Data analysis is becoming more and more important in solving real-world problems recently. It is widely applied in diverse studies in Science, Technology, Engineering, and Mathematics fields such as the oxygen vacancies on proton conduction pathways in yttrium-doped barium zirconate, image processing of mosquitoes, and Gastroesophageal reflux disease. Along with programming languages, various methods were applied in studies of this panel to analyze and visualize the trend of data such as a Large-scale Atomic/Molecular Massively Parallel Simulator, climbing nudge elastic band, time-based measures of centrality, and Kinetic Monte Carlo for characterizing long-range proton conduction, edge detection methods for extracting the traps and capturing mosquitoes' real maps and logistic regression method for scrutinizing the relationship between Gastroesophageal reflux disease and covid-19 pandemic. The data was organized logically to generate models that lead to valid results and conclusions for future studies.

Panel Moderator:

• Maria Alexandra Gomez, Professor of Chemistry,

Speakers:

• Chuhan Wang '24, Computer Science and Mathematics
• Karry Wang '23, Mathematics and Economics
• Charlotte Mao '24, Psychology
• Marie Nguyen '24, Data Science
• Astrid Zhao '24, Computer Science and Statistics double major