My research interest focuses on efficient numerical simulations within the tensor network state ansatz, to tackle novel phenomena in quantum manybody systems, including quantum spin liquid, unconventional superconductivity, topological states, etc.

Working on the PyTorch library as well as the QSpace library, I have developed several efficient thermal tensor network methods, e.g. series expansion thermal tensor network (SETTN), exponential tensor renormalization group (XTRG) and differentiable tensor renormalization group ($\partial$TRG) for accurate thermal simulations of quantum manybody systems.