Chuan Qin (秦川)

Chuan Qin (秦川)

CNIC, CAS

Dr. Chuan Qin is currently an Associate Professor at the Computer Network Information Center, Chinese Academy of Sciences. Previously, he gained extensive industry experience as a Senior Algorithm Engineer at Baidu, China’s leading search engine and AI company, and as a Senior Researcher at BOSS Zhipin, the country’s largest online recruitment platform. He earned his Ph.D. in Computer Science from the University of Science and Technology of China (USTC) in 2021, under the mentorship of Prof. Hui Xiong and Prof. Enhong Chen, following a B.S. in Computer Science from USTC in 2015. His general research interests include data mining and machine learning, with a focus on knowledge computing, cognitive computing, representation learning, and large foundational models. He is also committed to advancing these technologies’ interdisciplinary applications across the natural and social sciences. He has published more than 50 top-tier journals and leading conference proceedings such as IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), ACM Transactions on Information Systems (TOIS), ACM Transactions on Management Information Systems (TMIS), SIGKDD, SIGIR, NeurIPS, TheWebConf, IJCAI, AAAI, etc. He has been honored with the Excellence Award of the President’s Scholarship from Chinese Academy of Science (2021), a nomination for the Baidu Scholarship (top 20 globally) (2021), the Best Student Paper Award of SIGKDD-2018, and the 2022 Annual Hot Paper Award of SCIENCE CHINA Information Sciences.

🔥 News

  • 2025.03:  🎉🎉 The technical report of the SciHorizon project is now online arXiv:2503.13503. Welcome to check it out!
  • 2025.01:  🎉🎉 Our evaluation platform for AI4Science, SciHorizon, is now live. Stay tuned!
  • 2025.01:  🎉🎉 Two paper accepted by TMIS. Congrats to all the collaborators!

📝 Publications

(* Corresponding Authors, + Co-first Authors)

In the Year of 2025:

  • Chuan Qin, Xin Chen, Chengrui Wang, Pengmin Wu, Xi Chen, Yihang Cheng, Jingyi Zhao, Meng Xiao, Xiangchao Dong, Qingqing Long, Boya Pan, Han Wu, Chengzan Li, Yuanchun Zhou, Hui Xiong, Hengshu Zhu. Scihorizon: Benchmarking ai-for-science readiness from scientific data to large language models. arXiv preprint arXiv:2503.13503, 2025. [paper]

  • Yang Ji, Ying Sun, Yuting Zhang, Zhigaoyuan Wang, Yuanxin Zhuang, Zheng Gong, Dazhong Shen, Chuan Qin, Hengshu Zhu, Hui Xiong. A Comprehensive Survey on Self-Interpretable Neural Networks. arXiv preprint arXiv:2501.15638, 2025. [paper]

  • Chuan Qin, Chuyu Fang, Kaichun Yao, Xi Chen, Fuzhen Zhuang, Hengshu Zhu. COTR: Efficient Job Task Recognition for Occupational Information Systems with Class-Incremental Learning. ACM Transactions on Management Information Systems (ACM TMIS), 2025. [paper]

  • Zhenyu Tong+, Chuan Qin+, Chuyu Fang, Kaichun Yao, Xi Chen, Jingshuai Zhang, Chen Zhu, Hengshu Zhu. From Missteps to Mastery: Enhancing Low-Resource Dense Retrieval through Adaptive Query Generation. In Proceedings of the 31st SIGKDD Conference on Knowledge Discovery and Data Mining V.1 (SIGKDD-2025), 2025. [paper]

  • Haiping Ma, Manwei Li, Chuan Qin*, Dazhong Shen, Hengshu Zhu, Xingyi Zhang, Hui Xiong. Joint Ability Assessment for Talent Recruitment: A Neural Cognitive Diagnosis Approach. ACM Transactions on Management Information Systems (ACM TMIS), 2025. [paper]

  • Yang Ji, Ying Sun, Yuting Zhang, Zhigaoyuan Wang, Yuanxin Zhuang, Zheng Gong, Dazhong Shen, Chuan Qin, Hengshu Zhu, Hui Xiong. A Comprehensive Survey on Self-Interpretable Neural Networks. arXiv preprint arXiv:2501.15638, 2025. [paper]

In the Year of 2024:

  • Chuan Qin, Zhang Le, Yihang Cheng, Rui Zha, Dazhong Shen, Qi Zhang, Xi Chen, Ying Sun, Chen Zhu, Hengshu Zhu, Hui Xiong. A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics. arXiv preprint arXiv:2307.03195v2, 2024. [paper]

  • Xi Chen+, Chuan Qin+, Chuyu Fang, Chao Wang, Chen Zhu, Fuzhen Zhuang, Hengshu Zhu, Hui Xiong. Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS-2024), 2024. [paper]

  • Xiaoshan Yu, Chuan Qin*, Dazhong Shen, Haiping Ma*, Le Zhang, Xinyi Zhang, Hengshu Zhu, Hui Xiong. RDGT: Enhancing Group Cognitive Diagnosis with Relation-Guided Dual-Side Graph Transformer. In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2024.

