Chemical Data Analysis & Computational Methods

Chemical Data Analysis & Computational Methods

During my undergraduate studies at Tianjin University, I conducted research in applied chemistry with a focus on computational methods and data analysis techniques for chemical processes.

Research Focus

• Computational Chemistry: Applied statistical methods to analyze chemical reaction mechanisms
• Data Processing: Developed algorithms for processing and analyzing experimental data
• Statistical Analysis: Applied statistical techniques to identify patterns in chemical datasets
• Analytical Methods: Worked with various analytical instruments and data interpretation

Key Achievements

• Developed computational models for predicting chemical properties
• Applied machine learning techniques to chemical analysis problems
• Gained expertise in data visualization and statistical software
• Built foundation for transition into data science and analytics

Skills Developed

• Programming: Python, R, MATLAB for scientific computing
• Statistics: Regression analysis, hypothesis testing, experimental design
• Data Analysis: Data cleaning, visualization, pattern recognition
• Research Methods: Scientific methodology, literature review, technical writing

This research experience provided a strong foundation in analytical thinking and computational methods, which now informs my current work in data science and multi-modal analytics.