Summary
Jonathan Ji is an Associate Professor of Computing at the University of Connecticut specializing in deep learning, high-performance computing, and their applications to computer vision, NLP, and robotics. He combines a decade of industry research experience at companies like Intel, Microsoft, and Yahoo with a strong academic track record—over 50 publications in top conferences (CVPR, NeurIPS, ICCV, ICLR, ICML) and sustained funding from NSF, NIH, DoD, and industry partners. His work focuses on efficient algorithms that learn from heterogeneous data (image, audio, text, time series) at scale to automate decision-making in dynamic environments. A Duke Ph.D. trained under Larry Carin and a Senior Member of IEEE, he has led both academic centers and DoD-funded initiatives while mentoring students in ML, DL, and HPC projects. Less obvious: his career blends production-facing research on web search and ranking with foundational advances in Bayesian and compressed sensing methods, reflecting a rare ability to move ideas from prototypes to deployed systems.
10 years of coding experience
18 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Electrical and Computer Engineerning, Doctor of Philosophy (Ph.D.) Electrical and Computer Engineerning at Duke University
BS and MS Electrical Engineering, BS and MS Electrical Engineering at Xidian University