Summary
Baixi Sun is a Ph.D. candidate and Associate Instructor in Computer Science with nine years of experience spanning academic research and production software development. She has a strong background in large-scale data processing, ML and tensor-based methods for misinformation detection, and hands-on experience with Spark, Doc2Vec, SVMs, and deep learning from projects and teaching assignments. Her research at national labs and universities has focused on scalable surrogate models and high-performance AI on supercomputers, while industry internships and early-career roles sharpened her full-stack and backend engineering skills. As an instructor for cloud computing courses she blends theory with practical demos—having lectured on Spark SQL, streaming and ML libraries—and routinely tutors and grades graduate coursework. Notably, she bridges academic rigor and production constraints, able to prototype novel tensor-decomposition approaches and translate them into scalable Spark pipelines. Based in Bloomington, Indiana, she brings a research-driven engineering mindset to both teaching and applied AI systems.
9 years of coding experience
7 years of employment as a software developer
Bachelor's Degree, Computer Software Engineering, Bachelor's Degree, Computer Software Engineering at Harbin Engineering University
Doctor's Degree, Comouter Science, Doctor's Degree, Comouter Science at Indiana University Bloomington
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of California, Riverside
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Washington State University