陈贺昌

职称:副教授、博士生导师

毕业院校:吉林大学

email:chenhc@jlu.edu.cn

个人主页:https://www.semanticscholar.org/author/Hechang-Chen/2721051

研究方向:机器学习、数据挖掘、智能博弈、知识工程、复杂系统

个人简介

陈贺昌,吉林大学人工智能学院研究员,博士生导师,吉林大学人工智能学院院长助理,知识驱动人机智能教育部工程研究中心副主任,吉林省边防基础设施专家,省委军民融合办专家。作为负责人主持国家级项目4项,包括军委科技委主题项目2项(300万,150万),火箭军预研项目1项(100万),国家自然科学基金青年基金1项(25万),总经费575万元。作为骨干成员参与国家级项目4项,包括军委科技委重点项目子项1项,装备预研教育部创新团队项目1项,“叶企孙”科学基金联合基金重点项目1项,科技创新2030-“新一代人工智能”重大项目1项。近五年,在人工智能领域著名国际期刊和会议上发表CCF A类、Trans系列和中科院1区论文20余篇,其中,NeurIPS 2篇、SIGIR 1篇、AAAI 1篇、IJCAI 1篇、TKDE 1篇、TNNLS 2篇、TKDD 1篇,以及其它中科院1区论文10余篇。2021年获吉林省自然科学奖“一等奖”1项(排名第三),2023年获吉林省拔尖创新人才和吉林省优秀青年科研创新人才项目支持。


工作经历

2021.07 —— 至 今        吉林大学人工智能学院  研究员/副教授

2018.12 —— 2021.07   吉林大学人工智能学院  副研究员/助理教授

教育经历

2014.09 —— 2018.12    吉林大学计算机科学与技术学院  计算机软与理论专业(国家首批重点学科) 博士

2017.07 —— 2018.01    香港浸会大学(Hong Kong Baptist University, HKBU)  计算机学院  健康及医疗咨询学研究中心  访问博士

2015.11 —— 2016.12    美国伊利诺伊大学芝加哥校区(The University of Illinois at Chicago, UIC)   计算机学院   联合培养博士

讲授课程

《机器学习与模式识别》、《数据挖掘》、《人工智能前沿》、《人工智能导论》

科研项目

主持项目:

[1]. 先进技术类项目,300万,负责人。

[2]. 先进技术类项目,150万,负责人。

[3]. 先进技术类项目,100万,负责人。

[4]. 国家自然科学基金青年基金:异构数据驱动的输入型传染病主动监控方法, 25 万,负责人。

参与项目:

[1]. 军科委重点项目子项,1000万,骨干成员。

[2]. 装备预研教育部创新团队项目,150万,骨干成员。

[3]. “叶企孙”科学基金联合基金重点项目,237万,骨干成员。

[4]. 科技创新2030-“新一代人工智能”重大项目,496万,骨干成员。

代表性论文

        在机器学习和数据挖掘领域国际著名期刊和会议上发表学术论文60多篇,代表性成果如下:

[1]. Jifeng Hu, Yanchao Sun, Hechang Chen, Sili Huang, Haiyin Piao, Yi Chang, Lichao Sun. Distributional reward estimation for effective multi-agent deep reinforcement learning. In Proceedings of the International Conference on the Advances in Neural Information Processing Systems (NeurIPS’22), New Orleans, USA, Nov 28-Dec 9, 35, (2022): 12619-12632. (CCF A)

[2]. Huang, Sili, Yanchao Sun, Jifeng Hu, Siyuan Guo, Bo Yang, Hechang Chen, Yi Chang, Lichao Sun. Learning Generalizable Agents via Saliency-Guided Features Decorrelation. In Proceedings of the International Conference on the Advances in Neural Information Processing Systems (NeurIPS’23), New Orleans, USA, 2023. (CCF A)

[3]. Siyuan Guo, Lixin Zou, Hechang Chen, Bohao Qu, Haotian Chi, Philip S. Yu, Yi Chang. Sample Efficient Offline-to-Online Reinforcement Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023. (CCF A)

[4]. Siyuan Guo, Lixin Zou, Yiding Liu, Wenwen Ye, Suqi Cheng, Shuaiqiang Wang, Hechang Chen, Dawei Yin, Yi chang. Enhanced Doubly Robust Learning for Debiasing Post-Click Conversion Rate Estimation. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’21), Virtual Event, Canada, July 11–15, 2021: 275-284. (CCF A)

[5]. Xing Chen, Dongcui Diao, Hechang Chen, Hengshuai Yao, Haiyin Piao, Zhixiao Sun, Zhiwei Yang, Randy Goebel, Bei Jiang, Yi Chang. The Sufficiency of Off-policyness and Soft Clipping: PPO is still Insufficient According to an Off-policy Measure. In Proceedings of the 37th International Conference on the Association for the Advancement of Artificial Intelligence (AAAI’23), 2023, February 07-14, Washington D.C., USA, Vol. 37, No. 6, pp. 7078-7086. (CCF A)

[6]. Zhiwei Yang, Hechang Chen, Jiawei Zhang, Jing Ma, Yi Chang. Attention-based Multi-level Feature Fusion for Named Entity Recognition. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI’20), Virtual Event, Japan, January 7-15, 2021: 3594-3600. (CCF A)

