Welcome to my portfolio
Li Qing
Graduate Student & Researcher bridging Materials Science with AI, creating intelligent systems for discovery and optimization.
Core Competencies
- Materials Characterization: TGA, DIC, Phase Analysis, Hydration Kinetics, Pore Structure Analysis, NMR Spectroscopy
- AI & Machine Learning: Deep Learning, Physics-Informed Neural Networks (PINNs), Materials Property Prediction, Data-Driven Modeling
- Programming: Python, MATLAB, Data Processing, Scientific Computing, Visualization
Research Focus
Materials-AI Fusion: Developing intelligent systems that combine traditional materials science with modern AI techniques. Automating materials analysis, predicting material properties from microstructure, accelerating discovery of novel material compositions.
Portfolio
Expertise
Technical Skills
- Materials Characterization: TGA, DIC, Phase Analysis, Hydration Kinetics, Pore Structure Analysis, NMR Spectroscopy
- AI & Machine Learning: Deep Learning, Physics-Informed Neural Networks (PINNs), Materials Property Prediction, Data-Driven Modeling
- Programming: Python, MATLAB, Data Processing, Scientific Computing, Visualization
Research Methodologies
Combining experimental materials characterization with advanced AI techniques to accelerate materials discovery and optimize processing parameters. Focus on developing physics-informed machine learning models that bridge theory and practice.
Key Achievements
- • Developed automated analysis tools for thermal gravimetric and microcracking data
- • Created physics-informed neural networks for materials property prediction
- • Published research on materials-AI fusion methodologies
- • Built comprehensive data processing pipelines for materials science workflows
Growth
Contact
Get In Touch
GitHubgithub.com/liqinglq666
Resume
I'm currently refining my resume and will have it ready soon. Feel free to reach out via email!