  • Xiaoshan Yu, Chuan Qin*, Dazhong Shen, Shangshang Yang, Haiping Ma, Hengshu Zhu, Xingyi Zhang. RIGL: A Unified Reciprocal Approach for Tracing the Independent and Group Learning Processes. In Proceedings of the 30th SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD-2024), 2024. [paper]

  • Liyi Chen, Chuan Qin*, Ying Sun, Xin Song, Tong Xu, Hengshu Zhu, Hui Xiong*. Collaboration-Aware Hybrid Learning for Knowledge Development Prediction. In Proceedings of the Web Conference 2024 (WWW-2024), 2024. [paper]

  • Xiaoshan Yu, Chuan Qin*, Qi Zhang, Chen Zhu, Haiping Ma, Xingyi Zhang, Hengshu Zhu. DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation. In Proceedings of the IEEE International Conference on Data Mining 2024 (ICDM-2024), 2024.

  • Feihu Jiang, Chuan Qin*, Kaichun Yao, Chuyu Fang, Fuzhen Zhuang, Hengshu Zhu, Hui Xiong*. Enhancing Question Answering for Enterprise Knowledge Bases using Large Language Models. In Proceedings of the 29th International Conference on Database Systems for Advanced Applications (DASFAA-2024), 2024. [paper]

  • Feihu Jiang, Chuan Qin*, Jingshuai Zhang, Kaichun Yao, Xi Chen, Dazhong Shen, Chen Zhu, Hengshu Zhu, Hui Xiong*. Towards Efficient Resume Understanding: A Multi-Granularity Multi-Modal Pre-Training Approach. IEEE Conference on Multimedia Expo 2024 (ICME-2024), 2024. [paper]

  • Haiping Ma, Siyu Song, Chuan Qin*, Xiaoshan Yu, Limiao Zhang, Xingyi Zhang*, Hengshu Zhu. DGCD: An Adaptive Denoising GNN for Group-level Cognitive Diagnosis. In Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI-2024), 2024. [paper]

  • Haiping Ma, Yong Yang, Chuan Qin*, Xiaoshan Yu, Shangshang Yang, Xingyi Zhang*, Hengshu Zhu. HD-KT: Advancing Robust Knowledge Tracing via Anomalous Learning Interaction Detection. In Proceedings of the Web Conference 2024 (WWW-2024), 2024. [paper]

  • Dazhong Shen, Chuan Qin, Qi Zhang, Hengshu Zhu, Hui Xiong. Handling Over-Smoothing and Over-Squashing in Graph Convolution with Maximization Operation. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2024. [paper]

  • Rui Zha, Ying Sun, Chuan Qin, Le Zhang, Tong Xu, Hengshu Zhu, Enhong Chen. Towards Unified Representation Learning for Career Mobility Analysis with Trajectory Hypergraph. ACM Transactions on Information Systems (ACM TOIS), 2024. [paper]

  • Kaichun Yao, Hao Wang, Chuan Qin, Hengshu Zhu, Yanjun Wu, Libo Zhang. Unsupervised Code-Based Adversarial Attacks for Programming Language Models via Reinforcement Learning. ACM Transactions on Software Engineering and Methodology (ACM TOSEM）, 2024. [paper]

  • Xi Chen, Chuan Qin, Zhigaoyuan Wang, Yihang Cheng, Chao Wang, Hengshu Zhu, Hui Xiong. Pre-DyGAE: Pre-training Enhanced Dynamic Graph Autoencoder for Occupational Skill Demand Forecasting. In Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI-2024), 2024. [paper]

  • Xiao Han, Chen Zhu, Xiao Hu, Chuan Qin, Xiangyu Zhao, Hengshu Zhu. Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning. In Proceedings of the 30th SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD-2024), 2024. [paper]

  • Wei Wu, Chao Wang, Dazhong Shen, Chuan Qin, Liyi Chen, Hui Xiong. AFDGCF: Adaptive Feature De-correlation Graph Collaborative Filtering for Recommendations. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-2024), 2024. [paper]

