RESEARCH
The research in the Tang group thrives to understand the dynamics and control of stochastic systems for new materials, novel diagnostics and therapeutics, advanced (bio-)computing, and advanced manufacturing. Our specific focuses include: 1) soft matter and optimal control, including data-driven design of optimal control policies for reliable, predictive, and rapid assembly of micron and nanoparticles for metamaterials and in-situ crystallization for pharmaceutical applications; 2) systems and synthetic biology, focusing on the design of robust, modular, and versatile synthetic gene circuits and biological feedback controllers to regulate biological system dynamics; and 3) academic-industry enhancement, where we partner with industry to transition academic findings to industrial production.
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 represent the configurations, learn the system dynamics, adopt advanced control theory to design optimal operation strategies, and partner with experimental experts for implementation.
Synthetic and Computational Biology
Harnessing predictable gene expression and reliable metabolic pathway regulations could enable novel bio-devices and advanced diagnostics and customized therapeutics. We use mathematical modeling, control theory, and experimental validation, to the design RNA-based genetic circuits for rigorous gene expression regulation for biocomputing capabilities, and biological feedback controllers for novel metabolic and genetic interventions.