Summary
Keenan Hom is an Artificial Intelligence intern and first-year MS student in Computational Science and Engineering at Georgia Tech with 12 years of software experience and a strong foundation in applied machine learning and data-driven simulation. He has delivered production software at Google and built ML systems in research settings—training CNNs to automate cryo-EM image quality grading at Scripps and developing recurrent-reservoir models for neural data at UCSD. Comfortable across the stack, Keenan codes in Python, Java, TypeScript, SQL and more, and has applied those skills to both web/cloud tooling and scientific pipelines. He combines industry-grade engineering practices (Agile, testing, deployment) with academic rigor and expects to publish in 2025, reflecting his ability to translate research into practical tools. Based in Atlanta, he’s eager to tackle applied data science problems in industry or research and is notable for independently creating ML algorithms that outperform baseline tools in specialized domains.
12 years of coding experience
1 year of employment as a software developer
University of California, San Diego
Master of Science - MS, Computational Science and Engineering, 3.67 GPA, Master of Science - MS, Computational Science and Engineering, 3.67 GPA at Georgia Institute of Technology
Machine Learning/Artificial Intelligence, Certificate Received, Machine Learning/Artificial Intelligence, Certificate Received at UC San Diego Extension
IB Diploma, IB Diploma at George Mason High School