Xin LIU
St-Sulpice
Summary
Experienced in applying analytical and numerical methods to successfully model diverse systems, including molecular and large-scale mechanical structures. Consistently create and improve computational methods for dynamic and static analysis of engineering systems. Thrive in collaborative team environments and contribute to multi-disciplinary projects.
Overview
6
6
years of professional experience
Work History
Materials Scientist
École Polytechnique Fédérale de Lausanne (EPFL)
10.2024 - Current
- Performed computational modeling of metal-ceramic composites using multi-scale materials science and mechanical simulations to predict atomic structures, thermodynamic stability, and exceptional mechanical properties (e.g., wear resistance, ductility), guiding the development of advanced materials for high-precision watch components
- Conducted high-throughput quantum mechanical simulations to model atomistic structures of refractory carbide materials, and developed a universal graph neural network (GNN)-based machine learning force field to accelerate atomic-scale property prediction while maintaining quantum-level accuracy
Research Assistant
École Polytechnique Fédérale de Lausanne (EPFL)
10.2020 - 09.2024
- Developed a phase-field dislocation dynamics algorithm to simulate dislocation motion in metal alloys, combining theoretical modeling with a Python-based simulation framework. Achieved 90% reduction in computational cost versus traditional atomistic methods, enabling large-scale microstructure evolution studies for alloy design
- Uncovered the governing role of local chemical ordering in modulating strength mechanisms of Mo-Nb-Ta-W refractory high-entropy alloys (RHEAs), designing a predictive theoretical model coupled with Monte Carlo simulations to quantify atomic-scale compositional fluctuations. Achieved high accuracy in predicting alloy strength variations, overcoming a critical barrier in RHEA design for extreme environment applications
- Made novel discoveries into the dislocation motion behavior in Mg using Machine Learning model. Elucidated the nanoscale deformation mechanisms of Mg across different temperature regimes
R&D Intern
IFP Energies Nouvelles
02.2020 - 07.2020
- Conducted Finite Element Method (FEM) simulations to analyze wind turbine vibration dynamics under degradation defects (e.g., blade cracks, bearing wear), correlating structural performance degradation with defect severity to prioritize predictive maintenance strategies for renewable energy systems
- Designed and validated operational modal analysis (OMA) algorithms using stochastic subspace identification (SSI) and frequency-domain decomposition (FDD), in defect detection under high-noise conditions, enhancing reliability of structural health monitoring frameworks
R&D Intern
Freyssinet International & Cie
06.2019 - 08.2019
- Conducted Finite Element Analysis (FEA) of pre-stressed anchor blocks for a patent-pending engineering project, evaluating mechanical behavior under load conditions to validate design feasibility
- Optimized anchor block geometries in SolidWorks, refining structural design to enhance load-bearing capacity and ensure compliance with performance standards
Education
Ph.D. - Materials Science and Engineering
École Polytechnique Fédérale De Lausanne (EPFL)
Lausanne, Switzerland10.2024
Dipl.Ing. - Department of Mechanics and Materials
École Nationale Des Ponts Et Chaussées (IP Paris)
Paris, France07.2020
M.Eng. - Department of Mechanics
Tonji University
Shanghai, China07.2018
B.Eng. - Department of Mechanics
Tonji University
Shanghai, China07.2017
Skills
- Python
- Machine Learning
- High-Performance Computing
- Finite element method
- Optimization
- Multi-scale modeling
- Solid mechanics
Journal Publications
- Atomistic simulations reveal strength reductions due to short-range order in alloys, Xin Liu and W.A. Curtin, Acta Materialia, 263, 2024, 119471
- Strengthening by {110} and {112} edge dislocations in BCC high entropy alloys, Xin Liu et al., Modelling and Simulation in Materials Science and Engineering, 32, 2024
Honors And Awards
- Shanghai Outstanding Graduate Student Award, 2017, This award was given to the top graduate students (5%) in Shanghai universities.
- China National Scholarship, 2014, 2015, The highest honorary national scholarship for students in the top 0.02% in higher education.
Languages
English
Advanced (C1)
French
Upper intermediate (B2)
Chinese (Mandarin)
Bilingual or Proficient (C2)
Timeline
Materials Scientist
École Polytechnique Fédérale de Lausanne (EPFL)
10.2024 - Current
Research Assistant
École Polytechnique Fédérale de Lausanne (EPFL)
10.2020 - 09.2024
R&D Intern
IFP Energies Nouvelles
02.2020 - 07.2020
R&D Intern
Freyssinet International & Cie
06.2019 - 08.2019
Ph.D. - Materials Science and Engineering
École Polytechnique Fédérale De Lausanne (EPFL)
Dipl.Ing. - Department of Mechanics and Materials
École Nationale Des Ponts Et Chaussées (IP Paris)
M.Eng. - Department of Mechanics
Tonji University
B.Eng. - Department of Mechanics
Tonji University
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