Kyle Min is a Staff Research Scientist in AI/ML at Intel Labs, based in Santa Clara, CA. His research centers on egocentric video understanding and efficient video representations, where he leads projects using sparse transformers and graph neural networks. He actively collaborates with academia on topics such as diffusion models and machine unlearning.

He earned his Ph.D. and M.S. in EECS from the University of Michigan, and his B.S. from Seoul National University. His contributions have been recognized at top-tier conferences like CVPR, ECCV, and ICCV, and he has won multiple international challenges including Ego4D and ActivityNet.

Kyle also has experience teaching computer vision and advising students in physics and mathematics. Beyond research, he engages in academic service and professional outreach, and enjoys Brazilian Jiu Jitsu, squash, and rock climbing.