About Me

Xiaozhou Li (李小舟) was born in Chongqing, China. I received my B.Sc. in Mathematics and Applied Mathematics from the University of Science and Technology of China (USTC), where I also minored in Mathematical Economics, and later earned my Ph.D. in Applied Mathematics from Delft University of Technology in the Netherlands.

My academic work centers on computational mathematics—especially high-order numerical methods and large-scale scientific computing—where abstract ideas take shape as algorithms, and logic becomes a quiet craft for understanding the intricate world around us.

Beyond the university, I am drawn to the steady disciplines of strength training and the science of longevity. For years, I have practiced barbell-based training and more recently begun studying Mixed Martial Arts (MMA). These pursuits cultivate focus, clarity, and patience—virtues as essential in the gym as they are in mathematics.

They mirror the core principles of mathematical work: discipline, incremental progress, and the quiet resolve to pursue distant goals over time.

Just as strength training gradually shapes the body, I see mathematics as a long discipline of the mind—one that sharpens how we observe, reason, and build. It reminds me to stay rooted in the process rather than fixated on outcomes, and to trust in the slow, steady accumulation of insight.

Do not overestimate what can be done in a day, but never underestimate what can be built in a year.

Feel free to contact me via email or connect through GitHub, or other platforms linked below.

Education:

• 2011–2015, Ph.D., Applied Mathematics, Delft University of Technology, Netherlands.
• 2007–2010, B.S., Mathematics and Applied Mathematics, University of Science and Technology of China, China.
• 2006–2007, School of Information Science and Technology, University of Science and Technology of China, China.

Work:

• 2017-present, Associate Researcher, School of Mathematical Sciences, University of Electronic Science and Technology of China, China. Faculty Page
• 2015–2017, Postdoc, Institute of Computational Science, Università della Svizzera Italiana, Switzerland.
• 2015–2017, Postdoc, Center for Computational Medicine in Cardiology (CCMC), Università della Svizzera Italiana, Switzerland.

Computer Skills

Programming Languages

• Advanced: Python, Fortran
• Intermediate: C, C++, MPI, OpenMP, Pascal, LaTeX
• Basic: MATLAB, Maple, CUDA, Julia

High-Performance Computing (HPC)

• Proficient in parallel programming with MPI and OpenMP.
• Hands-on experience with large-scale simulations on supercomputing clusters (e.g., via SLURM/PBS).
• Familiar with hybrid CPU-GPU computing and basic CUDA programming.

Scientific Computing Tools & Frameworks

• Practical experience with MOOSE and FEniCS for PDE-based multiphysics simulations.
• Familiar with PETSc, Trilinos, NumPy/SciPy for solver development and numerical algorithms.
• Competent in Linux/Unix environments, Git version control, and visualization using ParaView and matplotlib.

Interests

• Strength training (advanced to elite level; PRs: DL 200 kg, SQ 165 kg, BP 95 kg at 70 kg body weight)
• Mixed Martial Arts (beginner level)

Last updated: 2025-05-01