Dr. Yan Wang is a research assistant professor at the Institute for AI Industry Research (AIR), Tsinghua University. His research interests include data compression powered by AI, perception in intelligent transportation and neural network compression. Before joining AIR, he was a senior researcher and team leader at SenseTime, where he and his team focus on research and product development in the fields of object detection, model compression and data compression powered by AI. He has extensive interdisciplinary knowledge and research experience in the fields of artificial intelligence, parameter estimation, computational fluid dynamics and public safety.
Profile：
https://yanwang202199.github.io
Email address:
wangyan@air.tsinghua.edu.cn
Education:
2014-2019 Tsinghua University, Safety Science and Engineering, PhD
2017-2018 Cornell University, Civil and Environmental Engineering Visiting, PhD
2010-2014 Tsinghua University, Engineering Physics, Bachelor
Career:
2022-now Institute for AI Industry Research (AIR), Tsinghua University, Research Assistant Professor
2019-2021 SenseTime. Researcher, Senior Researcher
Research Fields:
Data compression powered by AI, perception in intelligent transportation, neural network compression
Selected Publications:
1. Tongda Xu, Yan Wang, Dailan He, Chenjian Gao, Han Gao, Kunzan Liu, Hongwei Qin, Multiple-sample Neural Image Compression, NeurIPS, 2022.
2. Chenjian Gao, Tongda Xu, Dailan He, Yan Wang, Hongwei Qin, Flexible Neural Image Compression via Code Editing, NeurIPS, 2022.
3. Lina Guo, Xinjie Shi, Dailan He, Yuanyuan Wang, Rui Ma, Hongwei Qin, Yan Wang, Practical Learned Lossless JPEG Recompression with Multi-Level Cross-Channel Entropy Model in the DCT Domain, CVPR, 2022.
4. Dailan He, Ziming Yang, Weikun Peng, Rui Ma, Hongwei Qin, Yan Wang, ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding, CVPR, 2022.
5. Dailan He, Yaoyan Zheng, Baocheng Sun, Yan Wang, Hongwei Qin, Checkerboard context model for efficient learned image compression, CVPR, 2021.
6. Rundong Li, Yan Wang, Feng Liang, Hongwei Qin, Junjie Yan, Rui Fan, Fully quantized network for object detection, CVPR, 2019.
Major Honors and Awards：
2022 Champion of CVPR Challenge on Learned Image Compression (CLIC)
2018 ISCRAM Best Paper
2018 SenseTime Future Star
2014 Tsinghua Doctoral Fellowship for Future Scholar