  • Shasha Hu, Chao Wang, Chuan Qin, Hengshu Zhu, Hui Xiong. Super-node Generation for GNN-based Recommender Systems: Enhancing Distant Node Integration via Graph Coarsening. In Proceedings of the 29th International Conference on Database Systems for Advanced Applications (DASFAA 2024). 2024. [paper]

  • Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, Hengshu Zhu, Qi Liu, Hui Xiong, Enhong Chen, A Survey on Large Language Models for Recommendation, World Wide Web (WWWJ), 2024. [paper]

In the Year of 2023:

  • Chuan Qin, Hengshu Zhu, Dazhong Shen, Ying Sun, Kaichun Yao, Peng Wang, Hui Xiong. Automatic Skill-oriented Question Generation and Recommendation for Intelligent Job Interviews. In ACM Transactions on Information Systems (ACM TOIS), 2023. [paper]

  • Chuyu Fang+, Chuan Qin+, Qi Zhang, Kaichun Yao, Jingshuai Zhang, Hengshu Zhu, Fuzhen Zhuang, Hui Xiong. RecruitPro: A Pretrained Language Model with Skill-Aware Prompt Learning for Intelligent Recruitment. In Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD-2023), 2023. [paper]

  • Yunfei Zhang+, Chuan Qin+, Dazhong Shen, Haiping Ma, Le Zhang, Xingyi Zhang, Hengshu Zhu. ReliCD: A Reliable Cognitive Diagnosis Framework with Confidence Awareness. In proceedings of the 2023 IEEE International Conference on Data Mining (ICDM-2023), 2023. [paper]

  • Rui Zha, Chuan Qin*, Le Zhang*, Dazhong Shen, Tong Xu, Hengshu Zhu, Enhong Chen. Career Mobility Analysis with Uncertainty-aware Graph Autoencoders: A Job Title Transition Perspective. In IEEE Transactions on Computational Social Systems (TCSS), 2023. [paper]

  • Kaichun Yao, Jingshuai Zhang, Chuan Qin*, Xin Song, Peng Wang, Hengshu Zhu*, Hui Xiong. ResuFormer: Semantic Structure Understanding for Resumes via Multi-modal Pre-training. In Proceedings of the 39th IEEE International Conference on Data Engineering (ICDE-2023), 2023. [paper]

  • Chao Wang, Hengshu Zhu, Chen Zhu, Chuan Qin, Enhong Chen, Hui Xiong. SetRank: A Setwise Bayesian Approach for Collaborative Ranking in Recommender System. In ACM Transactions on Information Systems (ACM TOIS), 2023. [paper]

  • Haiping Ma, Yi Zeng, Yang Shuangshuang, Chuan Qin, Xingyi Zhang, Limiao Zhang. A Novel Computerized Adaptive Testing Framework with Decoupled Learning Selector. Complex \& Intelligent Systems, 2023. [paper]

  • Siyuan Hao, Le Dai, Le Zhang, Shengming Zhang, Chao Wang, Chuan Qin, Hui Xiong. Hybrid Heterogeneous Graph Neural Networks for Fund Performance Prediction. The 16th International Conference on Knowledge Science, Engineering and Management (KSEM 2023), 2023. [paper]

  • Shuhuan Liu, Xiaoshan Yu, Haiping Ma, Ziwen Wang, Chuan Qin, Xingyi Zhang. Homogeneous Cohort-Aware Group Cognitive Diagnosis: A Multi-grained Modeling Perspective. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM-2023), 2023. [paper]

In the Year of 2022:

  • Chuan Qin, Kaichun Yao, Hengshu Zhu, Tong Xu, Dazhong Shen, Enhong Chen, Hui Xiong. Towards Automatic Job Description Generation with Capability-Aware Neural Networks. In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2022. [paper]

  • Kaichun Yao, Jingshuai Zhang, Chuan Qin, Peng Wang, Hengshu Zhu, Hui Xiong. Knowledge Enhanced Person-Job Fit for Talent Recruitment. In Proceedings of the 38th IEEE International Conference on Data Engineering (ICDE-2022), 2022. [paper]

  • Zhe Zhang, Hui Xiong, Tong Xu, Chuan Qin, Le Zhang, Enhong Chen. Complex Attributed Network Embedding for Medical Complication Prediction. In Knowledge and Information Systems (KAIS), 2022. [paper]

  • Le Dai, Yu Yin, Chuan Qin, Enhong Chen, Hui Xiong. Decomposing Complementary and Substitutable Relations for Intercorporate Investment Recommendation. In Proceedings of the 22nd IEEE International Conference on Data Mining (ICDM-2022), 2022. [paper]

