University of Illinois
Ken Lau lab
I will leverage single-cell multiomics and data science paradigms to develop analytical frameworks for the investigation of cell specification and developmental state transitions. Emergent methods are capable of illustrating omic-scale phenomena on a single-cell level through the utilization of machine learning. However, the robust integration of different classes of high-dimensional data remains poorly understood. In addition to the iterative development of our own software, p-Creode, we will utilize mature, cloud-based artificial intelligence platforms such as Amazon Web Services to develop highly-scalable and interoperable frameworks elucidating multiomic relationships.