Yan Yan joins CS department
Yan Yan joins CS department Heading link
This fall, Yan Yan joined the computer science department as an associate professor. Yan’s research focuses on computer vision, machine learning, multimedia, and bioinformatics.
Most recently, Yan was an assistant professor at the Illinois Institute of Technology, where he ran their Computer Vision and Multimedia Laboratory. Prior to that, Yan was an assistant professor of computer science at Texas State University and a research fellow at the University of Michigan and at the University of Trento in Italy.
Yan received his PhD at the University of Trento, MS at the Georgia Institute of Technology, and at Shanghai Jiao Tong University in China. He also served as a visiting scholar at Carnegie Mellon University and at the University of Illinois Urbana-Champaign’s Advanced Digital Sciences Center in Singapore.
Yan has published more than 100 research papers, received multiple best paper awards, and served as chair for several major conferences. The National Institutes of Health, National Science Foundation, National Institute of Standards and Technology, Cisco, Snap, Advanced Micro Devices, Nvidia, and others have funded his work.
One of Yan’s areas of focus is neural network compression. Large deep learning models can’t be put into edge devices, such as smartphones and smart cameras, which have limited memory and computing power.
“We do some neural network compression techniques, we compress large deep learning models, but we still keep the comparable accuracy for different downstream tasks,” Yan said. “We can use this technology in the smart edge devices.”
Yan also works with object tracking and detection, human pose estimation and activity recognition, multimodal machine learning, and biomedical image analysis.
“I hope to collaborate with other faculty members in different fields who want to use computer vision and machine learning techniques in their research,” Yan said.
Yan has multiple openings available for PhD students in the fields of computer vision, biomedical image analysis, multimedia, and machine learning. He is also open to undergraduate students interested in these areas.