News:
[Top] In Fall 2024 and Spring 2025, I have multiple openings for postdocs and Ph.D students in the fileds of computer vision, biomedical image analysis, multimedia and machine learning. Feel free to contact me with your CV.
Dr. Yan Yan is currently an Associate Professor in the Department of Computer Science at University of Illinois Chicago. He was an assistant professor at Illinois Institute of Technology and Texas State University, a research fellow at the University of Michigan and the University of Trento. He received his Ph.D. in Computer Science at the University of Trento and M.S. at the Georgia Institute of Technology and Shanghai Jiao Tong University. He was a visiting scholar at the Carnegie Mellon University and the Advanced Digital Sciences Center (ADSC), UIUC, Singapore. He has published 100+ research papers in the fields of computer vision, machine learning and multimedia. He received IBM Best Student Paper Award in ICPR 2014, Best Paper Award in ACM Multimedia 2015 and Best Paper Finalist in ACM Multimedia 2018. He has been served as Area Chairs and PC members for several major conferences and reviewers for referred journals in computer vision and multimedia. He also served as associate editors in Neurocomputing, Computer Vision and Image Understanding (CVIU), Machine Vision and Applications (MVA), Image and Vision Computing (IVC), and guest editors in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Computer Vision and Image Understanding (CVIU) and ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM). In recent years, Dr. Yan's research has been funded by NIH, NSF, NIST, Cisco, Snap, AMD, Nvidia, etc. Know more information please check the CVM-LAB.
Most recent publications on Google Scholar.
MIM4DD: Mutual Information Maximization for Dataset Distillation
Yuzhang Shang, Zhihang Yuan, Yan Yan
Conference on Neural Information Processing Systems (NeurIPS), 2023
Boundary Guided Mixing Trajectory for Semantic Control with Diffusion Models
Ye Zhu, Yu Wu, Zhiwei Deng, Olga Russakovsky, Yan Yan
Conference on Neural Information Processing Systems (NeurIPS), 2023
Towards Saner Deep Image Registration
Bin Duan, Ming Zhong, Yan Yan
IEEE International Conference on Computer Vision (ICCV), 2023
Causal-DFQ: Causality Guided Data-free Network Quantization
Yuzhang Shang, Bingxin Xu, Gaowen Liu, Ramana Kompella, Yan Yan
IEEE International Conference on Computer Vision (ICCV), 2023
Post-training Quantization on Diffusion Models
Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Discrete Contrastive Diffusion for Cross-Modal Music and Image Generation
Ye Zhu, Yu Wu, Kyle Olszewski, Jian Ren, Sergey Tulyakov, Yan Yan
International Conference on Learning Representations (ICLR), 2023
Lipschitz Continuity Retained Binary Neural Network
Yuzhang Shang, Dan Xu, Bin Duan, Ziliang Zong, Liqiang Nie, Yan Yan
European Conference on Computer Vision (ECCV), 2022
Learning Omnidirectional Flow in 360-degree Video via Siamese Representation
Keshav Bhandari, Bin Duan, Gaowen Liu, Hugo Latapie, Ziliang Zong, Yan Yan
European Conference on Computer Vision (ECCV), 2022
Network Binarization via Contrastive Learning
Yuzhang Shang, Dan Xu, Ziliang Zong, Liqiang Nie, Yan Yan
European Conference on Computer Vision (ECCV), 2022
Quantized GAN for Complex Music Generation from Dance Videos
Ye Zhu, Kyle Olszewski, Yu Wu, Panos Achlioptas, Menglei Chai, Yan Yan, Sergey Tulyakov
European Conference on Computer Vision (ECCV), 2022
Lipschitz Continuity Guided Knowledge Distillation
Yuzhang Shang, Bin Duan, Ziliang Zong, Liqiang Nie, Yan Yan
IEEE International Conference on Computer Vision (ICCV), 2021
Describing Unseen Videos via Multi-Modal Cooperative Dialog Agents
Ye Zhu, Yu Wu, Yi Yang, Yan Yan
European Conference on Computer Vision (ECCV), 2020
Computer Vision and Multimedia Lab on CVM-LAB
Current Master students:
Alumni:
PhDs:
Visitings:
Masters with Thesis:
Undergraduates:
This website was built with jekyll based on a template by Martin Saveski.