Research scientist Resume

TECHNICAL SKILLS

Strong analytical and computational skills; strong modeling ability.
Excellent programming experience with C++, C, and Fortran.
Years’ of experience in parallel programming in supercomputers using MPI and OpenMP for CPU and Intel coprocessors, and CUDA for GPU to accelerate code execution.
Experienced in Monte Carlo simulations and linear algebra matrix computations.
Expert in large - scale numerical simulations in terms of using state-of-the-art large computer memory and CPU numbers.
Knowledge of optimization with annealing, quantum annealing techniques, and the recent D-Wave machines.

PROFESSIONAL EXPERIENCE

Research scientist

Confidential

Responsibilities:

I use supercomputers in Confidential and Texas Advanced Computing Center to do numerical simulations on interacting models in optical lattices and condensed matter systems.
Research projects include proposing a model to realize a stable quantum computer, studying long-range interacting dipolar systems, revealing the fractional charges in one-dimensional systems, and discovering the disordered enhanced superfluid and supersolid behaviors.
I wrote all the codes in these projects.

Postdoctoral research associate

Confidential

Responsibilities:

I used supercomputer Jaguar in Oak Ridge National Lab, which was at that time the fastest supercomputer in the world, to study electron response to external field perturbation in two-dimensional Hubbard model using quantum Monte Carlo method.
The resulting data was analyzed with Bayesian inference and Maximum entropy method. Thousands of
CPUs were used in one Monte Carlo simulation with a hybrid code of MPI and OpenMP. Since a rank 3 tensor was generated in the simulation, memory usage was reduced by employing symmetries based on Group theory, and the manipulation of the large tensor in one computation node was coded with OpenMP.
I made significant additions to the existing code in the research group.

Postdoctoral research associate

Confidential

Responsibilities:

I used NCSA supercomputers in UIUC to study liquid hydrogen under Mega bar high pressure (to mimic the most basic component of some planets, such as Jovian), which is of interest to astronomy in studying the structure of these planets.
Electrical conductivity was calculated for the first time with quantum Monte Carlo method.
The partial differential Schrodinger equation was solved with importance and correlated sampling techniques in Monte Carlo simulations.
My second project involved disorder average effect in dirty superconductors.
I numerically proved that a huge number of samples are needed in obtaining a correct average, challenging the usual belief that self averaging exists in a reasonably large system.
My third project was numerical investigation of interacting Bosons trapped in a super cold sphere (-459 degrees) by laser lights.
It is a memory-intensive Monte Carlo simulation, which requires efficient mapping of quantum operators into connected graphs representation. The result was generated in terms of Gigabyte data, which was ordered efficiently for later data processing.
I also proposed a fast new method to extract Bose-Einstein condensate fraction accurately from these huge data sets, and suggested that the method used in all previous calculations has overestimated the condensate fraction value. I made significant additions to the codes in the first project, and wrote all the codes for both second and third project.

Teaching and research assistant

Confidential

Responsibilities:

I used quantum Monte Carlo and MPI techniques to study superconducting mechanism for an organic superconductor C60 (“buckyball”).
A long series of matrix multiplication is needed in Monte Carlo simulation.
These multiplications are stabilized with singular value decomposition method.
The electronic energy that I calculated is the most accurate estimate currently, and the calculation strongly challenges the superconductivity mechanism proposed and held by a group of famous physicists for over 15 years.
I wrote all the codes in this research.