Song
Tang (唐宋)
Song
Tang (唐宋)
EDUCATION
Ph.D., Computer Science, University of Electronic Science and Technology of China (UESTC), 06.2017
M.S., Control Engineering, Chongqing University of Posts and Telecommunications (CQUPT), 06.2013
B.S., Electrical Engineering, Hainan University (HNU), 06.2005
WORK EXPERIENCE
Associate Professor, Institute of Machine Intelligence, University of Shanghai for Science and Technology (USST), 12.2019-Present
Assistant Researcher, Department of Informatics, Hamburg University (UHH), 06.2017-12.2019
Software Engineer, The 30th Research Institute of China Electronics Technology Group Corporation, 09.2009-09.2010
Electronic Engineer, Shanghai Mitsubishi Elevator Co., Ltd, 07.2005-09.2009
RESERACH EXPERIENCE
Assistant Researcher at UHH, 07.2017-12.2019
Dynamical neural network-based multi-modal fusion for intelligent robot.
During working toward the Ph.D. degree at UESTC, 09.2013-06.2017
Domain adaptation of object recognition and detection
During working toward the M.S. degree at CQUPT, 09.2010-06.2013
Gait of biped walk robot
Hyperchaotic invariant sets
RESERACH PROJECT
Crossmodal Learning under contract Sonderforschungsbereich Transregio 169, German Research Foundation, main investigator
STEP2DYNA, Horizon2020 RISE, main investigator
An unsupervised domain adaptive object detection method for service robots, National Natural Science Foundation of China (61773093), main investigator
The attractors coexistence and collective complexbehavior in memristive neural network, National Natural Science Foundation of China (61501073), main investigator
Note: * indicates the corresponding author.
Full list of publications in Google Scholar.
2023
S. Tang, A. Chang, F. Zhang, X. Zhu*, M. Ye* and C. Zhang, "Source-free Domain Adaptation via Target Prediction Distribution Searching", International Journal of Computer Vision, Otc. 2023. (IF = 19.6) [pdf][code]
S. Tang, Y. Shi, Z. Song, M. Ye*, C. Zhang and Jianwei Zhang*, "Progressive Source-Aware Transformer for Generalized Source-Free Domain Adaptation", IEEE Transactions on Multimedia, Otc. 2023. (IF = 7.3) [pdf][code]
L. Zhou, N. Li, M. Ye*, X. Zhu,S. Tang, "Source-free domain adaptation with Class Prototype Discovery", Pattern Recognition, Sep. 2023. (IF = 7.985) [pdf][code]
J. Mi, S. Tang, Z. Ma, D. Liu and J. Zhang, "Weakly supervised referring expression grounding via target-guided knowledge distillation", IEEE International Conference on Robotics and Automation (ICRA), June. 2023. [pdf][code]
S. Tang, W. Su, Y. Yang, L. Chen* and M. Ye, "Model adaptation via credible local context representation", CAAI Transactions on Intelligence Technology, May. 2023. (IF = 7.985) [pdf][code]
2022
S. Tang, Y. Zou, Z. Song, J. Lyu, L. Chen*, M. Ye, S. Zhong, J. Zhang, "Semantic consistency learning on manifold for source data-free unsupervised domain adaptation", Neural Networks, May. 2022, 152, pp. 467-478. (IF = 9.657) [pdf][code]
X. Pan, J. Wang, Z. Deng, Y. Shuai, W. Luo, W. Luo, Q. Xie, Y. Xiao, S. Tang, S. Jiang, C. Wu, F. Zhu, J. Zhang, W. Zhang, "A memristor-based bioinspired multimodal sensory memory system for sensory adaptation of robots", Advanced Intelligent Systems, July. 2022, 4(7), pp. 2200031. (IF = 7.298) [pdf]
2021
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Reviewer
CVPR (2021, 2022, PC Member), AAAI (2022, 2023, 2024, PC Member), ICRA, IROS, ICNSC (2022,Session chair)
Neural Networks, CAAI Transactions on Intelligence Technology, Applied Mathematical Modelling etc.
