Han Yu's Homepage

arXiv Preprints

L. Yi, H. Yu, C. Ren, H. Zhang, G. Wang, X. Liu & X. Li, "pFedAFM: Adaptive Feature Mixture for Batch-Level Personalization in Heterogeneous Federated Learning," arXiv preprint arXiv:2404.17847, 2024.
L. Yi, H. Yu, C. Ren, H. Zhang, G. Wang, X. Liu & X. Li, "pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning," arXiv preprint arXiv:2402.01350, 2024.
L. Yi, H. Yu, G. Wang, X. Liu & X. Li, "pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning," arXiv preprint arXiv:2310.13283, 2023.
A. Li, R. Liu, M. Hu, L. A. Tuan & H. Yu, "Towards Interpretable Federated Learning," arXiv preprint arXiv:2302.13473, 2023.
X. Guo & H. Yu, "On the Domain Adaptation and Generalization of Pretrained Language Models: A Survey," arXiv preprint arXiv:2211.03154, 2022.
S. Wang, Q. Li, L. Cui, Z. Yan, Y. Xu, Z. Shi, Z. Shen & H. Yu, "Towards AI-Empowered Crowdsourcing," arXiv preprint arXiv:2212.14676, 2022.
P. S. Kyaw & H. Yu, "Personalised Federated Learning: A Combinational Approach," arXiv preprint arXiv:2108.09618, 2021.
L. Wang, H. Yu & X. Han, "Federated Crowdsourcing: Framework and Challenges," arXiv preprint arXiv:2011.03208, 2020.
G. Li, C. Liu, H. Yu, Y. Fan, L. Zhang, Z. Wang & M. Wang, "SCNet: A Neural Network for Automated Side-Channel Attack," arXiv preprint arXiv:2008.00476, 2020.
M. Cong, X. Weng, H. Yu, J. Qu & S. M. Yiu, "Optimal Procurement Auction for Cooperative Production of Virtual Products: Vickrey-Clarke-Groves Meet Cremer-McLean," arXiv preprint arXiv:2007.14780, 2020.
C. Ju, R. Zhao, J. Sun, X. Wei, B. Zhao, Y. Liu, H. Li, T. Chen, X. Zhang, D. Gao, B. Tan, H. Yu & Y. Jin, "Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention," arXiv preprint arXiv:2006.10517, 2020.
Y. Chen, X. Yang, X. Qin, H. Yu, B. Chen & Z. Shen, "FOCUS: Dealing with Label Quality Disparity in Federated Learning," arXiv preprint arXiv:2001.11359, 2020.
S. Fauvel & H. Yu, "A Survey on Artificial Intelligence and Data Mining for MOOCs," arXiv preprint arXiv:1601.06862, 2016.
H. Yu, Z. Shen, Q. Wu & C. Miao, "Designing Socially Intelligent Virtual Companions," arXiv preprint arXiv:1411.7090, 2014.
J. Lin, H. Yu & Z. Shen, "An Empirical Analysis of Task Allocation in Scrum-based Agile Programming," arXiv preprint arXiv:1411.6201, 2014.
J. Lin, H. Yu & Z. Shen, "Identifying Talented Software Engineering Students through Data-driven Skill Assessment," arXiv preprint arXiv:1411.6197, 2014.

Books

Goebel, R., Yu, H., Faltings, B., Fan, L. & Xiong, Z. (Eds.). (2023). Trustworthy Federated Learning. Lecture Notes in Artificial Intelligence, vol. 13448, p. 158. Springer, Cham.
Yang, Q., Fan, L. & Yu, H. (Eds.). (2020). Federated Learning: Privacy and Incentive. Lecture Notes in Computer Science, vol. 12500, p. 282. Springer, Cham.
杨强、刘洋、程勇、康炎、陈天健、于涵《联邦学习》电子工业出版社，p. 208，2020.
Yang, Q., Liu, Y., Cheng, Y., Kang, Y., Chen, T. & Yu, H. (2020). Federated Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning, p. 189. Springer, Cham.

Book Chapters

Yu, H. & Tang, X. (2024). Mitigating Collusive Behaviours in Open Data Exchange Systems. In: Chellam, R. (Ed.). Artificial Intelligence Ethics & Governance Body of Knowledge, vol. 2, SCS.
Lu, S., Xing, P. & Yu, H. (2024). Graph-Aware Federated Learning. In: Federated Learning: Theory and Practice, pp. 181-197. Elsevier.
Lyu, L., Yu, H., Zhao, J. & Yang, Q. (2020). Threats to Federated Learning. In: Yang, Q., Fan, L. & Yu, H. (Eds.). Federated Learning: Privacy and Incentive, pp. 1-14. Springer, Cham.
Chen, Y., Wang, X., Qin, X., Yu, H., Chen, B. & Shen, Z. (2020). Dealing with Label Quality Disparity in Federated Learning. In: Yang, Q., Fan, L. & Yu, H. (Eds.). Federated Learning: Privacy and Incentive, pp. 106-120. Springer, Cham.
Liu, Y., Ai, Z., Sun, S., Zhang, S., Liu, Z. & Yu, H. (2020). FedCoin: A Peer-to-Peer Payment System for Federated Learning. In: Yang, Q., Fan, L. & Yu, H. (Eds.). Federated Learning: Privacy and Incentive, pp. 121-134. Springer, Cham.
Chen, Z., Liu, Z., Ng, K. L., Yu, H., Liu, Y. & Yang, Q. (2020). A Gamified Research Tool for Incentive Mechanism Design in Federated Learning. In: Yang, Q., Fan, L. & Yu, H. (Eds.). Federated Learning: Privacy and Incentive, pp. 164-171. Springer, Cham.
Lyu, L., Xu, X., Wang, Q. & Yu, H. (2020). Collaborative Fairness in Federated Learning. In: Yang, Q., Fan, L. & Yu, H. (Eds.). Federated Learning: Privacy and Incentive, pp. 185-199. Springer, Cham.
Cong, M., Yu, H., Weng, X. & Yiu, S.-M. (2020). A Game-Theoretic Framework for Incentive Mechanism Design in Federated Learning. In: Yang, Q., Fan, L. & Yu, H. (Eds.). Federated Learning: Privacy and Incentive, pp. 200-217. Springer, Cham.
Yu, H., Weng, J., Ong, Y. S. & Cong, G. (2020). Data Management. In: Chellam, R. (Ed.). Artificial Intelligence Ethics & Governance Body of Knowledge, vol. 1, SCS.
Yu, H., Miao, C., An, B., Shen, Z. & Leung, C. (2018). Making Efficient Reputation-aware Decisions in Multi-agent Systems. In: Hao, J. & Leung, H.-F. (Eds.). Interactions in Multiagent Systems, pp. 43-64. World Scientific, Singapore.
Tao, X., Shen, Z., Miao, C., Theng, Y. L., Miao, Y. & Yu, H. (2010). Automated Negotiation through a Cooperative-Competitive Model. In: Ito, T., Zhang, M., Robu, V., Fatima, S., Matsuo, T. & Yamaki, H. (Eds.). Innovations in Agent-Based Complex Automated Negotiations. Studies in Computational Intelligence, vol. 319, pp. 161-178. Springer, Berlin, Heidelberg.

