🎓 I am currently a master’s student at Shanghai Jiao Tong University (SJTU), where I also received my BEng degree. Having published an article on CMAME as the first author and one on IJNME as the third author, I am currently preparing another manuscript for Nature Communications. With an aspiration to delve into intriguing and innovative research, I am looking for a PhD position in the fall term of 2025. (For European universities, I am applying for positions with enrollment times around April to September.)

I am truly a programming guy and sometimes even debug until 4 a.m. On my GitHub, you can find various projects I did for research and coursework that demonstrate my programming skills in computational mechanics (and machine learning, some new projects will be released before my new paper is submitted). These include 2D/3D linear-elastic/hyperelastic static/dynamic finite element methods using MATLAB [GitHub link] and C++ [GitHub link], 2D kinematics and dynamics using C++ [GitHub link], and 2D steady incompressible flow and Stokes flow using Python [GitHub link].

🔫 Besides a fulfilling academic life, I relax by playing badminton🏸 or video games🎮, going to the gym🏋️, walking around the campus🚶, drinking a little🍺, and eating half of a watermelon🍉 (2kg maximum).

If you find my Chinese given name Xueling difficult to pronounce [Google translation], you can pronounce Sharrin which sounds similar. My Chinese name, which means snow (雪⛄) and elf (灵🧚), looks and sounds like a girl’s name, just like Sharrin.

Research Interest

My research interests lie in fracture phase field methods, machine learning, data-driven computational mechanics, or more general computational solid mechanics topics (depending on the prospective advisor). My current research aims to incorporate data-driven methods into traditional mechanical analysis, such as the finite element method and fatigue life prediction methods, to complement each other.

Education

• MEng, Computational Mechanics, Shanghai Jiao Tong University (SJTU)
  • Sept. 2022 - Present
  • GPA: 3.82/4.0
  • Thesis: Machine-Learning-Based Fatigue Life Prediction of Fiber-Reinforced Composite Materials
• BEng, Engineering Mechanics, Shanghai Jiao Tong University (SJTU)
  • Sept. 2018 - Jun. 2022
  • GPA: 3.78/4.3 (88.8/100)
  • Thesis: Data-Driven Phase Field Fracture Analysis
  • Minor: AI+X (华东五校AI+X微辅修)

Publications

• Xue-Ling Luo, Jia-Yu Ye, Pu-Song Ma, and Lu-Wen Zhang* . Data-driven enhanced phase field models for highly accurate prediction of Mode I and Mode II fracture. Computer Methods in Applied Mechanics and Engineering 400 (2022): 115535. [Publisher] [ResearchGate]

• Pu‐Song Ma¹, Xing‐Cheng Liu¹, Xue‐Ling Luo, Shaofan Li, and Lu‐Wen Zhang* . Asymptotic homogenization of phase‐field fracture model: An efficient multiscale finite element framework for anisotropic fracture. International Journal for Numerical Methods in Engineering (2024): e7489. [Publisher] [ResearchGate]

• (In preparation) Xue-Ling Luo and Lu-Wen Zhang* . Ensembling empirical models and machine learning: An example of fatigue life prediction of fiber-reinforced composites. [Will be uploaded to arXiv before submission]

• (In preparation) Zhichao Li, Xue-Ling Luo, Qu Chen, Jun Cai, and Jinwei Dong. Geospatial cloud computing and deep learning for large-scale infectious disease data reconstruction.

