Biomedicine is an interdisciplinary field of scientific research where medical practitioners, engineering and clinical researchers work together to find cutting-edge innovative solutions for advanced medical care that leads to improved quality of life. Due to rapid technological advances in this field, our knowledge about diseases, how we diagnose and treat them, is currently far beyond our expectations. This is achieved in part through the use of computational modeling and quantitative profiling, which are homologous to various aspects of human clinical biology.

The biomedical field involves science and engineering that uses clinical and biological data to develop cutting-edge algorithms and establish relationships between various clinical and biological systems. This sophisticated scientific field has significantly improved our current knowledge of medical and biological systems to individualize our treatment process. A large and growing field with advanced and sensitive scientific profiling requires precise in-depth knowledge, expertise, and understanding to ensure that innovative solutions to the world's most pressing clinical challenges are not misdirected.

The most advanced developments in this field are the quantitative analysis of stem cell populations and multimodal brain imaging to optimize the understanding of clinical therapeutic processes. However, a major challenge in stem cell biology is to characterize the proliferation and differentiation processes (i.e., dynamic growth), since little is known regarding the molecular stimuli involved in their regulatory mechanisms. This dynamic feature establishes the regulatory mechanisms involved in the expansion of cell populations and the acceleration of therapeutic processes towards the appropriate lineage. Our biomedical research team is working on the formulation of stochastic computational cell (myocyte, also known as satellite stem cells) models to understand and characterize these dynamics. We are also working on advanced multimodal medical imaging and probabilistic learning systems to improve existing neuropathological diagnostic and therapeutic systems.