International Journal Articles

Ren, C., Yu, H., Peng, H., Tang, X., Zhao, B., Yi, L., Tan, A. Z., Gao, Y., Li, A., Li, X., Li, Z. & Yang, Q. Advances and open challenges in federated foundation models. IEEE Communications Surveys and Tutorials, IEEE (2025).
Ren, C., Yan, R., Zhu, H., Yu, H., Xu, M., Shen, Y., Xu, Y., Xiao, M., Dong, Z. Y., Skoglund, M., Niyato, D. & Kwek, L. C. Towards quantum federated learning. IEEE Transactions on Neural Networks and Learning Systems, IEEE (2025).
Tang, X. & Yu, H. Towards trustworthy AI-empowered real-time bidding for online advertisement auctioning. ACM Computing Surveys, ACM (2025).
Gao, Y., Ren, C., Yu, H., Xiao, M. & Skoglund, M. Fairness-aware multi-server federated learning task delegation over wireless networks. IEEE Transactions on Network Science and Engineering, IEEE (2024).
Tang, X. & Yu, H. Fairness-aware reverse auction-based federated learning. IEEE Internet of Things Journal, IEEE (2024).
Tang, X. & Yu, H. A cost-aware utility-maximizing bidding strategy for auction-based federated learning. IEEE Transactions on Neural Networks and Learning Systems, IEEE (2024).
Li, A., Wang, G., Hu, M., Sun, J., Zhang, L., Tuan, L. A. & Yu, H. Joint client-and-sample selection for federated learning via bi-level optimization. IEEE Transactions on Mobile Computing, IEEE (2024).
Gao, Y., Ye, Z. & Yu, H. Cost-efficient computation offloading in SAGIN: A deep reinforcement learning and perception-aided approach. IEEE Journal on Selected Areas in Communications 42(12), 3462-3476, IEEE (2024).
Ren, C., Dong, Z., Yu, H., Xu, M., Xiong, Z. & Niyato, D. ESQFL: Digital twin-driven explainable and secured quantum federated learning for voltage stability assessment in smart grids. IEEE Journal of Selected Topics in Signal Processing, IEEE (2024).
Wu, X. & Yu, H. MarS-FL: Enabling competitors to collaborate in federated learning. IEEE Transactions on Big Data 10(6), 801-811, IEEE (2024).
Chen, C., Lyu, L., Yu, H. & Chen, G. Practical attribute reconstruction attack against federated learning. IEEE Transactions on Big Data 10(6), 851-863, IEEE (2024).
Xing, P., Lu, S., Wu, L. & Yu, H. BiG-Fed: Bilevel optimization enhanced graph-aided federated learning. IEEE Transactions on Big Data 10(6), 903-914, IEEE (2024).
Shi, H., Xu, Y., Jiang, Y., Yu, H. & Cui, L. Efficient asynchronous multi-participant vertical federated learning. IEEE Transactions on Big Data 10(6), 940-952, IEEE (2024).
Tan, X., Ng, W. C., Lim, W. Y. B., Xiong, Z., Niyato, D. & Yu, H. Reputation-aware federated learning client selection based on stochastic integer programming. IEEE Transactions on Big Data 10(6), 953-964, IEEE (2024).
Yao, R., Song, J., Li, Z., Yu, H., & Wang, Y. Smart meter data sharing for AI-enhanced energy systems: A review of relevant techniques and detailed case studies. IEEE Power and Energy Magazine 22(6), 42-53, IEEE (2024).
Chen, Y., Tan, A., Feng, S., Yu, H., Deng, T., Zhao, L. & Wu, F. General federated class-incremental learning with lightweight generative replay. IEEE Internet of Things Journal 11(20), 33927-33939, IEEE (2024).
Tang, X. & Yu, H. Efficient large-scale personalizable bidding for multi-agent auction-based federated learning. IEEE Internet of Things Journal 11(15), 26518-26530, IEEE (2024).
Chen, Y., Huzhang, G., Yu, Q., Sun, H., Li, H.-Y., Li, J., Ni, Y., Zeng, A., Yu, H. & Zhou, Z. Learning personalizable clustered embedding for recommender systems. ACM Transactions on Recommender Systems, ACM (2024).
Shi, Y., Yu, H. & Leung, C. Towards fairness-aware federated learning. IEEE Transactions on Neural Networks and Learning Systems 35(9), 11922-11938, IEEE (2024).
Lyu, L., Yu, H., Ma, X., Chen, C., Sun, L., Zhao, J., Yang, Q. & Yu, P. S. Privacy and robustness in federated learning: Attacks and defenses. IEEE Transactions on Neural Networks and Learning Systems 35(7), 8726-8746, IEEE (2024). (Highly Cited Paper)
Li, A., Chen, Y., Zhang, J., Cheng, M., Huang, Y., Wu, Y., Luu, A. T. & Yu, H. Historical embedding-guided efficient large-scale federated graph learning. Proceedings of the ACM on Management of Data 2(3), 144:1-144:24, ACM (2024).
Yi, L., Shi, X., Wang, N., Wang, G., Liu, X., Shi, Z. & Yu, H. pFedKT: Personalized federated learning with dual knowledge transfer. Knowledge-Based Systems, Elsevier (2024).
Li, Q., Feng, B., Tang, X., Yu, H. & Song, H. MuLAN: Multi-level attention-enhanced matching network for few-shot knowledge graph completion. Neural Networks, Elsevier (2024).
Liu, R., Xing, P., Deng, Z., Li, A., Guan, C. & Yu, H. Federated graph neural networks: Overview, techniques and challenges. IEEE Transactions on Neural Networks and Learning Systems, IEEE (2024).
Liu, R., Chen, Y., Li, A., Ding, Y., Yu, H. & Guan, G. Aggregating intrinsic information to enhance BCI performance through federated learning. Neural Networks 172, Elsevier (2024).
Liu, S., You, L., Zhu, R., Liu, B., Liu, R., Yu, H. & Yuen, C. AFM3D: An asynchronous federated meta-learning framework for driver distraction detection. IEEE Transactions on Intelligent Transportation Systems, IEEE (2024).
Ren, C., Yan, R., Xu, M., Yu, H., Xu, Y., Niyato, D. & Dong, Z. Y. QFDSA: A quantum-secured federated learning system for smart grid dynamic security assessment. IEEE Internet of Things Journal 11(5), 8414-8426, IEEE (2024).
Ren, C., Yu, H., Yan, R., Li, Q., Xu, Y., Niyato, D. & Dong, Z. Y. SecFedSA: A secure differential privacy-based federated learning approach for smart cyber-physical grid stability assessment. IEEE Internet of Things Journal 11(4), 5578-5588, IEEE (2024).
Kaewpuang, R., Xu, M., Lim, W. Y. B., Niyato, D., Yu, H., Kang, J. & Shen, X. Cooperative resource management in quantum key distribution networks for semantic communication. IEEE Internet of Things Journal 11(3), 4454-4469, IEEE (2024).
Feng, S., Yu, H. & Zhu, Y. MMVFL: A simple vertical federated learning framework for multi-class multi-participant scenarios. Sensors, MDPI (2024).
Xu, H., Che, M., Say, S. Y. A., Yu, H., Zhou, Q., Shu, J., Sun, W. & Luo, X. Investigating customers' continuous trust towards mobile banking apps. Humanities and Social Sciences Communications, SpringerNature (2023).
Tan, A. Z., Yu, H., Cui, L. & Yang, Q. Towards personalized federated learning. IEEE Transactions on Neural Networks and Learning Systems 34(12), 9587-9603, IEEE (2023). (Highly Cited Paper)
Li, A., Huang, J., Jia, J., Peng, H., Zhang, L., Tuan, L. A., Yu, H. & Li, X.-Y. Efficient and privacy-preserving feature importance-based vertical federated learning. IEEE Transactions on Mobile Computing, doi:10.1109/TMC.2023.3333879, IEEE (2023).
Li, A., Cao, Y., Guo, J., Peng, H., Guo, Q. & Yu, H. FedCSS: Joint client-and-sample selection for hard sample-aware noise-robust federated learning. Proceedings of the ACM on Management of Data 1(3), 212:1- 212:24, ACM (2023).
Ren, C., Zou, C., Xiong, Z., Yu, H., Dong, Z. Y. & Niyato, D. Achieving 500x acceleration for adversarial robustness verification of tree-based smart grid dynamic security assessment. IEEE/CAA Journal of Automatica Sinica, IEEE (2023).
Guo, Y., Liu, W., Lu, Y., Nie, J., Lyu, L., Xiong, Z., Kang, J., Yu, H. & Niyato, D. Haze visibility enhancement for promoting traffic situational awareness in vision-enabled intelligent transportation. IEEE Transactions on Vehicular Technology, IEEE (2023).
Liu, C. & Yu, H. AI-empowered persuasive video generation: A survey. ACM Computing Surveys 55(13), 285:1-285:31, ACM (2023).
Ren, C., Yu, H., Xu, Y. & Dong, Z. Y. Understanding discrepancy of power system dynamic security assessment with unknown faults: A reliable transfer learning-based method. CSEE Journal of Power and Energy Systems, CSEE (2023).
Ren, C., Wang, T., Yu, H., Xu, Y. & Dong, Z. Y. EFedDSA: An efficient differential privacy-based horizontal federated learning approach for smart grid dynamic security assessment. IEEE Journal on Emerging and Selected Topics in Circuits and Systems 13(3), 817-828, IEEE (2023).
Wang, J., Shi, Y., Yu, H., Yan, Z. , Li, H. & Chen, Z. A novel KG-based recommendation model via relation-aware attentional GCN. Knowledge-Based Systems 275, doi:10.1016/j.knosys.2023.110702, Elsevier (2023).
