陈贺昌，吉林大学人工智能学院研究员，院长助理，知识驱动人机智能教育部工程研究中心副主任。作为负责人主持国家级项目5项，包括国家重大需求类项目3项（300万、150万、100万），国家自然科学基金面上项目1项（50万），青年基金1项（25万），重点项目子项2项，包括国家自然科学基金“叶企孙”科学基金子项1项（100万），新一代人工智能国家科技重大专项子项1项（60万），其它省部级项目2项，纵向经费800余万元。在人工智能领域知名期刊和会议上发表学术论文70余篇，其中，CCF/CAAI A类、ACM/IEEE Trans、中科院1区论文30余篇，包括：TKDE、TNNLS、TIST、TKDD、NeurIPS、ICML、KDD、SIGIR等。2021年获吉林省自然科学奖“一等奖”1项（排名第三），2023入选“吉林省拔尖创新人才”和“吉林省优秀青年科研创新人才”。 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

机器学习、数据挖掘、智能博弈、智能科学、具身智能

[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. Advances in Neural Information Processing Systems (NeurIPS’23), New Orleans, USA, Dec 10-16, 36, (2023): 13524-13537. (CCF A) [3]. Sili Huang, Jifeng Hu, Zhejian Yang, Liwei Yang, Tao Luo, Hechang Chen, Lichao Sun, Bo Yang. Hybrid Mamba: An Promising In-Context RL for Long-Term Decision. Advances in Neural Information Processing Systems (NeurIPS’24), New Orleans, USA, Dec 10-16, 36, (2024): 11145-1154. (CCF A) [4]. Siyuan Guo, Cheng Deng, Ying Wen, Hechang Chen, Yi Chang, Jun Wang. DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning. The Forty-first International Conference on Machine Learning (ICML’24), Vienna, Austria, Jul 21-Jul 27, (2024): 1-20. (CCF A) [5]. Sili Huang, Jifeng Hu, Hechang Chen, Lichao Sun, Bo Yang. In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought. The Forty-first International Conference on Machine Learning (ICML’24), Vienna, Austria, Jul 21-Jul 27, 2024, v235: 19871-19885. (CCF A) [6]. 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), 2024, 36(3), pp: 1299-1310. (CCF A, IF=8.9, 中科院1区) [7]. Xinqi Du, Ziyue Li, Cheng Long, Yongheng Xing, Philip S. Yu, Hechang Chen. FELight: Fairness-Aware Traffic Signal Control via Sample-Efficient Reinforcement Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024, 36(9), pp: 4678-4692. (CCF A) [8]. Fan Li, Xu Si, Shisong Tang, Dingmin Wang, Kunyan Han, Bing Han, Guorui Zhou, Yang Song, Hechang Chen. Contextual Distillation Model for Diversified Recommendation. The 30th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’24), Barcelona, Spain, Aug 25-Aug 29, (2024): 5307-5316. (CCF A) [9]. 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) [10]. 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, Feb. 07-14, Washington D.C., USA, 37, pp: 7078-7086. (CCF A) [11]. 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) [12]. Zhiwei Yang, Jing Ma, Hechang Chen, Jiawei Zhang, Yi Chang. Context-Aware Attentive Multilevel Feature Fusion for Named Entity Recognition. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024, 35(1): 973-984. (CAAI A, 中科院1区) [13]. 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, 35(10): 13411-13425. (CAAI A, 中科院1区) [14]. Liu Zhaogeng, Ji Feng, Yang Jielong, Cao Xiaofeng, Zhang Muhan, Chen Hechang, Chang Yi. Refining Euclidean Obfuscatory Nodes Helps: A Joint-Space Graph Learning Method for Graph Neural Networks. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024, 35(9): 11720-11733. (CAAI A, 中科院1区) [15]. Haiyin Piao, Shengqi Yang, Hechang Chen, Junnan Li, Jin Yu, Xuanqi Peng, Xin Yang, Zhen Yang, Zhixiao Sun, Yi Chang. Discovering Expert-Level Air Combat Knowledge via Deep Excitatory-Inhibitory Factorized Reinforcement Learning. ACM Transactions on Intelligent Systems and Technology (TIST), 2024, 15(4): 65:1-65:28. [16]. Sili Huang, Hechang Chen, Haiyin Piao, Zhixiao Sun, Yi Chang, Lichao Sun, Bo Yang. Boosting Weak-to-Strong Agents in Multi-Agent Reinforcement Learning via Balanced PPO. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024. 1-15. (CAAI A, 中科院1区) [17]. 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. [18]. 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, 145: 109917. (中科院1区) [19]. Xinqi Du, Hechang Chen, Bo Yang, Cheng Long, and Songwei Zhao. HRL4EC: Hierarchical Reinforcement Learning for Multi-mode Epidemic Control. Information Sciences, 2023, 640: 119065. (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)