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Ping Hu |
Biography
Ping Hu is a Professor with the School of Computer Science and Engineering, University of Electronic Science and Technology of China (SCSE, UESTC). He was working as a postdoctoral researcher in the CS department at Boston University. He obtained his Ph.D. degree in the Image and Video Computing (IVC) Group at Boston University, advised by Prof. Kate Saenko and Prof. Stan Sclaroff . Before that, he was a research assistant at Nanyang Technological University, advised by Dr. Gang Wang and Prof. Yap-Peng Tan. He obtained his M.E degree from the University of Chinese Academy of Science under the supervision of Prof. Weiqiang Wang.
Ping's primary research areas are centered on the efficiency and robustness of Machine Learning and Computer Vision models. In particular, he focus on problems of video/image understanding with low/weak supervision, fast speed, and low-power consumption to address real-world applications.
胡平，电子科技大学计算机科学与工程学院教授，博士生导师，入选国家高层次青年人才计划。2023年博士毕业于美国波士顿大学，曾任波士顿大学图像与视频计算实验室博士后研究员，主要研究方向为视频场景分析与高效深度学习方法。
常年招收博士后、博士、硕士、本科实习生，欢迎邮件联系 chinahuping@gmail.com。[更多信息]
News
- 02-2024: We are organizing The 2nd Multi-Modal Video Reasoning and Analyzing Competition and Vision and Learning for an Enhanced Metaverse Workshop at ICME24.
- 01-2024: Serving as an Area Chair for ACM-MM 2024.
- 01-2024: Joining the UESTC as a faculty member at the School of Computer Science and Engineering.
- 12-2023: Serving as a Senior Program Committee (SPC) member for IJCAI-24.
- 08-2023: Serving as an Area Chair for CVPR 2024.
- 05-2023: Serving as Program Chair Assistant for NeurIPS 2023.
- 04-2023: Serving as a DEI committee member for CVPR 2023
- 01-2023: We are organizing Efficient Deep Learning for Computer Vision Workshop at CVPR23
- 12-2022: Serving as a Senior Program Committee (SPC) member for IJCAI-23.
Research
My primary research areas are centered on Computer Vision and Deep Learning, especially when the computing resources or data are limited.- Effective Perception
- Scene Understanding, Video Analysis, Multi-sensory Collaboration
- Efficient Learning
- Low-data Learning, Open-world Learning, Foundation Models with PEFT
Services
Workshop Organizers:
IEEE ICME Grand Challenge – 2nd Multi-Modal Video Reasoning and Analyzing Competition 2024.
Efficient Deep Learning for Computer Vision Workshop at CVPR23.
Visual Domain Adaptation Challenge at ICCV2019.
Conference Service:
- Area Chair, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
- Area Chair, ACM Multimedia (ACM-MM), 2024.
- Area Chair, IEEE Conference on Artificial Intelligence (CAI), 2024.
- Senior PC, International Joint Conference on Artificial Intelligence (IJCAI), 2023, 2024.
- Assistant Program Chair, International Conference on Neural Information Processing Systems (NeurIPS), 2023.
- Session Chair, International Conference on Robotics and Automation (ICRA), 2020.
Conference Reviewer:
- CVPR, ICCV, ECCV, ICLR, NeurIPS, ICML, etc.
Journal Reviewer:
- IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI)
- International Journal of Computer Vision (IJCV)
- IEEE Transactions on Image Processing (T-IP)
- ISPRS Journal of Photogrammetry and Remote Sensing (ISPRS-JPRS)
- IEEE Transactions on Multimedia (T-MM)
- IEEE Robotics and Automation Letters (RA-L)
- Computer Vision and Image Understanding (CVIU)
- IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT)
- IEEE Transactions on Computational Imaging (T-CI)
Teaching
Teaching Assistant:
- Fall 2022, Principles of Machine Learning, Boston University,
- Summer 2022, AI4All Project, Boston University
- Spring 2016, Machine Learning and Image Analysis, University of Chinese Academy of Sciences
- Fall 2015, Computer Vision, University of Chinese Academy of Sciences
- Spring 2015, Digital Image Processing, University of Chinese Academy of Sciences