Bian, H., Tian, J., Yu, J. & Yu, H. Bayesian co-evolutionary optimization based entropy search for high-dimensional many-objective optimization. Knowledge-Based Systems 274, doi:10.1016/j.knosys.2023.110630, Elsevier (2023).
Li, Q., Yao, J., Tang, X., Yu, H., Jiang, S., Yang, H. & Song, H. Capsule neural tensor networks with multi-aspect information for few-shot knowledge graph completion. Neural Networks 164, 323-334, Elsevier (2023).
Kaewpuang, R., Sawadsitang, S., Niyato, D. & Yu, H. Evolutionary carrier selection for shared truck delivery services. IEEE Transactions on Vehicular Technology 72(5), 6778-6782, IEEE (2023).
Yi, C., Chen, H., Xu, Y., Chen, H., Liu, Y., Tan, H., Yan, Y. & Yu, H. Multi-component adversarial domain adaptation: A general framework. IEEE Transactions on Neural Networks and Learning Systems 34(10), 6824-6838, IEEE (2023).
Liu, Z., Chen, Y., Zhao, Y., Yu, H., Liu, Y., Bao, R., Jiang, J., Nie, Z., Xu, Q. & Yang, Q. CAreFL: Enhancing smart healthcare with contribution-aware federated learning. AI Magazine, doi:10.1002/aaai.12082, AAAI Press (2023).
Guo, X., Wang, S., Zhao, H., Diao, S., Chen, J., Ding, Z., He, Z., Lu, J., Xiao, Y., Long, B., Yu, H. & Wu, L. Intelligent online selling point extraction and generation for e-commerce recommendation. AI Magazine, doi:10.1002/aaai.12083, AAAI Press (2023).
Zou, Y., Zhang, X., Zhou, J., Diao, S., Chen, J., Ding, Z., He, Z., He, X., Xiao, Y., Long, B., Ma, M., Xu, S., Yu, H. & Wu, L. Automatic product copywriting for e-commerce. AI Magazine, doi:10.1002/aaai.12084, AAAI Press (2023).
Zhang, J. & Yu, H. EID: Facilitating explainable AI design discussions in team-based settings. International Journal of Crowd Science, 7(2), 47-54, Tsinghua University Press (2023).
Zhang, J., Shu, Y. & Yu, H. Fairness in Design: A framework for facilitating ethical AI designs. International Journal of Crowd Science 7(1), 32-39, Tsinghua University Press (2023). (Excellent Paper Award)
Wang, T., Yang, H., Liu, Y., Yu, H. & Song, H. A multimodal approach for improving market price estimation in online advertising. Knowledge-Based Systems, doi:10.1016/j.knosys.2023.110392, Elsevier (2023).
Ngoenriang, N., Xu, M., Kang, J., Niyato, D., Yu, H., Shen, X. S. DQC²O: Distributed quantum computing for collaborative optimization in future networks. IEEE Communications Magazine, IEEE (2023).
Wang, J., Shi, Y., Yu, H., Zhang, K., Wang, X., Yan, Z. & Li, H. Temporal density-aware sequential recommendation networks with contrastive learning. Expert Systems with Applications 211, doi:10.1016/j.eswa.2022.118563, Elsevier (2023).
Cheng, L., Shi, Y., Li, L., Yu, H., Wang, X. & Yan, Z. KLECA: Knowledge-level-evolution and category-aware personalized knowledge recommendation. Knowledge and Information Systems, Springer (2022).
Feng, S., Li, B., Yu, H., Liu, Y. & Yang, Q. Semi-supervised federated heterogeneous transfer learning. Knowledge-Based Systems 252, doi:10.1016/j.knosys.2022.109384, Elsevier (2022).
Yang, H., Jiang, S., Shi, Y., Li, Q., Tang, X., Yu, H. & Song, H. Kaplan-Meier Markov network: Learning the distribution of market price by censored data in online advertising. Knowledge-Based Systems 251, doi:10.1016/j.knosys.2022.109248, Elsevier (2022).
Xie, Y.-A., Kang, J., Niyato, D., Van, N. T. T., Luong, N. C., Liu, Z. & Yu, H. Securing federated learning: A covert communication-based approach. IEEE Network, IEEE (2022).
Liu, R. W., Liang, M., Nie, J., Yuan, Y., Xiong, Z., Yu, H. & Guizani, N. STMGCN: Mobile edge computing-empowered vessel trajectory prediction using spatio-temporal multi-graph convolutional network. IEEE Transactions on Industrial Informatics 18(11), 7977-7987, IEEE (2022). (Highly Cited Paper)
Liu, R. W., Guo, Y., Nie, J., Hu, Q., Xiong, Z., Yu, H. & Guizani, M. Intelligent edge-enabled efficient multi-source data fusion for autonomous surface vehicles in maritime Internet of Things. IEEE Transactions on Green Communications and Networking, doi:10.1109/TGCN.2022.3158004, IEEE (2022).
Liu, Z., Chen, Y., Yu, H., Liu, Y. & Cui, L. GTG-Shapley: Efficient and accurate participant contribution evaluation in federated learning. ACM Transactions on Intelligent Systems and Technology 13(4), 60:1-60:21, ACM (2022).
Guo, X., Yu, H., Li, B., Wang, H., Xing, P., Feng, S., Nie, Z. & Miao, C. Federated learning for personalized humor recognition. ACM Transactions on Intelligent Systems and Technology 13(4), 68:1-68:18, ACM (2022). (PREMIA Certificate of Commendation)
Zhang, Y., Wang, J., Chen, Y., Yu, H. & Qin, T. Adaptive memory networks with self-supervised learning for unsupervised anomaly detection. IEEE Transactions on Knowledge and Data Engineering, doi:10.1109/TKDE.2021.3139916, IEEE (2022).
Hu, C., Chen, Y., Hu, L., Yu, H. & Lu, D. Disagreement-based class incremental random forest for sensor-based activity recognition. Knowledge-Based Systems 239, doi:10.1016/j.knosys.2021.108044, Elsevier (2022).
Liu, Y., Huang, A., Luo, Y., Huang, H., Liu, Y., Chen, Y., Feng, L., Chen, T., Yu, H. & Yang, Q. Federated learning-powered visual object detection for safety monitoring. AI Magazine 42(2), 19-27, AAAI Press (2021).
Zheng, Y., Yu, H., Shi, Y., Zhang, K., Zhen, S., Cui, L., Leung, C. & Miao, C. Optimizing smart grid operations from the demand side. AI Magazine 42(2), 28-37, AAAI Press (2021).
Zeng, A., Yu, H., Da, Q., Zhan, Y., Yu, Y., Zhou, J. & Miao, C. Improving search engine efficiency through contextual factor selection. AI Magazine 42(2), 50-58, AAAI Press (2021).
Guo, S., Zhang, T., Xu, G., Yu, H., Xiang, T. & Liu, Y. Byzantine-resilient decentralized stochastic gradient descent. IEEE Transactions on Circuits and Systems for Video Technology 32(6), 4096-4106, IEEE (2021).
Liu, Y., Zou, X. & Yu, H. 3R Model: A post-purchase context-aware reputation model to mitigate unfair ratings in e-commerce. Knowledge-Based Systems 231, doi:10.1016/j.knosys.2021.107441, Elsevier (2021).
Guo, S., Zhang, T., Xu, G., Yu, H., Xiang, T. & Liu, Y. Topology-aware differential privacy for decentralized image classification. IEEE Transactions on Circuits and Systems for Video Technology 32(6), 4016-4027, IEEE (2021).
Huzhang, G., Pang, Z.-J., Gao, Y., Liu, Y., Shen, W., Zhou, W.-J., Lin, Q., Da, Q., Zeng, A.-X., Yu, H., Yu, Y. & Zhou, Z.-H. AliExpress Learning-To-Rank: Maximizing online model performance without going online. IEEE Transactions on Knowledge and Data Engineering, doi:10.1109/TKDE.2021.3098898, IEEE (2021).
Kairouz, P., McMahan, H. B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A. N., Bonawitz, K., Charles, Z., Cormode, G., Cummings, R., D'Oliveira, R. G. L., Rouayheb, S. E., Evans, D., Gardner, J., Garrett, Z., Gascon, A., Ghazi, B., Gibbons, P. B., Gruteser, M., Harchaoui, Z., He, C., He, L., Huo, Z., Hutchinson, B., Hsu, J., Jaggi, M., Javidi, T., Joshi, G., Khodak, M., Konecny, J., Korolova, A., Koushanfar, F., Koyejo, S., Lepoint, T., Liu, Y., Mittal, P., Mohri, M., Nock, R., Ozgur, A., Pagh, R., Raykova, M., Qi, H., Ramage, D., Raskar, R., Song, D., Song, W., Stich, S. U., Sun, Z., Suresh, A. T., Tramer, F., Vepakomma, P., Wang, J., Xiong, L., Xu, Z., Yang, Q., Yu, F. X., Yu, H. & Zhao, S. Advances and open problems in federated learning. Foundations and Trends in Machine Learning 14(1-2), 1-210, Now Publishers (2021).
Yang, H., Wang, T., Tang, X., Yu, H., Liu, F. & Song, H. Dynamically optimizing display advertising profits under diverse budget settings. IEEE Transactions on Knowledge and Data Engineering, doi:10.1109/TKDE.2021.3077699, IEEE (2021).
Lei, M., Li, J., Li, M., Zou, L. & Yu, H. An improved UNet++ model for congestive heart failure diagnosis using short-term RR intervals. Diagnostics 11(3), doi:10.3390/diagnostics11030534, MDPI (2021).
Lei, M., Rao, Z., Wang, H., Chen, Y., Zou, L. & Yu, H. Maceral groups analysis of coal based on sematic segmentation of photomicrographs via the improved U-net. Fuel 294, doi:10.1016/j.fuel.2021.120475, Elsevier (2021).
Zhou, Q., Lim, F. J., Yu, H., Xu, G., Ren, X., Liu, D., Wang, X., Mai, X. & Xu, H. A study on factors affecting service quality and loyalty intention in mobile banking. Journal of Retailing and Consumer Services 60, doi:10.1016/j.jretconser.2020.102424, Elsevier (2021).
Yin, X., Huang, J., He, W., Guo, W., Yu, H. & Cui, L. Group task allocation approach for heterogeneous software crowdsourcing tasks. Peer-to-Peer Networking and Applications, doi:10.1007/s12083-020-01000-6, Springer (2020).
