Research Interests

As a computational physicist, my research interests span condensed matter physics, algorithm design and high-performance computing (HPC). In physics, my expertise is in the state-of-the-art classical and parallel Monte Carlo algorithms in statistical mechanics for the study of thermodynamics and phase transitions, first principles methods (density functional theory and quantum Monte Carlo) for the study of materials properties, as well as the applications of machine learning techniques to computer simulations and data analytics. My other research interests and experience include the study of structural transitions of proteins and polymers, physical properties of classical and quantum spin models, quantum entanglement and quantum information.

In computational sciences, I specialize in HPC algorithm design, scientific software development and engineering, performance analysis and optimization, with an emphasis on programming for heterogeneous system architectures consisting of CPUs and GPU accelerators. I am a developer of and contributed to several open-source, massively parallel, and scalable scientific software packages for supercomputers, such as OWL, LSMS, DCA++ and QMCPACK.