People / Alumni / Class of 2023
I graduated in advance from American University and majored in Statistics, specializing in Data Science. While studying at American University, I mastered many programming languages like Python, R, SQL, and Java. Although, as an undergraduate student, I have taken many courses at the graduate level. I learned a lot about how to clean, explore the data, and model through machine learning. I also learned parallel programming, Natural Language Processing, and so on. These skills help me build a solid path in real-world data analysis. Although the course load was heavy, I worked as a research assistant at American University. Under the help of Professor David Gerard, Thomas and I succeeded in building an R package called Glipld to examine a new approach to measure linkage disequilibrium, the degree of association of alleles of different loci. With the help of the supercomputer, we analyzed the real data and got some exciting results. Then, our result was posted in the JSM. During this period, I not only consolidated my statistics knowledge, programming skills, and collaboration skills but also learned many high-level statistics, including EM algorithms, Markov chains, simulation, and so on. This experience helped me learn how to combine statistics and programming skills to solve those real-world issues. Beyond the research, I built an R package for some small finite groups like the Klein-4 group, as S3 objects called sgroupr, and a shiny app with interactive graphs via Leaflet and Plotly. Besides, I also used transformers to build a system to check elements in the essays during my NLP courses. As an incoming MSiA* program student, I look forward to creating some awesome works with classmates and professors and improving my programming and analysis skills. I hope to become a professional data scientist and apply data science to business.
*later renamed MS in Machine Learning and Data Science