Yi, C., Xu, Y., Yu, H., Yan, Y. & Liu, Y. Multi-component transfer metric learning for handling unrelated source domain samples. Knowledge-Based Systems 203, doi:10.1016/j.knosys.2020.106132, Elsevier (2020).
Lyu, L., Yu, J., Nandakumar, K., Li, Y., Ma, X., Jin, J., Yu, H. & Ng, K. S. Towards fair and privacy-preserving federated deep models. IEEE Transactions on Parallel and Distributed Systems 31(11), 2524-2541, IEEE (2020).
Zou, L., Yu, X., Li, M., Lei, M. & Yu, H. Nondestructive identification of coal and gangue via near-infrared spectroscopy based on improved broad learning. IEEE Transactions on Instrumentation and Measurement 69(10), 8043-8052, IEEE (2020).
Yu, H., Liu, Z., Liu, Y., Chen, T., Cong, M., Weng, X., Niyato, D. & Yang, Q. A sustainable incentive scheme for federated learning. IEEE Intelligent Systems 35(4), 58-69, IEEE (2020).
Feng, S., Yu, H. & Duarte, M. F. Autoencoder based sample selection for self-taught learning. Knowledge-Based Systems 192, doi:10.1016/j.knosys.2019.105343, Elsevier (2020).
Wang, J., Chen, Y., Feng, W., Yu, H., Huang, M. & Yang, Q. Transfer learning with dynamic distribution adaptation. ACM Transactions on Intelligent Systems and Technology 11(1), 6:1-6:25, ACM (2020). (Highly Cited Paper)
Zheng, Y., Yu, H., Cui, L., Miao, C., Leung, C., Liu, Y. & Yang, Q. Addressing the challenges of government service provision with AI. AI Magazine 41(1), 33-43, AAAI Press (2020).
Guo, X., Yu, H., Chen, Y. & Miao, C. Weakly supervised neural representation learning through exploiting expert knowledge. International Journal of Information Technology 25(1), 1-9, Singapore Computer Society (2019).
Chen, Y., Wang, J., Huang, M. & Yu, H. Cross-position activity recognition with stratified transfer learning. Pervasive and Mobile Computing 57, 1-13, Elsevier (2019).
Wang, T., Yang, H., Yu, H., Zhou, W., Liu, Y. & Song, H. A revenue-maximizing bidding strategy for demand-side platforms. IEEE Access 7(1), 68692-68706, IEEE (2019).
Yu, H. Ethics and AI: Teaching our machines to tell right from wrong. The IT Society 1, 2-3, Singapore Computer Society (2019).
Hu, C., Chen, Y., Peng, X., Yu, H., Gao, C. & Hu, L. A novel incremental feature learning method for sensor-based activity recognition. IEEE Transactions on Knowledge and Data Engineering 31(6), 1038-1050, IEEE (2019).
Wang, W., Zheng, V. W., Yu, H. & Miao, C. A survey of zero-shot learning: Settings, methods and applications. ACM Transactions on Intelligent Systems and Technology 10(2), 13:1-13:19, ACM (2019).
Jiang, S., Xu, Y., Wang, T., Yang, H., Qiu, S., Yu, H. & Song, H. Multi-label metric transfer learning jointly considering instance space and label space distribution divergence. IEEE Access 7(1), 10362-10373, IEEE (2019).
Deng, Z., Zhang, J. & Yu, H. A survey of ethics in resource allocation and crowdsourcing. International Journal of Information Technology 24(2), 1-17, Singapore Computer Society (2018).
Guo, X., Yu, H. & Chen, Y. Building a smart assistant for improving chronic pain management in primary care. International Journal of Information Technology 24(2), 1-16, Singapore Computer Society (2018).
Miao, C., Zeng, Z., Wu, Q., Yu, H. & Leung, C. Humanized artificial intelligence: What, why and how. International Journal of Information Technology 24(2), 1-21, Singapore Computer Society (2018).
Chen, Y., Hu, C., Hu, B., Hu, L., Yu, H. & Miao, C. Inferring cognitive abilities from motor patterns. IEEE Transactions on Knowledge and Data Engineering 30(12), 2340-2353, IEEE (2018).
Lin, J., Yu, H., Pan Z., Shen, Z. & Cui, L. Towards data-driven software engineering skills assessment. International Journal of Crowd Science 2(2), 123-135, Emerald (2018).
Shen, Z., Yu, H., Yu, L., Miao, C., Chen, Y. & Lesser, V. R. Dynamic generation of Internet of Things organizational structures through evolutionary computing. IEEE Internet of Things Journal 5(2), 943-954, IEEE (2018).
Yu, H., Miao, C., Leung, C. & White, T. J. Towards AI-powered personalization in MOOC learning. npj Science of Learning 2(15), doi:10.1038/s41539-017-0016-3, Nature Publishing Group (2017).
Yu, H., Miao, C., Chen, Y., Fauvel, S., Li, X. & Lesser, V. R. Algorithmic management for improving the collective productivity in crowdsourcing. Scientific Reports 7(12541), doi:10.1038/s41598-017-12757-x, Nature Publishing Group (2017).
Cui, L., Zhao, X., Liu, L., Yu, H. & Miao, Y. Complex crowdsourcing task allocation strategies employing supervised and reinforcement learning. International Journal of Crowd Science 1(2), 146-160, Emerald (2017).
Yu, H., Shen, Z., Miao, C., Leung, C., Chen, Y., Fauvel, S., Lin, J., Cui, L., Pan, Z. & Yang, Q. A dataset of human decision-making in teamwork management. Scientific Data 4(160127), doi:10.1038/sdata.2016.127, Nature Publishing Group (2017).
Mei, J.-P., Yu, H., Shen, Z. & Miao, C. A social influence based trust model for recommender systems. Intelligent Data Analysis 22(2), IOS Press (2017).
Yu, H., Miao, C., Leung, C., Chen, Y., Fauvel, S., Lesser, V. R. & Yang, Q. Mitigating herding in hierarchical crowdsourcing networks. Scientific Reports 6(4), doi:10.1038/s41598-016-0011-6, Nature Publishing Group (2016).
Zhang, W., Shi, Y., Liu, L., Zhang, S., Zheng, Y., Cui, L. & Yu, H. CTP: A scheduling strategy to smooth response time fluctuations in multi-tier website system. Microprocessors and Microsystems 47(A), 198-208, Elsevier (2016).
Shi, Y., Zhang, K., Cui, L., Liu, L., Zheng, Y., Zhang, S. & Yu, H. MapReduce short jobs optimization based on resource reuse. Microprocessors and Microsystems 47(A), 178-187, Elsevier (2016).
Miao, C. Yu, H., Shen, Z. & Leung, C. Balancing quality and budget considerations in mobile crowdsourcing. Decision Support Systems 90, 56-64, Elsevier (2016).
Lin, J., Yu, H. & Shen, Z. Using Goal Net to model user stories in agile software development. International Journal of Information Technology 21(2), 1-17, Singapore Computer Society (2015).
Yu, H., Shen, Z., Miao, C., An, B. & Leung, C. Filtering trust opinions through reinforcement learning. Decision Support Systems 66, 102-113, Elsevier (2014).
Yu, H., Shen, Z., Leung, C., Miao, C. & Lesser, V. R. A survey of multi-agent trust management systems. IEEE Access 1(1), 35-50, IEEE (2013).
Yu, H., Shen, Z. & Miao, C. Towards health care service ecosystem management for the elderly. International Journal of Information Technology 19(2), 1-16, Singapore Computer Society (2013).
Ji, J., Yu, H., Li, B., Shen, Z. & Miao, C. Learning Chinese characters with gestures. International Journal of Information Technology 19(1), 1-11, Singapore Computer Society (2013).
Cheng, P., Yu, H., Shen, Z. & Liu, Z. An interactive 3D product design tool for mobile pre-commerce environments. International Journal of Information Technology 18(2), 1-9, Singapore Computer Society (2012).
Leung, C., Miao, C., Yu, H. & Helander, M. Towards an ageless computing ecosystem. International Journal of Information Technology 18(1), 1-20, Singapore Computer Society (2012).
Shen, Z., Yu, H., Miao, C. & Weng, J. Trust-based web-service selection in virtual communities. Web Intelligence and Agent Systems 9(3), 227-238, IOS Press (2011).
Pan, L, Meng, M., Shen, Z. & Yu, H. A reputation-based trust aware web service interaction pattern for manufacturing grids. International Journal of Information Technology 17(1), 1-8, Singapore Computer Society (2011).
Yu, H., Shen, Z., Miao, C., Leung, C. & Niyato, D. A survey of trust and reputation management systems in wireless communications. Proceedings of the IEEE 98(10), 1755-1772, IEEE (2010). (Highly Cited Paper)
Yu, H., Shen, Z. & Leung, C. Towards trust-aware health monitoring body area sensor networks. International Journal of Information Technology 16(2), 1-20, Singapore Computer Society (2010). (Best Student Paper Award)
Qin, T., Yu, H., Leung, C., Shen, Z. & Miao, C. Towards a trust aware cognitive radio architecture. ACM SIGMOBILE Mobile Computing and Communications Review 13(2), 86-95, ACM (2009).
Yu, H., Shen, Z. & Miao, C. A goal oriented development tool to automate the incorporation of intelligent agents into interactive digital media applications. ACM Computers in Entertainment 6(2), 24:1-24:15, ACM (2008).

