王靖，bet356手机版唯一官网登录助理研究員，研究方向包括機器學習、大模型、學習基因等，研究成果發表于國際期刊IEEE TPAMI、IEEE TNNLS、IEEE TCSVT，以及國際會議ICML、AAAI、IJCAI上。獲得江蘇省優秀博士學位論文獎、吳文俊優秀博士學位論文（提名）獎，主持國家自然科學基金、江蘇省自然科學基金以及橫向項目多項。
2015年 - 2021年，bet356手机版唯一官网，bet356手机版唯一官网，博士研究生，導師 耿新 教授；
2013年 - 2015年，東北大學，信息學院，碩士研究生，導師 王興偉 教授；
2009年 - 2013年，蘇州科學大學，電子學院，本科生；
2022年 - 至今，bet356手机版唯一官网，bet356手机版唯一官网，助理研究員
期刊論文（*表示共同一作）：
Zhiqiang Kou, Jing Wang*, Yuheng Jia, and Xin Geng. Inaccurate Label Distribution Learning. IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), 2024, in press (CCF B)
Jing Wang and Xin Geng. Explaining the Better Generalization of Label Distribution Learning for Classification. SCIENCE CHINA Information Sciences (SCIS), 2024, in press (CCF A)
Adam AQ Mohammed, Xin Geng, Jing Wang, and Zafar Ali. Driver distraction detection using semi-supervised lightweight vision transformer. Engineering Applications of Artificial Intelligence (EAAI), vol. 129, 107618, Mar. 2024
Jing Wang, Jianhui Lv, and Xin Geng. Label Distribution Learning by Partitioning Label Distribution Manifold. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2023, in press (CCF B)
Jing Wang and Xin Geng. Large Margin Weighted k-Nearest Neighbors Label Distribution Learning for Classification. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2023, in press (CCF B)
Zhiqiang Kou, Jing Wang*, Yuheng Jia, Biao Liu, and Xin Geng. Instance-Dependent Inaccurate Label Distribution Learning. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2023, in press (CCF B)
Yuexuan An, Hui Xue, Xingyu Zhao, and Jing Wang. From instance to metric calibration: A unified framework for open-world few-shot learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPMAI), 2023, inpress (CCF A)
Jing Wang and Xin Geng. Label distribution learning by exploiting label distribution manifold. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 34(2): 839-852, Feb. 2023 (CCF B)
Jing Wang, Xin Geng, and Hui Xue. Re-weighting large margin label distribution learning for classification. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 44(9): 5445-5459, Sep. 2022 (CCF A)
王靖, 耿新. 标記分布學習. 中國人工智能學會通訊, 6(9): 21-25, 2016
會議論文：
Zhiqiang Kou, Jing Wang*, Jiawei Tang, Yuheng Jia, and Xin Geng. Exploiting multi-Label correlation in label distribution learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'24). 2024, in press (CCF A 類會議)
Xingyu Zhao, Yuexuan An, Ning Xu, Jing Wang, and Xin Geng. Imbalanced label distribution learning. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI'23). 2023, pp. 11336-11344(CCF A 類會議)
Jing Wang and Xin Geng. Label distribution learning machine. In: Proceedings of the International Conference on Machine Learning (ICML'21). 2021. 10749-10759. (CCF A 類會議)
Jing Wang and Xin Geng. Learn the highest label and rest label description degrees. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'21). 2021. 3097-3103. (CCF A 類會議)
Jing Wang and Xin Geng. Classification with label distribution learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'19). 2019. 3712-3718. (CCF A 類會議)
Jing Wang and Xin Geng. Theoretical analysis of label distribution learning. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI'19). 2019. 5256-5263. (CCF A 類會議)
江蘇省優秀博士學位論文獎；
吳文俊優秀博士學位（提名）獎；
江蘇省計算機學會優秀博士學位論文獎；
bet356手机版唯一官网優秀博士學位論文獎；
入選江蘇省卓越博士後計劃；