[7]. Zhiwei Yang, Jing Ma, Hechang Chen, Jiawei Zhang, Yi Chang. Context-aware Attentive Multi-level Feature Fusion for Named Entity Recognition. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022. DOI: 10.1109/TNNLS.2022.3178522. (中科院1区)

[8]. Zhaogeng Liu, Jielong Yang, Xionghu Zhong, Wenwu Wang, Hechang Chen, and Yi Chang. A Novel Composite Graph Neural Network. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023. (中科院1区)

[9]. Xueyan Liu, Bo Yang, Hechang Chen, Katarzyna Musial, Hongxu Chen, Yang Li, Wanli Zuo. A Scalable Redefined Stochastic Blockmodel. ACM Transactions on Knowledge Discovery from Data (TKDD), 2021, 15(3): 46:1-46:28. (CCF B)

[10]. Xinqi Du, Hechang Chen, Che Wang, Yongheng Xing, Jielong Yang, Philip S. Yu, Yi Chang, Lifang He. Robust multi-agent reinforcement learning via Bayesian distributional value estimation. Pattern Recognition, available online 28 August 2023, 109917. (中科院1区)

[11]. Xinqi Du, Hechang Chen, Bo Yang, Cheng Long, and Songwei Zhao. HRL4EC: Hierarchical reinforcement learning for multi-mode epidemic control. Information Sciences 640 (2023): 119065 - 119065. (中科院1区)

[12]. Tianyi Liu, Hechang Chen, Jifeng Hu, Zhejian Yang, Bo Yu, Xinqi Du, Yinxiao Miao, Yi Chang. Generalized Multi-Agent Competitive Reinforcement Learning with Differential Augmentation. Expert Systems with Applications, 2023. (中科院1区)

[13]. Hongren Zhou, Hechang Chen∗, Bo Yu∗, Shuchao Pang, Xianling Cong, Lele Cong. An End-to-End Weakly Supervised Learning Framework for Cancer Subtype Classification using Histopathological Slides. Expert Systems with Applications, 2023. (中科院1区)

[14]. Bo Yu, Peng Yin, Hechang Chen, Yifei Wang, Yu Zhao, Xianling Cong, Jouke Dijkstra, and Lele Cong. Pyramid Multi-Loss Vision Transformer for Thyroid Cancer Classification Using Cytological Smear. Knowledge-Based Systems, 2023. (中科院1区)

[15]. Yue Wei, Hechang Chen, Bo Yu, Chengyou Jia, Xianling Cong, and Lele Cong. Multi-scale Sequential Feature Selection for Disease Classification using Raman Spectroscopy Data. Computers in Biology and Medicine (CIBM), 162 (2023): 107053. (中科院1区)

[16]. Bo Yu, Hechang Chen, Chengyou Jia, Hongren Zhou, Lele Cong, Xiankai Li, Jianhui Zhuang, and Xianling Cong. Multi-modality multi-scale cardiovascular disease subtypes classification using Raman image and medical history. Expert Systems with Applications, 2023, 224: 119965. (中科院1区)

[17]. Bo Yu, Hechang Chen, Yunke Zhang, Lele Cong, Shuchao Pang, Hongren Zhou, Ziye Wang, Xianling Cong. Data and Knowledge Co-driving for Cancer Subtypes Classification on Multi-Scale Histopathological Slide. Knowledge-Based Systems, 2023, 260: 110168. (中科院1区)

[18]. Yang Li, Bo Yang, Xuehua Zhao, Zhejian Yang, Hechang Chen. SSBM: A signed stochastic block model for multiple structure discovery in large-scale exploratory signed networks. Knowledge-Based Systems, 2023, 259: 110068. (中科院1区)

[19]. Liping Huang, Yongjian Yang, Hechang Chen, Yunke Zhang, Zijia Wang, Lifang He. Context-aware road travel time estimation by coupled tensor decomposition based on trajectory data. Knowledge-Based Systems, 2022, 245: 108596. (中科院1区)

[20]. Bo Yang, Hongbin Pei, Hechang Chen, Jiming Liu, Shang Xia. Characterizing and Discovering Spatiotemporal Social Contact Patterns for Healthcare. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017, 39(8): 1532-1546. (CCF A)



社会兼职

吉林省边防基础设施专家,省委军民融合办专家

机械工业教育协会,人工智能与大数据专业委员会委员

     

担任多个国际著名期刊和会议的审稿人,包括:

TPAMI: IEEE Transactions on Pattern Analysis and Machine Intelligence

TKDE: IEEE Transactions on Knowledge and Data Engineering

TCYB: IEEE Transactions on Cybernetics

TITS: IEEE Transactions on Intelligent Transportation Systems

TKDD: ACM Transactions on Knowledge Discovery from Data

TNNLS: IEEE Transactions on Neural Networks and Learning Systems

KBS: Knowledge-Based Systems

EAAI: Engineering Applications of Artificial Intelligence


NeurIPS: Advances in Neural Information Processing Systems

ICML: International Conference on Machine Learning

ICLR: International Conference On Learning Representations

KDD: Knowledge Discovery and Data Mining

WWW: The Web Conference

AAAI: AAAI (Association for the Advancement of Artificial Intelligence) Conference on Artificial Intelligence

IJCAI: Joint Conference on Artificial Intelligence

WSDM: ACM International Conference on Web Search and Data Mining



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