International Conference Publications

X. Tang & H. Yu, "Reputation-aware Revenue Allocation for Auction-based Federated Learning," in Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI-25), 2025.
L. Yi, H. Yu, C. Ren, G. Wang, X. Liu & X. Li, "pFedES: Generalized Proxy Feature Extractor Sharing for Model Heterogeneous Personalized Federated Learning," in Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI-25), 2025.
X. Guo, K. Yu, L. Cui, H. Yu & X. Li, "Federated Causally Invariant Feature Learning," in Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI-25), 2025.
Q. Ye, G. Yu, J. Liu, E. Chen, C. Dong, X. Lin, Z. Liu, H. Yu & T. Ruan, "IMQC: A Large Language Model Platform for Medical Quality Control," in Proceedings of the 37th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-25), 2025. (Innovative Application of AI Award)
L. Yi, H. Yu, C. Ren, G. Wang, X. Liu & X. Li, "Federated Model Heterogeneous Matryoshka Representation Learning," in Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS'24), 2024.
M. Chen, X. Wu, X. Tang, T. He, Y.-S. Ong, Q. Liu, Q. Lao & H. Yu, "Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning," in Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS'24), 2024.
X. Tang, H. Yu, X. Li & S. Kraus, "Intelligent Agents for Auction-based Federated Learning: A Survey," in Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), pp. 8253-8261, 2024.
X. Tang, H. Yu, Z. Li & X. Li, "A Bias-Free Revenue-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning," in Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), pp. 4991-4999, 2024.
X. Tang, H. Yu, R. Tang, C. Ren, A. Li & X. Li, "Dual Calibration-based Personalised Federated Learning," in Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), pp. 4982-4990, 2024.
L. Yi, H. Yu, Z. Shi, G. Wang, X. Liu, L. Cui & X. Li, "FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning," in Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), pp. 5371-5379, 2024.
X. Guo, K. Yu, H. Wang, L. Cui, H. Yu & X. Li, "Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection," in Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), pp. 4071-4079, 2024.
H. Peng, H. Yu, X. Tang & X. Li, "FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler," in Proceedings of the 41st International Conference on Machine Learning (ICML'24), pp. 40331-40346, 2024.
P. Xing, S. Lu & H. Yu, "Federated Neuro-Symbolic Learning," in Proceedings of the 41st International Conference on Machine Learning (ICML'24), pp. 54635-54655, 2024.
J. Zhang, Q. Yu, Y. Chen, G. Zhou, Y. Sun, C. Liang, Y. Liu, G. Huzhang, Y. Ni, A. Zeng & H. Yu, "An E-Commerce Dataset Revealing Variations during Sales," in Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'24), pp. 1162-1171, 2024.
A. Z. Tan, S. Feng & H. Yu, "FL-CLIP: Bridging Plasticity and Stability in Pre-Trained Federated Class-Incremental Learning Models," in Proceedings of the 2024 IEEE International Conference on Multimedia and Expo (ICME'24), 2024.
Y. Gao, Z. Hou, C. Yang, Z. Li, H. Yu & X. Li, "The Prospect of Enhancing Large-Scale Heterogeneous Federated Learning with Foundation Models," in Proceedings of the 2024 IEEE International Conference on Multimedia and Expo (ICME'24), 2024.
X. Tang, H. Yu & X. Li, "Agent-oriented Joint Decision Support for Data Owners in Auction-based Federated Learning," in Proceedings of the 2024 IEEE International Conference on Multimedia and Expo (ICME'24), 2024.
Q. Li, X. Tang, S. Zhou, H. Yu, H. Song, L. Cui & X. Li, "FedRMS: Privacy-Preserving Federated Knowledge Graph Embedding through Randomization," in Proceedings of the 2024 IEEE International Conference on Multimedia and Expo (ICME'24), 2024.
Z. Xiong, Y. Zhang, Z. Shen, P. Ren & H. Yu, "Multi-modal Learnable Queries for Image Aesthetics Assessment," in Proceedings of the 2024 IEEE International Conference on Multimedia and Expo (ICME'24), 2024.
Y. Zhao, S. Zhou, Y. Gao & H. Yu, "A Fair Incentive Mechanism for Federated Auctioning Networks," in Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN'24), 2024.
X. Tang & H. Yu, "Multi-Session Multi-Objective Budget Optimization for Auction-Based Federated Learning," in Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN'24), 2024.
X. Tan & H. Yu, "Hire When You Need to: Gradual Participant Recruitment for Auction-Based Federated Learning," in Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN'24), 2024.
Q. Li, J. Chen, X. Tang, H. Yu & H. Song, "Modeling Time Decay Effect in Temporal Knowledge Graphs via Multivariate Hawkes Process," in Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN'24), 2024.
A. Li, Y. Chen, M. Cheng, Y. Huang, J. Zhang, Y. Wu, A. T. Luu & H. Yu, "Historical Embedding-Guided Efficient Large-Scale Federated Graph Learning," the 2024 ACM SIGMOD/PODS International Conference on Management of Data (SIGMOD'24), 2024.
A. Li, Y. Cao, J. Guo, H. Peng, Q. Guo & H. Yu, "FedCSS: Joint Client-and-Sample Selection for Hard Sample-Aware Noise-Robust Federated Learning," the 2024 ACM SIGMOD/PODS International Conference on Management of Data (SIGMOD'24), 2024.
C. Ren, M. Xu, H. Yu, Z. Xiong, Z. Zhang & D. Niyato "Variational Quantum Circuit and Quantum Key Distribution-based Quantum Federated Learning: A Case of Smart Grid Dynamic Security Assessment," in Proceedings of the 2024 IEEE International Conference on Communications (ICC'24), 2024.
I. King, G. Long, Z. Xu & H. Yu, "FL@FM-TheWebConf'24: International Workshop on Federated Foundation Models for the Web," in Companion Proceedings of the ACM on Web Conference 2024 (WWW Companion'24), pp. 1546-1547, 2024.
Y. Shi & H. Yu, "Fairness-Aware Job Scheduling for Multi-Job Federated Learning," in Proceedings of the 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'24), 2024.
Z. Deng & H. Yu, "Noise-Resistant Graph Neural Network for Node Classification," in Proceedings of the 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'24), 2024.
Z. Xiong, Y. Zhang, Z. Shen, P. Ren & H. Yu, "Image Aesthetics Assessment via Learnable Queries," in Proceedings of the 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'24), 2024.
Y. Zhang & H. Yu, "LR-XFL: Logical Reasoning-based Explainable Federated Learning," in Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), pp. 21788-21796, 2024.
S. Tan, H. Cheng, X. Wu, H. Yu, T. He, Y.-S. Ong, C. Wang & X. Tao, "FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants," in Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), pp. 15231-15239, 2024.
C. Su, G. Yu, J. Wang, H. Li, Q. Li & H. Yu, "Multi-dimensional Fair Federated Learning," in Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), pp. 22770-22778, 2024.
C. Liu, P. Hou, A. Zeng & H. Yu, "Transformer-empowered Multi-modal Item Embedding for Enhanced Image Search in E-Commerce," in Proceedings of the 36th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-24), pp. 22770-22778, 2024. (Innovative Application of AI Award)
H. Sun, X. Tang, C. Yang, Z. Yu，X. Wang, Q. Ding, Z. Li & H. Yu, "HiFi-Gas: Hierarchical Federated Learning Incentive Mechanism Enhanced Gas Usage Estimation," in Proceedings of the 36th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-24), pp. 22824-22832, 2024. (Innovative Application of AI Award)
Y. Shi, L. Cheng, C. Jiang, H. Zhang, G. Li, X. Tang, H. Yu, Z. Shen & C. Leung, "IBCA: An Intelligent Platform for Social Insurance Benefit Qualification Status Assessment," in Proceedings of the 36th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-24), pp. 22815-22823, 2024. (Innovative Application of AI Award)
W. Lu, J. Wang, H. Yu, L. Huang, X. Zhang, Y. Chen & X. Xie, "FIXED: Frustratingly Easy Domain Generalization with Mixup," in Proceedings of the 2024 Conference on Parsimony and Learning (CPAL'24), 2024.
Y. Chen, A. Zeng, Q. Yu, K. Zhang, Y. Cao, K. Wu, G. Huzhang, H. Yu & Z. Zhou, "Recurrent Temporal Revision Graph Networks," in Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS'23), 2023.
K. Hu, R. Liu & H. Yu, "Horizontal Federated Learning for Brain-Computer Interface," in Proceedings of the 5th Distributed Artificial Intelligence Conference (DAI'23), 2023.
L. Yi, G. Wang, X. Liu, Z. Shi & H. Yu, "FedGH: Heterogeneous Federated Learning with Generalized Global Header," in Proceedings of the 31st ACM Multimedia Conference (ACM MM'23), pp. 8686-8696, 2023.
Z. Ye, Y. Gao, Y. Xiao, M. Xu, H. Yu & D. Niyato, "Smart Healthcare with Hybrid Mobile Edge-Quantum Computing: Dynamic Computation Offloading for Latency Improvement," in Proceedings of the IEEE 98th Vehicular Technology Conference (VTC'23-Fall), 2023.
Y. Ma, Y. Chen, H. Yu, Y. Gu, S. Wen & S. Guo, "Letting Go of Self-Domain Awareness: Multi-Source Domain-Adversarial Generalization via Dynamic Domain-Weighted Contrastive Transfer Learning," in Proceedings of the 26th European Conference on Artificial Intelligence (ECAI'23), 2023.
X. Tang & H. Yu, "Competitive-Cooperative Multi-Agent Reinforcement Learning for Auction-based Federated Learning," in Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), pp. 4262-4270, 2023. (KDDSG23 Best Poster Runner-Up Award)
Y. Chen, Z. Chen, P. Wu & H. Yu, "FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning," in Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), pp. 3541-3549, 2023.
J. Wang, Y. Shi, H. Yu, X. Wang, Z. Yan & F. Kong, "Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation," in Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'23), pp. 372-382, 2023.
Y. Shi, Z. Liu, Z. Shi & H. Yu, "Fairness-Aware Client Selection for Federated Learning," in Proceedings of the 2023 IEEE International Conference on Multimedia and Expo (ICME'23), pp. 324-329, 2023. (KDDSG23 Best Poster Award)
X. Tang & H. Yu, "Utility-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning," in Proceedings of the 2023 IEEE International Conference on Multimedia and Expo (ICME'23), pp. 330-335, 2023.
Z. Xiong, H. Yu & Z. Shen, "Federated Learning-based Personalized Image Aesthetics Assessment," in Proceedings of the 2023 IEEE International Conference on Multimedia and Expo (ICME'23), pp. 336-341, 2023.
Y. Gao, Y. Zhao & H. Yu, "Multi-Tier Client Selection for Mobile Federated Learning Networks," in Proceedings of the 2023 IEEE International Conference on Multimedia and Expo (ICME'23), pp. 666-671, 2023.
R. Kaewpuang, M. Xu, S. J. Turner, D. Niyato, H. Yu & D. I. Kim, "Entangled Pair Resource Allocation under Uncertain Fidelity Requirements," in Proceedings of the 31st Biennial Symposium on Communications (BSC'23), 2023.
