Yan Yan
Gladwin Development Chair Assistant Professor
Department of Computer Science
Illinois Institute of Technology
office: Stuart Building Room 237C
email: yyan34 [AT] iit.edu
News:
[Top] In Fall 2024, 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.
Bio
Dr. Yan Yan is currently a Gladwin Development Chair Assistant Professor in the Department of Computer Science at Illinois Institute of Technology. He was an assistant professor at the 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.
Publications
Most recent publications on Google Scholar.
Versatile Navigation under Partial Observability via Value-Guided Diffusion Policy
Gengyu Zhang, Hao Tang, Yan Yan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
Token Transformation Matters: Towards Faithful Post-hoc Explanation for Vision Transformer
Junyi Wu, Bin Duan, Weitai Kang, Hao Tang, Yan Yan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
On the Faithfulness of Vision Transformer Explanations
Junyi Wu, Weitai Kang, Hao Tang, Yuan Hong, Yan Yan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
Enhancing Post-training Quantization Calibration through Contrastive Learning
Yuzhang Shang, Gaowen Liu, Ramana Rao Kompella, Yan Yan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
Efficient Multitask Dense Predictor via Binarization
Yuzhang Shang, Dan Xu, Gaowen Liu, Ramana Rao Kompella, Yan Yan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
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
Projects
Teaching
CS 577: Deep Learning (Fall 2023)CS 584: Machine Learning (Spring 2024, Spring 2023, Fall 2022, Fall 2021, Spring 2021)
CS 595: Advanced Topics on Computer Vision and Multimedia (Spring 2022)
Members
Computer Vision and Multimedia Lab on CVM-LAB
Bin Duan (Fall 2019-current, B.S.: Lanzhou University)
Jianyuan Ni (txstate, Fall 2020-current)
Yuzhang Shang (Fall 2021-current, B.S.: Wuhan University)
Bin Xie (Fall 2021-current, M.S.: IIT)
Changchang Sun (Fall 2021-current, B.S./M.S.: Shandong University)
Zhenghao Zhao (Fall 2022-current, M.S.: IIT)
Weitai Kang (Fall 2022-current, B.S.: Sun Yat-sen University)
Junyi Wu (Spring 2023-current, B.S.: Sun Yat-sen University)
Gengyu Zhang (Spring 2023-current, M.S.: University of Georgia)
Haoxuan Wang (Fall 2023-current, B.S./M.S.: Shanghai Jiao Tong University)
Kaiang Wen (Fall 2023-current, B.S.: Beijing Jiao Tong University)
Feiran Wang (Spring 2024-current, M.S.: University of Illinois Urbana-Champaign)
Mark Leischner (Part-time, Fall 2021-current, working at Google)
Bingxin Xu (Part-time, Spring 2023-current, working at Discover Financial Services)
Current Master students:
Nikhil Sharma (Spring 2024-current)
Alumni:
Postdocs:
Gaowen Liu (Postdoc 2018-2020, First Employment: Research Scientist at Cisco Research)
PhDs:
Keshav Bhandari (PhD 2018-2022, First Employment: Senior Scientist at Tesla)
Ye Zhu (PhD 2019-2023, First Employment: Postdoctoral Researcher at Princeton University)
Visitings:
Hao Tang (Visiting PhD 2018-2019 from University of Trento, Next: Postdoc at ETH Zürich)
Yutian Lin (Visiting PhD 2018-2019 from University of Technology Sydney, Next: Associate Professor at Wuhan University)
Xianjin Han (Visiting PhD 2019-2020 from Shandong University, Next: Postdoc at National University of Singapore)
Na Zheng (Visiting PhD 2019-2020 from Shandong University, Next: Postdoc at National University of Singapore)
Aihua Zheng (Visiting Professor 2019-2020 from Anhui University)
Songsong Wu (Visiting Professor 2018-2019 from Nanjing University of Posts and Telecommunications)
Masters with Thesis:
Castaneda Lopez Luis (Master 2022, First Employment: Software Engineer at NextShift)
Chaguer Reda (Master 2022, First Employment: Software Engineer at Meta)
Elomari Alaoui Ismail (Master 2022, First Employment: Software Dev Engineer at Amazon)
Jorge Cervera Perez (Master 2021, First Employment: Senior Software Engineer at Qualcomm)
De Miguel Juan Carlos (Master 2021, First Employment: Data Scientist at Caterpillar Inc)
Ali Issaoui (Master 2021, First Employment: Software Engineer at Amazon Web Services)
Undergraduates:
Mario A. DeLaGarza (Undergraduate 2019, First Employment: Software Engineer at Google)
Theo William Guidroz (Undergraduate 2021-2022, First Employment: Software Engineer at Google)
Chengyuan Xue (University of Toronto REU 2023, Next: University of Toronto)
William Zhu (UChicago High School Student 2022, Next: Yale University)
Kavya Uppal (Illinois Mathematics and Science Academy High School Student 2023)
Misc
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