Research Experience

• Acceleration Schemes of Fracture-phase-field-based Fatigue Simulation
  • Period: Jul. 2024 - Present (as a research intern)
  • Supervisor: Prof. Emilio Martínez Pañeda (University of Oxford)
  • Role: (Will be the co-1st author) A comparative study on various acceleration methods for fracture phase field simulations of fatigue, implemented using deal.II.
• Fracture Phase Field Method in Helium Embrittlement
  • Period: Jul. 2024 - Present (as a master’s student)
  • Supervisor: Prof. Luwen Zhang (SJTU)
  • Role: (Will be the co-1st author) Propose a fracture phase field method coupled with Helium diffusion and Helium bubbles and simulate it using COMSOL.
• Physics-Informed Machine Learning for Fatigue Life Prediction
  • Period: Sept. 2022 – Present (as a master’s student)
  • Supervisor: Prof. Luwen Zhang (SJTU)
  • Role: (1st author of Publication in preparation) Proposed an ensemble learning framework facilitating both empirical formulations and machine learning models (Source code and data that will be released before submission); proposed a Transformer-based model to consider the lay-up sequences of fiber-reinforced composites; constructed a benchmark platform of machine learning models for tabular prediction in Python (TabularEnsemble).
• Multiscale Fracture Phase Field Method
  • Period: Sept. 2022 – Mar. 2024 (as a bachelor’s & master’s student)
  • Supervisors: Prof. Luwen Zhang (SJTU) & Prof. Shaofan Li (UC Berkeley)
  • Role: (3rd author of Publication) Participated in the conceptualization, discussions, and revision of an asymptotic-expansion-based multiscale fracture phase field method.
• Data-driven Fracture Phase Field Method
  • Period: Sept. 2021 – Aug. 2022 (as a bachelor’s student)
  • Supervisor: Prof. Luwen Zhang (SJTU)
  • Role: (1st author of Publication) Proposed the data-driven algorithm for the fracture phase field method; implemented the proposed algorithm in MATLAB, based on a traditional 2D/3D finite element solver; validated the proposed algorithm for mode I and mode II fractures of linear elastic and neo-Hookean hyperelastic models.
• Machine Learning & Deep Learning in Geology and Public Health
  • Period: Jul. 2021 – Present (as a research intern)
  • Supervisor: Dr. Zhichao Li (Associate research fellow at Chinese Academy of Sciences)
  • Role: (2nd author of Publication in preparation) Applied the Generative Adversarial Network in imputation of temporal and spatial dengue data in Brazil; evaluated the impacts of environmental factors on the dispersion of COVID-19 from humans to animals using machine learning; applied explainable machine learning in clinical disease diagnoses.
• Morphing Airfoil Design through Topology Optimization
  • Period: Sept. 2020 - Nov. 2021 (as a undergraduate student researcher)
  • Supervisor: Prof. Wenwang Wu (SJTU)
  • Role: Performed topology optimization using ABAQUS to obtain a cellular superstructure twisting under pressure; validated the deformation behavior of the superstructure through 3D printing and experiments.
• Modeling and Force Analysis of External Piping of Aero-Engine
  • Period: Mar. 2020 - Sept. 2020 (as a undergraduate student researcher)
  • Supervisor: Prof. Yadong Wu (SJTU)
  • Role: Proposed the theoretical stress formulation of wire-wrapped pipe using elasticity theory; analyzed burst pressure values of wire-wrapping layers according to the theoretical formulation.

Honors & Awards

• National Scholarship (Top <1% nationwide, the highest honor for students in China) (Dec. 2023)
• Outstanding Teaching Assistant (Top 1%) (Sept. 2023)
• Second Prize in the China Post-Graduate Mathematical Contest in Modeling (Top 15%) (Jan. 2023)
• Excellent Undergraduate Graduation Design (Thesis) of Mechanics Major in National Universities (2/20) (Jul. 2022)
• Regal Lloyds (华高莱斯) Scholarship (2/20) (Dec. 2021)
• Changshi (常石) Scholarship (3/20) (Dec. 2020)
• Second Prize in China Undergraduate Mathematical Contest in Modeling (Top 3.6%) (Nov. 2020)
• Second Prize in Shanghai Jiao Tong University Structural Design Competition (2/56) (Nov. 2020)
• Wu Yousheng (吴有生) Scholarship (3/20) (Nov. 2019)

Teaching

• Teaching Assistant, Mechanics of Materials (Sophomore) Mar. 2024 – Jul. 2024
• Teaching Assistant, Mechanics of Materials (Sophomore) Mar. 2023 – Jul. 2023
  • Won the Outstanding Teaching Assistant (Top 1%) prize for this work
• Teaching Assistant, Theoretical Mechanics (Sophomore) Sept. 2022 – Jan. 2023

Conferences Attended

• China Computational Mechanics Conference, Dalian, China (Poster: Data-driven-based Fracture Phase Field Method) Aug. 2023
• National Symposium on Data-driven Computational Mechanics, Dalian, China Apr. 2023

Skills

• MATLAB: 2D and 3D finite element implementation with implicit and explicit solvers for the fracture phase field method
• Python: Machine learning, PyTorch/TensorFlow-based deep learning, OpenMMLab-based computer vision, and data analysis
• C++: deal.II, 2D/3D finite element implementation for beam structures, dynamics simulation of mechanical structures
• Mechanical Analysis Software: COMSOL, ABAQUS and its secondary development with Python, Ansys and Ansys Fluent, and Adams
• Auxiliary Research Skills: LaTeX, Unix, Git, Docker, Unity, Solidworks, Adobe Illustrator/Photoshop, and Visio

Languages & Tests

• Languages: English and Chinese
• TOEFL: 113 = Reading 30 + Listening 30 + Speaking 25 + Writing 28 (Jul. 2024)
• GRE: 330 = Verbal 160 + Quant 170 (May. 2024)