RESEARCH
The research in the Tang group is focused on using control theory, mathematical modeling, and statistical inferences to control stochastic systems at the molecular level. Current research is on colloidal self-assembly and synthetic biology.
CONTROL OF COLLOIDAL SELF-ASSEMBLY
Controlling colloidal self-assembly has been a promising route to achieve perfect crystals for novel photonic properties. But controlling small-scale particles is challenging. In our group, we leverage machine learning to learn the system dynamics, adopt advanced control theory to design optimal operation strategies, and employ real systems to evaluate and improve the performance.
GENE EXPRESSION REGULATION
Harnessing predictable gene expression regulation could enable sophisticated dynamic functions that open doors to biosensors, clean energy, and advanced diagnostics and therapy. We use mathematical modeling, control theory, and statistical inferences, to guide the design and validation of RNA-based genetic circuits for rigorous regulation of gene expression.