Summary
Wen Tang is an applied research leader and Ph.D. in Computer Engineering with a decade of experience turning machine learning research into production-grade multi-modal AI systems. Based in California and now managing applied research at eBay, she has driven major improvements in visual search and embeddings—delivering up to 43% better top-1 matching while shrinking storage by orders of magnitude and beating a leading cloud offering. Her background spans theory (sparse dictionary learning, zero-shot image classification) to large-scale engineering (distributed training, on-the-fly embedding pipelines, multi-cluster resource management). Wen has a track record of launching industry-academic collaborations and challenges (CVPR workshops) and building practical data products— from functional zone discovery to high-accuracy web content extraction—often improving accuracy and efficiency substantially. Notably, she blends deep mathematical training with hands-on system design, enabling both novel algorithms and the infrastructure to scale them.
10 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Engineering, Doctor of Philosophy (Ph.D.), Computer Engineering at North Carolina State University
Visiting Scholar, Visiting Scholar at CentraleSupélec
Bachelor of Science (BS), Computer Science, Bachelor of Science (BS), Computer Science at Fayetteville State University
Bachelor of Science (BS), Mathematics, Bachelor of Science (BS), Mathematics at East China University of Science and Technology