Z. Shi, Z. Yao, L. Yi, H. Yu, L. Zhang & X.-Y. Li, "FedWM: Federated Crowdsourcing Workforce Management Service for Productive Laziness," in Proceedings of the 2023 IEEE International Conference on Web Services (ICWS'23), pp. 152-160, 2023.
S. Wang, Q. Li, L. Cui, Y. Jiang, Z. Shen & H. Yu, "CSP-RM: Reputation Management Decision Support for Crowdsourcing Service Providers," in Proceedings of the 2023 IEEE International Conference on Web Services (ICWS'23), pp. 161-169, 2023.
X. Tan, W. Y. B. Lim, D. Niyato & H. Yu, "Reputation-Aware Opportunistic Budget Optimization for Auction-based Federation Learning," in Proceedings of the 2023 International Joint Conference on Neural Networks (IJCNN'23), 2023.
A. Li, H. Peng, L. Zhang, J. Huang, Q. Guo, H. Yu & Y. Liu, "FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning," in Proceedings of the 2023 IEEE International Conference on Computer Communications (INFOCOM'23), 2023.
R. Kaewpuang, M. Xu, D. Niyato, H. Yu, Z. Xiong & J. Kang, "Stochastic Qubit Resource Allocation for Quantum Cloud Computing," in Proceedings of the 36th IEEE/IFIP Network Operations and Management Symposium (NOMS'23), 2023.
Y. Chen, G. Huzhang, Q. Yu, H. Sun, H.-Y. Li, J. Li, Y. Ni, A. Zeng, H. Yu & Z. Zhou, "Clustered Embedding Learning for Large-scale Recommender Systems," in Proceedings of the ACM Web Conference 2023 (WWW'23), pp. 1074–1084, 2023.
R. Kaewpuang, M. Xu, D. Niyato, H. Yu, Z. Xiong & S. Shen, "Adaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learning," in Proceedings of the 2023 International Conference on Computing, Networking and Communications (ICNC'23), pp. 71-76, 2023.
Y. Chen, Z. Chen, S. Guo, Y. Zhao, Z. Liu, P. Wu, C. Yang, Z. Li & H. Yu, "Efficient Training of Large-scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout," in Proceedings of the 35th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-23), pp. 15485-15493, 2023. (Innovative Application of AI Award)
Z. Q. Liew, H. Du, W. Y. B. Lim, Z. Xiong, D. Niyato & H. Yu, "Economics of Semantic Communication in Metaverse: An Auction Approach," in Proceedings of the 20th IEEE Consumer Communications & Networking Conference (CCNC'23), pp. 398-403, 2023.
X. Guo, B. Li & H. Yu, "Improving the Sample Efficiency of Prompt Tuning with Domain Adaptation," in Findings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP'22), pp. 3523-3537, 2022.
M. Xu, W. C. Ng, D. Niyato, H. Yu, C. Miao, D. I. Kim & S. Shen, "Stochastic Resource Allocation in Quantum Key Distribution for Secure Federated Learning," in Proceedings of the 2022 IEEE Global Communications Conference (GLOBECOM'22), pp. 4377-4382, 2022.
Y. Gao, Z. Ye, H. Yu, Z. Xiong, Y. Xiao & D. Niyato, "Multi-Resource Allocation for On-Device Distributed Federated Learning Systems," in Proceedings of the 2022 IEEE Global Communications Conference (GLOBECOM'22), pp. 160-165, 2022.
X. Cao, Y. Shi, J. Wang, H. Yu, X. Wang & Z. Yan, "Cross-modal Knowledge Graph Contrastive Learning for Machine Learning Method Recommendation," in Proceedings of the 30th ACM Multimedia Conference (ACM MM'22), pp. 3694-3702, 2022.
J. Qu, R. W. Liu, J. Nie, X. Deng, Z. Xiong, Y. Zhang, H. Yu & D. Niyato, "Edge Computing-Enabled Multi-Sensor Data Fusion for Intelligent Surveillance in Maritime Transportation Systems," in Proceedings of the 20th IEEE International Conference on Dependable, Autonomic & Secure Computing (DASC'22), doi:10.1109/DASC/PiCom/CBDCom/Cy55231.2022.992799, 2022.
Y. Zhang & H. Yu, "Towards Verifiable Federated Learning," in Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI'22), pp. 5686-5693, 2022.
S. Zeng, Z. Li, H. Yu, Y. He, Z. Xu, D. Niyato & H. Yu, "Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training," in Proceedings of the 27th International Conference on Database Systems for Advanced Applications (DASFAA-22), pp. 455-471, 2022.
J. Zhang & H. Yu, "A Methodological Framework for Facilitating Explainable AI Design," in Proceedings of the 14th International Conference on Social Computing and Social Media (SCSM'22), pp. 437-446, 2022.
Y. Loh, Z. Chen, Y. Zhao & H. Yu, "FLAS: A Platform for Studying Attacks on Federated Learning," in Proceedings of the 14th International Conference on Social Computing and Social Media (SCSM'22), pp. 160-169, 2022.
Z. Liu, Y. Chen, Y. Zhao, H. Yu, Y. Liu, R. Bao, J. Jiang, Z. Nie, Q. Xu & Q. Yang, "Contribution-Aware Federated Learning for Smart Healthcare," in Proceedings of the 34th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-22), pp. 12396-12404, 2022. (Innovative Application of AI Award)
X. Guo, S. Wang, H. Zhao, S. Diao, J. Chen, Z. Ding, Z. He, Y. Xiao, B. Long, H. Yu & L. Wu, "Intelligent Online Selling Point Extraction for E-Commerce Recommendation," in Proceedings of the 34th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-22), pp. 12360-12368, 2022. (Innovative Application of AI Award)
X. Zhang, Y. Zou, H. Zhang, J. Zhou, S. Diao, J. Chen, Z. Ding, Z. He, X. He, Y. Xiao, B. Long, H. Yu & L. Wu, "Automatic Product Copywriting for E-Commerce," in Proceedings of the 34th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-22), pp. 12423-12431, 2022. (Innovative Application of AI Award)
H.-Y. Li, Y. Ni, A. Zeng, H. Yu & C. Miao, "Prior-Guided Transfer Learning for Enhancing Item Representation in E-commerce," in Proceedings of the 34th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-22), pp. 12387-12395, 2022. (Innovative Application of AI Award)
D. Feng, C. Helena, W. Y. B. Lim, J. S. Ng, H. Jiang, Z. Xiong, J. Kang, H. Yu, D. Niyato & C. Miao, "CrowdFL: A Marketplace for Crowdsourced Federated Learning," in Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22), pp. 13164-13166, 2022.
X. R. Z. Ho, W. Y. B. Lim, H. Jiang, J. S. Ng, H. Yu, Z. Xiong, D. Niyato & C. Miao, "Dynamic Incentive Mechanism Design for COVID-19 Social Distancing," in Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22), pp. 13173-13175, 2022.
H. Yang, T. Wang, X. Tang, Q. Li, Y. Shi, S. Jiang, H. Yu & H. Song, "Multi-task Learning for Bias-Free Joint CTR Prediction and Market Price Modeling in Online Advertising," in Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM'21), pp. 2291-2300, 2021.
H. Z. C. Teng, H. Jiang, X. R. Z. Ho, W. Y. B. Lim, J. S. Ng, H. Yu, Z. Xiong, D. Niyato & C. Miao, "Predictive Analytics for COVID-19 Social Distancing," in Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI'21), pp. 5016-5019, 2021.
P. S. Kyaw & H. Yu, "Personalised Federated Learning: A Combinational Approach," in Proceedings of the 1st International Student Conference on Artificial Intelligence (STCAI'21), 2021. (Best Paper Award)
Y. Shu, J. Zhang & H. Yu, "Fairness in Design: A Tool for Guidance in Artificial Intelligence Design," in Proceedings of the 13th International Conference on Social Computing and Social Media (SCSM'21), pp. 500-510, 2021.
J. Zhang, Y. Shu & H. Yu, "Human-Machine Interaction for Autonomous Vehicles: A Review," in Proceedings of the 13th International Conference on Social Computing and Social Media (SCSM'21), pp. 190-201, 2021.
X. Cao, Y. Shi, H. Yu, J. Wang, X. Wang, Z. Yan & Z. Chen, "DEKR: Description Enhanced Knowledge Graph for Machine Learning Method Recommendation," in Proceedings of the 44th ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'21), pp. 203-212, 2021.
C. Liu, H. Yu, Z. Shen, I. Dixon, Y. Yu, Z. Gao, P. Wang, P. Ren, X. Xie, L. Cui & C. Miao, "Enhancing Viewing Experience of Generated Visual Storylines for Promotional Videos," in Proceedings of the 2021 IEEE International Conference on Multimedia and Expo (ICME'21), doi:10.1109/ICME51207.2021.9428292, 2021.
C. Liu, H. Yu, B. Li, Z. Shen, Z. Gao, P. Ren, X. Xie, L. Cui & C. Miao, "Noise-resistant Deep Metric Learning with Ranking-based Instance Selection," in Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'21), pp. 6811-6820, 2021. (PREMIA Best Student Paper Runners Up Award)
X. Guo, B. Li, H. Yu & C. Miao, "Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection," in Proceedings of the 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT'21), pp. 5394-5407, 2021. (PREMIA Best Presentation Award)
Y. Chen, B. Li, H. Yu, P. Wu & C. Miao, "HyDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks," in Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-21), pp. 7081-7089, 2021.
H. Jiang, W. Y. B. Lim, J. S. Ng, H. Z. C. Teng, H. Yu, Z. Xiong, D. Niyato & C. Miao, "AI-Empowered Decision Support for COVID-19 Social Distancing," in Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-21), pp. 16044-16047, 2021.
A. Zeng, H. Yu, H. He, Y. Ni, Y. Li, J. Zhou & C. Miao, "Enhancing E-commerce Recommender System Adaptability with Online Deep Controllable Learning-To-Rank," in Proceedings of the 33rd Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21), pp. 15214-15222, 2021. (Innovative Application of AI Award)
Q. Meng, L. Cui, G. Yu, H. Yu, W. Guo & H. Li, "CLUE: Personalized Hospital Readmission Prediction Against Data Insufficiency under Imbalanced-Data Environment," in Proceedings of the 2020 International Conference on Bioinformatics and Biomedicine (BIBM'20), pp. 469-472, 2020.
K. L. Ng, Z. Chen, Z. Liu, H. Yu, Y. Liu & Q. Yang, "A Multi-player Game for Studying Federated Learning Incentive Schemes," in Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI'20), pp. 5179-5281, 2020.
H. J. Y. Wong, Z. Deng, H. Yu, J. Huang, C. Leung & C. Miao, "A Testbed for Studying COVID-19 Spreading in Ride-Sharing Systems," in Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI'20), pp. 5294-5296, 2020.
C. Liu, Z. Y. Lim, H. Yu, Z. Shen, I. Dixon, Z. Gao, P. Wang, P. Ren, X. Xie, L. Cui & C. Miao, "An AI-empowered Visual Storyline Generator," in Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI'20), pp. 5267-5269, 2020.
C. Liu, H. Yu, Y. Dong, Z. Shen, Y. Yu, I. Dixon, Z. Gao, P. Wang, P. Ren, X. Xie, L. Cui & C. Miao, "Generating Engaging Promotional Videos for E-commerce Platforms," in Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-20), pp. 13865-13866, 2020.
Z. Deng, A. Tu, Z. Liu & H. Yu, "Efficient Spatial-Temporal Rebalancing of Shareable Bikes," in Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-20), pp. 13775-13776, 2020.
A. Zeng, H. Yu, Q. Da, Y. Zhan & C. Miao, "Accelerating Ranking in E-Commerce Search Engines through Contextual Factor Selection," in Proceedings of the 32nd Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-20), pp. 13212-13219, 2020. (Innovative Application of AI Award)
