Katie Truong Email & Phone Number

Katie Truong is a Data Analytics Intern - Singelyn Center for Innovative Analytics at Boeing. She is proficient in English. Colleagues describe her as "Katie was my student in the Location Analytics for Business class (CIS3350), and she learned about the spatial data and implementation of spatial methodologies using Python. She did a project on finding the best place to build a new EV charging station. She demonstrated her ability to use variety of complex spatial data and analytics methods to provide a solution for decision makers. She then took another class on Advanced Data Analytics (CIS4680) and she learned how to use Python to implement several NLP and timeseries models to solve real-world problems. In the project, she adopted named entity recognition on privacy policies to investigate their differences. She was one the best performing students in terms of course assignments and projects. Because of her skills and dedication, I have invited her to be part of a Boeing NLP maintenance project. She showed her ability to learn new methods and implement them to solve problems for the client. She was always professional and reliable in doing her assigned tasks. She helped to build a BERT model for custom NER and a dashboard to show main defective objects on an aircraft." and "I advised the team working on Boeing Maintenance Analytics project and Katie was a member of the team. She is intelligent, honest, and hardworking. She spent numerous hours labeling, preprocessing, and visualizing the data using Excel, Python, and Tableau and generated great insights from it. She also demonstrated that she can work independently and find solutions to problems when help is not readily available."

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  Boeing Text Mining Project

  Boeing

  Nov 2022 - Present

  The project goal is to extract object, defect, and location information from over 20k maintenance records from Boeing in order to provide insights to Boeing in controlling and preventing corrosion in aircraft. Skills: - Build Python scripts for data preprocessing, automatic labeling, splitting text into n-grams, and exploding data for visualization.- Develop a BERT (Bidirectional Encoder Representations from Transformers) model to detect the entities- Utilize Tableau for insight data visualization highlighting locations and objects with the most defects, and their correlation.