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Logan Wilson

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Logan, a San Diego native, graduated cum laude from Washington and Lee University in May of 2017, double majoring in Mathematics and Engineering with a minor in Music. Throughout his coursework, he excelled in applying mathematical concepts from an engineering perspective to solve problems with a methodical and analytical approach.

Throughout the MSiA program, Logan has continued to develop his knowledge of data science and machine learning, both inside and outside of the classroom. Through the practicum project, Logan and his team collaborated with Zurich North America to evaluate and improve the workers compensation pricing tool with respect to accuracy, execution, and business impact. In addition to his coursework, Logan completed an independent research project to develop a web application leveraging machine learning to make song recommendations and visualize personalized audio profiles based on song preferences from user ratings.

More recently, over the summer Logan interned in New York with the data science team at BuzzFeed. Logan designed an algorithm for identifying, sorting, and labeling trending topics for BuzzFeed News through clustering and natural language processing. Collaborating with both software engineering and data science teams, Logan built a service connecting data pipelines from several internal sources to implement his algorithm in real-time. He also had the opportunity to present the product to editors and stakeholders to showcase both the methodology of the underlying algorithm as well as how to effectively integrate it into existing workflows. The tool currently influences the content populating the trending module on, seen by hundreds of thousands of users daily.

An aspiring data scientist, Logan is especially interested in the applications of machine learning to understand how and why audiences consume digital media. As he prepares to complete his graduate education, Logan is exploring full-time opportunities to leverage data to shape today's shifting media landscape.