Y. Zheng, H. Yu, Y. Shi, K. Zhang, S. Zhen, L. Cui, C. Leung & C. Miao, "PIDS: An Intelligent Electric Power Management Platform," in Proceedings of the 32nd Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-20), pp. 13220-13227, 2020. (Innovative Application of AI Award)
Y. Liu, A. Huang, Y. Luo, H. Huang, Y. Liu, Y. Chen, L. Feng, T. Chen, H. Yu & Q. Yang, "FedVision: An Online Visual Object Detection Platform powered by Federated Learning," in Proceedings of the 32nd Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-20), pp. 13172-13179, 2020. (Innovative Application of AI Award)
H. Yu, Z. Liu, Y. Liu, T. Chen, M. Cong, X. Weng, D. Niyato & Q. Yang, "A Fairness-aware Incentive Mechanism for Federated Learning," in Proceedings of the 3rd AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES-20), pp. 393-399, 2020.
D. Gao, Y. Liu, A. Huang, C. Jiu, H. Yu & Q. Yang, "Privacy-preserving Heterogeneous Federated Transfer Learning," in Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData'19), pp. 2552-2559, 2019.
Y. Dong, C. Liu, Z. Shen, Z. Gao, P. Wang, C. Zhang, P. Ren, X. Xie, H. Yu & Q. Huang, "Domain Specific and Idiom Adaptive Video Summarization," in Proceedings of the 1st ACM International Conference on Multimedia in Asia (MM Asia'19), pp. 49:1-49:6, 2019.
C. Liu, Y. Dong, H. Yu, Z. Shen, Z. Gao, P. Wang, C. Zhang, P. Ren, X. Xie, L. Cui & C. Miao, "Generating Persuasive Visual Storylines for Promotional Videos," in Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM'19), pp. 901-910, 2019.
T. Wang, J. Zhao, H. Yu, J. Liu, X. Yang, X. Ren & S. Shi, "Privacy-preserving Crowd-guided AI Decision-making in Ethical Dilemmas," in Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM'19), pp. 1311-1320, 2019.
Y. Dong, C. Liu, Z. Shen, Z. Gao, P. Wang, C. Zhang, P. Ren, X. Xie & H. Yu, "Personalized Video Summarization with Idiom Adaptation," in Proceedings of the 27th ACM Multimedia Conference (ACM MM'19), pp. 1041-1043, 2019.
J. Kang, Z. Xiong, D. Niyato, H. Yu, Y.-C. Liang & D. I. Kim, "Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach," in Proceedings of the 2019 IEEE VTS Asia Pacific Wireless Communications Symposium (APWCS'19), pp. 1-5, 2019. (2023 Best Influential Conference Paper Award)
J. W. Kong, Y. Xu & H. Yu, "Deep Transfer Learning for Abnormality Detection," in Proceedings of the 4th International Conference on Crowd Science and Engineering (ICCSE'19), 2019.
H. Yu, Y. Liu, X. Wei, C. Zheng, T. Chen, Q. Yang & X. Peng, "Fair and Explainable Dynamic Engagement of Crowd Workers," in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19), pp. 6575-6577, 2019. (Innovation Award)
X. Wei, Q. Li, Y. Liu, H. Yu, T. Chen & Q. Yang, "Multi-Agent Visualization for Explaining Federated Learning," in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19), pp. 6572-6574, 2019.
A. Zeng, H. Yu, X. Gao, K. Ou, Z. Huang, P. Hou, M. Song, C. Miao & J. Zhang, "An Online Intelligent Live Interaction System," in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19), pp. 6578-6580, 2019.
Y. Zheng, H. Yu, K. Zhang, Y. Shi, C. Leung & C. Miao, "Intelligent Decision Support for Improving Power Management," in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19), pp. 6587-6589, 2019.
X. Guo, H. Yu, C. Miao & Y. Chen, "Agent-based Decision Support for Pain Management in Primary Care Settings," in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19), pp. 6521-6523, 2019.
Q. Li, H. Lin, X. Wei, Y. Liu, R. Lin, H. Yu, T. Chen & Q. Yang, "Learning Federated Learning," the 28th International Joint Conference on Artificial Intelligence (IJCAI'19), 2019. (Most Educational Video Award)
J. Wang, Y. Chen, H. Yu, M. Huang & Q. Yang, "Easy Transfer Learning by Exploiting Intra-domain Structures," in Proceedings of the 2019 IEEE International Conference on Multimedia and Expo (ICME'19), doi:10.1109/ICME.2019.00211, 2019.
Z. Liu, H. Yu, L. Wang, L. Hu & Q. Yang, "Social Mobilization to Reposition Indiscriminately Parked Shareable Bikes," in Proceedings of the 18th International Conference on Autonomous Agents and Multi-agent Systems (AAMAS'19), pp. 2099-2101, 2019.
H. Yu, Z. Shen, L. Cui, Y. Zheng & V. R. Lesser, "Ethically Aligned Sacrifice Coordination to Enhance Social Welfare in Multi-agent Systems," in Proceedings of the 18th International Conference on Autonomous Agents and Multi-agent Systems (AAMAS'19), pp. 2300-2302, 2019.
Z. Liu, H. Yu, L. Wang, L. Hu & Q. Yang, "Ethically Aligned Mobilization of Community Effort to Reposition Shared Bikes," in Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19), pp. 9983-9984, 2019.
H. Yu, C. Miao, Y. Zheng, L. Cui, S. Fauvel & C. Leung, "Ethically Aligned Opportunistic Scheduling for Productive Laziness," in Proceedings of the 2nd AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES-19), pp. 45-51, 2019.
J. Wang, W. Feng, Y. Chen, H. Yu, M. Huang & P. S. Yu, "Visual Domain Adaptation with Manifold Embedded Distribution Alignment," in Proceedings of the 26th ACM Multimedia Conference (ACM MM'18), pp. 402-410, 2018.
S. Fauvel, H. Yu, C. Miao, L. Cui, H. Song, L. Zhang, X. Li & C. Leung, "Artificial Intelligence Powered MOOCs: A Brief Survey," in Proceedings of the 3rd IEEE International Conference on Agents (ICA'18), pp. 56-61, 2018.
C. Miao, Z. Zeng, X. Yu, H. Zhang, H. Yu, Q. Wu, A. H. Tan, D. Wang, B. T. H. Tan, D. W. Q. Ng, C. Leung, Q. Yang & Z. Shen, "Persuasive AI Companions for Active Independent Ageing," the 27th International Joint Conference on Artificial Intelligence (IJCAI'18), 2018. (Most Societally Beneficial Video Award)
H. Yu, Z. Shen, C. Miao, C. Leung, V. R. Lesser & Q. Yang, "Building Ethics into Artificial Intelligence," in Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18), pp. 5527-5533, 2018.
H. Yu, C. Miao, L. Cui, Y. Chen, S. Fauvel & Q. Yang, "Opportunistic Work-Rest Scheduling for Productive Aging," in Proceedings of the 10th International Conference on Social Computing and Social Media (SCSM'18), pp. 413-428, 2018.
Y. Dong, H. Hu, Y. Wen, H. Yu & C. Miao, "Personalized Emotion-aware Video Streaming for the Elderly," in Proceedings of the 20th International Conference on Human-Computer Interaction (HCI'18), pp. 372-382, 2018.
Y. Zheng, H. Yu, L. Cui, C. Miao, C. Leung & Q. Yang, "SmartHS: An AI Platform for Improving Government Service Provision," in Proceedings of the 30th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-18), pp. 7704-7711, 2018. (Innovative Application of AI Award)
H. Zhang, C. Miao & H. Yu, "Fuzzy Logic based Assessment on the Adaptive Level of Rehabilitation Exergames for the Elderly," in Proceedings of the 5th IEEE Global Conference on Signal and Information Processing (GlobalSIP'17), pp. 423-427, 2017.
H. Yu, Z. Shen, S. Fauvel, L. Cui & C. Miao, "Efficient Scheduling in Crowdsourcing based on Workers' Mood," in Proceedings of the 2nd IEEE International Conference on Agents (ICA'17), pp. 121-126, 2017.
Y. Dong, H. Hu, H. Yu & L. Zhang, "Towards Emotion Adaption in Multimedia Caring Services for the Elderly," in Proceedings of the 5th International Conference on Ageless Aging (ICAA'17), 2017.
W. Wang, H. Yu & C. Miao, "Deep Model for Dropout Prediction in MOOCs," in Proceedings of the 2nd International Conference on Crowd Science and Engineering (ICCSE'17), pp. 26-32, 2017.
L. Cui, X. Zhao, L. Liu, H. Yu & C. Miao, "Learning Complex Crowdsourcing Task Allocation Strategies from Humans," in Proceedings of the 2nd International Conference on Crowd Science and Engineering (ICCSE'17), pp. 33-37, 2017.
X. Min, Y. Shi, L. Cui, H. Yu & Y. Miao, "Efficient Crowd-Powered Active Learning for Reliable Review Evaluation," in Proceedings of the 2nd International Conference on Crowd Science and Engineering (ICCSE'17), pp. 136-143, 2017. (Best Poster Award)
H. Zhang, C. Miao, H. Yu & C. Leung, "A Computational Assessment Model for the Adaptive Level of Rehabilitation Exergames for the Elderly," in Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI-17), pp. 5021-5022, 2017.
Z. Pan, H. Yu, C. Miao & C. Leung, "Crowdsensing Air Quality with Image Analytics and Deep Learning," in Proceedings of the 29th AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI-17), pp. 4728-4733, 2017.
H. Yu, Z. Pan, C. Miao & C. Leung, "Crowd Computing for Population Aging Challenges," in Proceedings of the 1st International Conference on Crowd Science and Engineering (ICCSE'16), 2016.
J. Lin, H. Yu, Z. Pan, Z. Shen & L. Cui, "Towards Data-driven Software Engineering Skills Assessment," in Proceedings of the 1st International Conference on Crowd Science and Engineering (ICCSE'16), 2016. (Best Paper Award)
H. Lin, H. Yu, C. Miao & L. Qiu, "Towards Emotionally Intelligent Machines: Taking Social Context into Account," in Proceedings of 8th International Conference on Social Computing and Social Media (SCSM'16), pp. 12-24, 2016. (Best Paper Award)
H. Yu, "Algorithmic Crowdsourcing for Productive Aging," in Proceedings of the 9th World Congress on Active Ageing (WCAA'16), pp. 11-12, 2016.
C. Miao, C. Leung, Y. Chen & H. Yu, "Interactive Games for Active Ageing," in Proceedings of the 9th World Congress on Active Ageing (WCAA'16), pp. 11, 2016.
S. Liu, Z. Shen, H. Yu, H. Lin, Z. Guo, Z. Pan, C. Miao & C. Leung, "A Kinect-based Interactive Game for Improving the Cognitive Inhibition of the Elderly," in Proceedings of the 15th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'16), pp. 1479-1481, 2016.
C. Sun, Y. Shi, Q. Li, L. Cui, H. Yu & C. Miao, "A Hybrid Approach for Detecting Fraudulent Medical Insurance Claims," in Proceedings of the 15th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'16), pp. 1287-1288, 2016.
H. Yu, C. Miao, Z. Shen, J. Lin & C. Leung, "Infusing Human Factors into Algorithmic Crowdsourcing," in Proceedings of the 28th AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI-16), pp. 4062-4063, 2016.
Z. Pan, H. Yu, C. Miao & C. Leung, "Efficient Collaborative Crowdsourcing," in Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), pp. 4248-4249, 2016. (Best Student Poster Award)
H. Yu, S. Liu, Z. Pan, N. S. B. Khalid, Z. Shen, C. Miao & C. Leung, "Productive Aging through Intelligent Personalized Crowdsourcing," in Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), pp. 4405-4406, 2016.
Z. Shen, H. Yu, S. Li & C. Miao, "Multi-Agent System Development MADE Easy," in Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), pp. 4391-4392, 2016.
Y. Shi, C. Sun, Q. Li, L. Cui, H. Yu & C. Miao, "A Fraud Resilient Medical Insurance Claim System," in Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), pp. 4393-4394, 2016.
