclinical research and (2) a personalized medicine tool for bedside applications.