Our group is interested in the field of quantitative biology – the use of computational tools to understand and advance biological sciences. Our primary goal is to develop methods to quantify, analyze, and detect patterns in biomedical data, particularly (but not exclusively!) data that comes from imaging modalities.
Our research revolves around three primary focuses:
We take an engineering approach to biomedical problems. We develop tools for analyzing large datasets and images, building computational models to describe disease states, and building complex prediction algorithms to detect and diagnose disease. These tools generate new hypotheses to advance biological science.
The techniques we use can be applied to many fields; however, as biomedical scientists, our interest is in the complex world of biology and medicine. In the classroom, we are developing truly cross-disciplinary engineers and biologists capable not only of excelling in their fields but in communicating and collaborating with experts from across the academic world.
We believe that biomedical science research should inspire changes in clinical practice that improve patient care. To that end, we collaborate with clinical practitioners in the Kaleida Health network across a wide variety of disciplines to share ideas and innovations, which in turn guide our research and development efforts.
We are always looking for talented students and collaborators interested in machine learning, structure and functional modeling, image and volumetric analysis, and advancing clinical care through application of computational methods. If you would like to have a chat to discuss potential collaboration or mentorship opportunities, please drop a line!
Quantitative Reconstruction and Analysis of Cadaver CT Scans
Investigating Microvessel Connections between the Vagina and the Bladder
Analysis and Modeling of Oral Cavity Cancer from Serial Histopathology