In the Year of 2021:

  • Dazhong Shen, Chuan Qin, Hengshu Zhu, Tong Xu, Enhong Chen, Hui Xiong. Joint Representation Learning with Relation-enhanced Topic Models for Intelligent Job Interview Assessment. In ACM Transactions on Information Systems (ACM TOIS), 2021. [paper]

  • Dazhong Shen, Chuan Qin, Chao Wang, Hengshu Zhu, Enhong Chen, Hui Xiong. Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-2021), 2021. [paper]

  • Dazhong Shen, Chuan Qin, Chao Wang, Zheng Dong, Hengshu Zhu, Hui Xiong. Topic Modeling Revisited: A Document Graph-based Neural Network Perspective. In Proceedings of the 35th Conference on Neural Information Processing Systems. (NeurIPS-2021), 2021. [paper]

  • Ying Sun, Hengshu Zhu, Chuan Qin, Fuzhen Zhuang, Qing He, Hui Xiong. Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation. In Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS-2021), 2021. [paper]

  • Kaichun Yao, Chuan Qin, Hengshu Zhu, Chao Ma, Jingshuai Zhang, Yi Du. Hui Xiong. An Interactive Neural Network Approach to Keyphrase Extraction in Talent Recruitment. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM-2021), 2021. [paper]

  • Miao Chen, Chao Wang, Chuan Qin, Tong Xu, Jianhui Ma, Enhong Chen, Hui Xiong. A Trend-aware Investment Target Recommendation System with Heterogeneous Graph. In Proceedings of the International Joint Conference on Neural Networks (IJCNN-2021), 2021. [paper]

  • Yuqing Zhao, Xi Zhang, Xinlin Tang, Chuan Qin, Hengshu Zhu. Embedding Fairness into the AI-Based Talent Recruitment Systems: The Perspective of Environment Cycle and Knowledge Cycle. In Proceedings of the Twenty-fifth Pacific Asia Conference on Information Systems (PACIS-2021), 2021. [paper]

In the Year of 2020:

  • Chuan Qin, Hengshu Zhu, Tong Xu, Chen Zhu, Chao Ma, Enhong Chen, Hui Xiong. An Enhanced Neural Network Approach to Person-Job Fit in Talent Recruitment. In ACM Transactions on Information Systems (ACM TOIS), 2020. [paper]

  • 秦川，祝恒书，庄福振，郭庆宇，张琦，张乐，王超，陈恩红，熊辉，基于知识图谱的推荐系统研究综述.《中国科学: 信息科学》，2020. （《中国科学：信息科学》热点论文奖） [paper]

  • Le Dai, Yu Yin, Chuan Qin, Tong Xu, Xiangnan He, Enhong Chen, Hui Xiong. Enterprise Cooperation and Competition Analysis with Sign-Oriented Preference Network. In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD-2020), 2020. [paper]

  • Le Zhang, Tong Xu, Hengshu Zhu, Chuan Qin, Qingxin Meng, Hui Xiong. Enhong Chen, Large-Scale Talent Flow Embedding for Company Competitive Analysis. In Proceedings of the 31st Web Conference (WWW-2020), 2020. [paper]

  • Chao Wang, Hengshu Zhu, Chen Zhu, Chuan Qin, Hui Xiong, SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-2020), 2020 [paper]

  • Qingyu Guo, Fuzhen Zhuang, Chuan Qin, Hengshu Zhu, Xing Xie, Hui Xiong, Qing He, A Survey on Knowledge Graph-Based Recommender Systems. In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2020. [paper]

  • Hui Zhong, Zaiyi Chen, Chuan Qin, Zai Huang, Vincent Zheng, Tong Xu, Enhong Chen, Adam Revisited: A Weighted Past Gradients Perspective, Frontiers of Computer Science (FCS), 2020. [paper]

  • 郑值，徐童，秦川，廖祥文，郑毅，刘同柱，童贵显, 基于多源情境协同感知的药品推荐. 《计算机研究与发展》, 2020.

