Mr. Haojie Liu | Machine Vision | Best Researcher Award
Ph.D. candidate at Zhejiang University | China
Haojie Liu is a Ph.D. candidate at Zhejiang University, China, specializing in control science and engineering. His research focuses on advanced topics in artificial intelligence, including person re-identification, multi-modal learning, and content-based visual search. He has published extensively in leading international journals such as IEEE TNNLS, IEEE IoT Journal, IEEE JSTSP, IEEE TKDE, and IEEE TCSS, along with multiple papers under review in prestigious venues including IJCV and IEEE TSMC. His contributions have been recognized through innovative approaches such as spectrum-aware feature augmentation, modality bias calibration, and collaborative mixed learning for visible-infrared person re-identification, significantly advancing the field of AI-driven surveillance and smart systems.
Profile Verification
Scopus
Education Details
He is pursuing a doctoral degree in control science and engineering at Zhejiang University under the supervision of Prof. Wei Jiang. He previously completed a joint master’s program in computer science and technology at Xiamen University under Prof. Rongrong Ji and obtained his master’s degree in computer science and technology at Guizhou Normal University under Prof. Daoxun Xia.
Professional Experience
He has gained professional experience as a visual algorithm engineer at the Yuyao Research Center, Zhejiang University Robotics Research Institute in Ningbo, China, where he contributed to the development and application of advanced visual recognition and learning systems.
Research Interests
His primary research interests include person re-identification, multi-modal learning, and content-based visual search, with a focus on bridging modality gaps, enhancing model robustness, and advancing real-world applications in intelligent visual perception and surveillance.
Awards and Honors
He has been recognized with multiple awards for academic excellence and innovation, including provincial-level prizes in national innovation and entrepreneurship competitions, honors as an outstanding graduate, and distinctions such as the university-level three-good student award.
Publication Top Notes
SFANet: A Spectrum-Aware Feature Augmentation Network for Visible-Infrared Person Reidentification. IEEE Transactions on Neural Networks and Learning Systems, 2023.
Visible-Thermal Person Reidentification in Visual Internet of Things with Random Gray Data Augmentation and A New Pooling Mechanism. IEEE Internet of Things Journal, 2023.
Towards Homogeneous Modality Learning and Multi-Granularity Information Exploration for Visible-Infrared Person Re-Identification. IEEE Journal of Selected Topics in Signal Processing, 2023.
Inter-Intra Modality Knowledge Learning and Clustering Noise Alleviation for Unsupervised Visible-Infrared Person Re-Identification. IEEE Transactions on Knowledge and Data Engineering, 2024.
Modality Bias Calibration Network via Information Disentanglement for Visible-Infrared Person Re-Identification in Social Surveillance System. IEEE Transactions on Computational Social Systems, 2024.
Conclusion
Through his strong academic background, impactful research contributions, and recognized achievements, Haojie Liu has established himself as a promising researcher in the fields of artificial intelligence, computer vision, and intelligent surveillance, with significant potential for advancing multi-modal learning and real-world applications in AI-driven systems.