Z. Pan, H. Yu, C. Miao, C. Leung, Q. Yang, Z. Shen, Y. Chen, L. Cui, B. Huang, Y. Zhang, D. W. Q. Ng & K. K. Ong, "Artificial Intelligence for Liveable Cities," the 30th AAAI Conference on Artificial Intelligence (AAAI-16), 2016. (Best Video - People's Choice Award)
S. Liu, C. Miao, Y. Liu, H. Yu, J. Zhang & C. Leung, "An Incentive Mechanism to Elicit Truthful Opinions for Crowdsourced Multiple Choice Consensus Tasks," in Proceedings of the 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'15), pp. 96-103, 2015.
Z. Pan, C. Miao, B. T. H. Tan, H. Yu & C. Leung, "Agent Augmented Inter-generational Crowdsourcing," in Proceedings of the 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'15), pp. 237-238, 2015. (Best Demo Award)
Z. Pan, C. Miao, H. Yu, C. Leung & J. J. Chin, "The Effects of Familiarity in Design on the Adoption of Wellness Games by the Elderly," in Proceedings of the 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'15), pp. 387-390, 2015.
B. Li, H. Yu, Z. Shen, L. Cui & V. R. Lesser, "An Evolutionary Optimization based Multi-Agent Organization Framework," in Proceedings of the 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'15), pp. 35-38, 2015.
H. Lin, J. Hou, H. Yu, Z. Shen & C. Miao, "An Agent-based Game Platform for Exercising People's Prospective Memory," in Proceedings of the 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'15), pp. 235-236, 2015.
A. Borjigin, C. Miao, Z. Shen, H. Yu, S. F. Lim, T. H. Tan, Z. Zeng, Y. Guo, S. Fauvel, Y. Qiu, K. H. Pang & J. Ji, "Goal Oriented Teachable Agent in Virtual Learning Environment," the 24th International Joint Conference in Artificial Intelligence (IJCAI'15), 2015. (Best Application Video Award)
S. Liu, C. Miao, Y. Liu, H. Fang, H. Yu, J. Zhang & C. Leung, "A Reputation Revision Mechanism for Mitigating the Negative Effect of Misreported Reputation Ratings," in Proceedings of the 17th International Conference on Electronic Commerce (ICEC'15), pp. 7:1-7:8, 2015.
C. Leung, Z. Shen, H. Zhang, Q. Wu, J. C. Leung, K. H. Pang, H. Yu & C. Miao, "Aging in-Place: From Unobtrusive Sensing to Graceful Aging," in Proceedings of the 24th Annual John K. Friesen Conference "Harnessing Technology for Aging-in-Place", 2015.
J. Lin, H. Yu, C. Miao & Z. Shen, "An Affective Agent for Studying Composite Emotions," in Proceedings of the 14th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'15), pp. 1947-1948, 2015.
H. Yu, C. Miao, Z. Shen & C. Leung, "Quality and Budget aware Task Allocation for Spatial Crowdsourcing," in Proceedings of the 14th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'15), pp. 1689-1690, 2015.
H. Yu, H. Lin, S. F. Lim, J. Lin, Z. Shen & C. Miao, "Empirical Analysis of Reputation-aware Task Delegation by Humans from a Multi-Agent Game," in Proceedings of the 14th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'15), pp. 1687-1688, 2015.
H. Yu, C. Miao, Z. Shen, C. Leung, Y. Chen & Q. Yang, "Efficient Task Sub-delegation for Crowdsourcing," in Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), pp. 1305-1311, 2015.
J.-P. Mei, H. Yu, Y. Liu, Z. Shen & C. Miao, "A Social Trust Model Considering Trustees' Influence," in Proceedings of the 17th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA'14), pp. 357-364, 2014.
J. Lin, H. Yu, Z. Shen & C. Miao, "Studying Task Allocation Decisions of Novice Agile Teams with Data from Agile Project Management Tools," in Proceedings of the 29th IEEE/ACM International Conference on Automated Software Engineering (ASE'14), pp. 689-694, 2014.
Y. Liu, S. Liu, H. Fang, J. Zhang, H. Yu & C. Miao, "RepRev: Mitigating the Negative Effects of Misreported Ratings," in Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), pp. 3124-3125, 2014.
Y. Liu, J. Zhang, H. Yu & C. Miao, "Reputation-aware Continuous Double Auction," in Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), pp. 3126-3127, 2014.
J. Lin, H. Yu, Z. Shen & C. Miao, "Using Goal Net to Model User Stories in Agile Software Development," in Proceedings of the 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD'14), pp. 1-6, 2014.
Y. Cai, Z. Shen, S. Liu, H. Yu, J. Ji, M. McKeown, C. Leung & C. Miao, "An Agent-based Game for the Predictive Diagnosis of Parkinson's Disease," in Proceedings of the 13th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'14), pp. 1663-1664, 2014.
H. Yu, X. Yu, S.F. Lim, J. Lin, Z. Shen & C. Miao, "A Multi-Agent Game for Studying Human Decision-making," in Proceedings of the 13th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'14), pp. 1661-1662, 2014.
H. Yu, C. Miao, B. An, Z. Shen & C. Leung, "Reputation-aware Task Allocation for Human Trustees," in Proceedings of the 13th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'14), pp. 357-364, 2014.
H. Yu, Z. Shen & C. Leung, "Bringing Reputation-awareness into Crowdsourcing," in Proceedings of the 9th International Conference on Information, Communications and Signal Processing (ICICS'13), pp. 1-5, 2013.
H. Yu, Z. Shen & C. Leung, "From Internet of Things to Internet of Agents," in Proceedings of the 2013 IEEE International Conference on Internet of Things (iThings'13), pp.1054-1057, 2013.
H. Yu, C. Miao, B. An, C. Leung & V. R. Lesser, "A Reputation Management Approach for Resource Constrained Trustee Agents," in Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pp. 418-424, 2013.
S. Liu, H. Yu, C. Miao & A. C. Kot, "A Fuzzy Logic based Reputation Model against Unfair Ratings," in Proceedings of the 12th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'13), pp. 821-828, 2013.
H. Yu, Z. Shen, C. Miao & B. An, "A Reputation-aware Decision-making Approach for Improving the Efficiency of Crowdsourcing Systems," in Proceedings of the 12th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'13), pp. 1315-1316, 2013.
Q. Wu, X. Han, H. Yu, Z. Shen & C. Miao, "The Innovative Applications of Learning Companions in Chronicles of Singapura," in Proceedings of the 12th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'13), pp. 1171-1172, 2013.
H. Yu, Z. Shen, C. Miao & B. An, "Challenges and Opportunities for Trust Management in Crowdsourcing," in Proceeding of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'12), pp. 486-493, 2012.
H. Yu, Z. Shen & B. An, "An Adaptive Witness Selection Method for Reputation-based Trust Models," in Proceedings of the 15th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA'12), pp. 184-198, 2012.
H. Yu, C. Leung & C. Miao, "A Simple, General and Robust Trust Agent to Help the Elderly Select online Services," in Proceedings of the 2nd Southeast Asian Network of Ergonomics Societies Conference (SEANES'12), pp. 1-5, 2012.
H. Song, Z. Shen, H. Yu & Y. Chen, "Probabilistic-based Scheduling for Runtime Goal Sequence of Agents," in Proceedings of the2012 International Conference on Computer Science and Automation Engineering (CSAE'12), pp. 490-494, 2012.
H. Yu, S. Liu, A.C. Kot, C. Miao & C. Leung, "Dynamic Witness Selection for Trustworthy Distributed Cooperative Sensing in Cognitive Radio Networks," in Proceedings of the 13th IEEE International Conference on Communication Technology (ICCT'11), pp. 1-6, 2011. (Best Paper Award)
H. Yu, Z. Shen, C. Miao & A.-H. Tan, "A Simple Curious Agent to Help People be Curious," in Proceedings of the 10th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'11), pp. 1159-1160, 2011.
J. Lin, C. Miao & H. Yu, "A Cloud & Agent Based Architecture Design for an Educational Mobile SNS Game," in Proceedings of the 6th International Conference on E-learning and Games (Edutainment'11), pp. 212-219, 2011.
Z. Shen, C. Miao, L. Zhang, H. Yu & M. J. Chavez, "An Emotion Aware Agent Platform for Interactive Storytelling and Gaming," in Proceedings of the International Academic Conference on the Future of Game Design and Technology (Futureplay'10), pp. 257-258, 2010.
H. Yu, Y. Cai, Z. Shen, X. Tao & C. Miao, "Agents as Intelligent User Interfaces for the Net Generation," in Proceedings of the 15th International Conference on Intelligent User Interfaces (IUI'10), pp. 429-430, 2010.
H. Yu, Z. Shen & C. Miao, "A Trustworthy Beacon-based Location Tracking Model for Body Area Sensor Networks in m-Health," in Proceedings of the 7th International Conference on Information, Communications and Signal Processing (ICICS'09), doi:10.1109/ICICS.2009.5397622, 2009.
L. Pan, X. Meng, Z. Shen & H. Yu, "A Reputation Pattern for Service Oriented Computing," in Proceedings of the 7th International Conference on Information, Communications and Signal Processing (ICICS'09), doi:10.1109/ICICS.2009.5397618, 2009.
H. Yu, C. Miao, X. Tao, Z. Shen, Y. Cai, B. Li & Y. Miao, "Teachable Agents in Virtual Learning Environments: a Case Study," in Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare and Higher Education (E-LEARN'09), pp. 1088-1096, 2009.
B. Li, H. Yu, Z. Shen & C. Miao, "Evolutionary Organizational Search," in Proceedings of the 8th Joint International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'09), pp. 1329-1330, 2009.
H. Yu, Z. Shen, C.P. Low & C. Miao, "Transforming Learning through Agent Augmented Virtual World," in Proceedings of the 8th IEEE International Conference on Advanced Learning Technologies (ICALT'08), pp. 933-937, 2008.
H. Yu, Z. Shen & C. Miao, "Intelligent Software Agent Design Tool Using Goal Net Methodology," in Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'07), pp. 43-46, 2007.
H. Yu, Z. Shen & C. Miao, "A Service Based Multi-Agent System Design Tool for Modeling Integrated Manufacturing and Service Systems," in Proceedings of the 12th IEEE Conference on Emerging Technologies and Factory Automation (ETFA'07), pp. 149-154, 2007.
Y. L. Theng, K. L. Tan, E. P. Lim, J. Zhang, D. H. L. Goh, K. Chatterjea, H. C. Chew, A. X. Sun, H. Yu, N. Dang, Y. Li & M. C. Vo, "Mobile G-Portal Supporting Collaborative Sharing and Learning in Geography Fieldwork: An Empirical Study," in Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL'07), pp. 462-471, 2007.
H. Yu, L. Ding, X. Lu & B. Xie, "A Virtual Agent Based Mobile 3D Game with Mascot Capsule Micro3D API," in Proceedings of the 3rd IEE International Conference on Mobile Technology, Application and Systems (Mobility'06), pp. 36:1-36:6, 2006.
H. Yu, "Developing Mobile 3D Game Using MIDP 2.0 Game API and JSR-184 M3G API," in Proceedings of the SIGRAD 2005 Conference, pp. 69-73, 2005.

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Research Interest

Education

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Professional Society Membership

Professional Organization Services

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