Before 2020:

  • Chuan Qin, Hengshu Zhu, Chen Zhu, Tong Xu, Fuzhen Zhuang, Chao Ma, Jingshuai Zhang, Hui Xiong. DuerQuiz: A Personalized Question Recommender System for Intelligent Job Interview. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD-2019), 2019. [paper]

  • Le Zhang, Chen Zhu, Hengshu Zhu, Tong Xu, Enhong Chen, Chuan Qin, Hui Xiong. Large-Scale Talent Flow Forecast with Dynamic Latent Factor Model. In Proceedings of the 30th Web Conference (WWW-2019), 2019. [paper]

  • Chuan Qin, Hengshu Zhu, Tong Xu, Chen Zhu, Liang Jiang, Enhong Chen, Hui Xiong. Enhancing Person-Job Fit for Talent Recruitment: An Ability-aware Neural Network Approach. In Proceedings of the 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-2018), 2018. [paper]

  • Hongyuan Zhu, Qi Liu, Nicholas Jing Yuan, Chuan Qin, Jiawei Li, Kun Zhang, Guang Zhou, Furu Wei, Yuanchun Xu, Enhong Chen. XiaoIce Band: A Melody and Arrangement Generation Framework for PopMusic. In Proceedings of the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD-2018), 2018. (Best Student Paper Award of Research Track) [paper]

  • Linli Xu, Liang Jiang, Chuan Qin, Zhe Wang, Dongfang Du, How Images Inspire Poems: Generating Classical Chinese Poetry from Images with Memory Networks. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-2018), 2018. [paper]

  • Yanan Wang, Qi Liu, Chuan Qin, Tong Xu, Yijun Wang, Enhong Chen, and Hui Xiong. Exploiting Topic-based Adversarial Neural Network for Cross-domain Keyphrase Extraction. In Proceedings of the 18th International Conference on Data Mining (ICDM-2018), 2018. [paper]

  • Yingzi Wang, Nicholas Yuan, Yu Sun, Chuan Qin, Xing Xie. App download forecasting: an evolutionary hierarchical competition approach. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-2017), 2017. [paper]

🎖 Selected Honors and Awards

  • 2024 Outstanding Contribution Award for the Development of IEEE Standard 3154-2024.
  • 2022 Hot Paper Award of SCIENCE CHINA Information Sciences.
  • 2021 Excellence Award of the President’s Scholarship from Chinese Academy of Science.
  • 2021 Top 100 AI Rising Star of Chinese Scholars.[Link]
  • 2020 Baidu Scholarship top 20 Candidate.
  • 2020 CETC The 14th Research Institute Glarun Scholarship.
  • 2019 SIGKDD 2019 Student Travel Award.
  • 2019 Global Digital Creations Excellence Scholarship.
  • 2018 Best Student Paper Award of SIGKDD 2018 (Research Track).
  • 2018 SIGIR 2018 Student Travel Grant.
  • 2018 Guoyuan Securities Scholarship.
  • 2015-2020 UCTC First-class Scholarship (six times).
  • 2015 Microsoft Research Asia: Stars of Tomorrow Internship Award.
  • 2014 Kwang-Hua Scholarship.

📖 Educations

  • 2015.09 - 2021.06, Ph.D. in Computer Science. School of Computer Science and Technology, University of Science and Technology of China
  • 2011.09 - 2015.07, B.Eng. in Computer Science. School of Computer Science and Technology, University of Science and Technology of China

📚 Services

Journal Reviewers:

  • IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE)
  • IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS)
  • ACM Transactions on Information Systems (ACM TOIS)
  • ACM Transactions on Knowledge Discovery from Data (TKDD)
  • Frontiers of Computer Science (FCS)

Seniro Program Committee Member/Program Committee Member:

  • The ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD-2022,2023,2024,2025)
  • The International Conference on Machine Learning (ICML-2022,2023,2024,2025)
  • The ACM Web Conference (WWW-2023,2024,2025)
  • The Annual Meeting of the Association for Computational Linguistics (ACL-2023,2024,2025)
  • The International Conference on Neural Information Processing Systems (NeurlPS-2022,2023,2024)
  • The International Conference on Learning Representations (ICLR-2024,2025)
  • The International Joint Conference on Artificial Intelligence (IJCAI-2021,2022,2023,2024,2025)
  • The AAAI Conference on Artificial Intelligence (AAAI-2021,2023,2024,2025)
  • The Conference on Empirical Methods in Natural Language Processing (EMNLP-2021,2022,2023)
  • The International Conference on Computational Linguistics (COLING-2020,2022)
  • The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-2020,2021,2022,2023,2025)
  • The ACM International Conference on Information and Knowledge Management (CIKM-2023)
  • The International Conference on Web Search and Data Mining (WSDM-2022)
  • The Pacific Rim International Conference on Artificial Intelligence (PRICAI-2022,2023)
  • The International Conference on Database Systems for Advanced Applications (DASFAA-2024,2025)
  • The IEEE Conference on Multimedia Expo (ICME-2024)