Kyle Min is a research scientist at Intel Labs, working in computer vision and especially in video understanding applications. He finished his Ph.D. in EECS at the University of Michigan, advised by Prof. Jason Corso. He has devoted recent years to the development of GraVi-T, an advanced graph learning framework for efficient video understanding. He has led multiple research projects on video transformers and also won many challenges, including the Ego4D challenges and ActivityNet.