Hong YAO

Professor

School of Computer Science, Future City Campus,

China University of Geosciences, Wuhan

Address: No. 68 Jincheng Street, East Lake High-tech Development Zone, Wuhan city, Hubei Province, P.R.China, 430078

Email: yaohong@cug.edu.cn  

Research Interests: Geoinformatics and Spatiotemporal Big Data.

Brief Biography

Dr. Hong YAO completed his Doctor of Engineering in computer science at Huazhong University of Science and Technology in 2010 under the supervision of Professor Hai Jin. He currently holds the position of professor in the School of Computer Science, China University of Geosciences, Wuhan. His recent research focuses on Geoinformatics and Spatiotemporal Big Data.

Dr. Yao has authored over 100 papers in refereed journals and conferences. He holds more than ten technology invention patents in China. He was awarded the First Prize of the Education Ministry Technological Innovation Award in 2010. During the academic year 2014-2015, he served as a visiting scholar in Professor Jie Wu's lab at Temple University in Philadelphia, USA.

Dr. Yao is a member of the " State Key Laboratory of Biogeology and Environmental Geology", and actively participates in the Hubei Provincial Innovation Group "Geobiological Big Data and Computational Simulation". He is a member of the ACM/ IEEE/ CCF.

Academic Background

Education

Huazhong University of Science and Technology, Wuhan, China

D.Eng., Computer Science, March 2010, Advisor: Pro. Hai JIN

China University of Geosciences, Wuhan, China

M. Eng., Cartography and Geographic Information Engineering, June 2002, Advisor: Pro. Zhihua CAI

Wuhan Technical University of Surveying and Mapping, Wuhan, China

B. Eng., Computer and application, June 1998

Career

July 1998-Present, School of Computer Science, China University of Geosciences, Wuhan, P.R.China

·      2018-Present, Professor

·      2010-2017, Associate Professor

·      2003-2009, Lecturer

·      1998-2002, Teaching assistant

HONORS & AWARDS

“Core Support Technology of Large-scale Network Streaming Media Services” was awarded the "First Prize of the Ministry of Education Technology Invention Award" in 2010 (as the 5th contributor).

Journal articles (Selected)

[1] T. Li, R. Chen, Y. Duan, Y. Xie, S. Li, and H. Yao, "Spatial context-enhanced temporal knowledge graph reasoning," Information Processing & Management, vol. 63, no. 2, pt. B, p. 104456, 2026. doi: 10.1016/j.ipm.2025.104456.

[2] B. Jiang, L. Dong, X. Peng, R. Chen, C. Liu, and H. Yao, "Which plays a key role in sampling-based large-scale GNNs, sampling or iteration?," Neurocomputing, vol. 666, p. 132246, 2026. doi: 10.1016/j.neucom.2025.132246.

[3] S. Li, K. Liu, R. Chen, J. Lei, T. Li, and H. Yao, “Synthesizing event semantics for geographical entity representation,” Int. J. Geogr. Inf. Sci., vol. 39, no. 12, pp. 2839–2861, 2025, doi: 10.1080/13658816.2025.2505050.

[4] D. Zhou, S. Li, and H. Yao, “Mineral resource prediction based on representation learning,” Expert Syst. Appl., early access, 2025, doi: 10.1016/j.eswa.2025.128286.

[5] S. Li, Y. Wu, C. Fan, Y. Ye, and H. Yao, “Fine-grained geographic named entity recognition with few-shot learning,” Int. J. Geogr. Inf. Sci., early access, 2025, doi: doi.org/10.1080/13658816.2025.2505046.

[6] D. Zhou, Y. Duan, S. Li, and H. Yao, “Open-world semi-supervised relation extraction,” Neural Netw., vol. 186, p. 107266, May 2025, doi: 10.1016/j.neunet.2025.107266.

[7] Q. Chen, H. Yao, and D. Zhou, “The joint extraction of fact-condition statement and super relation in scientific text with table filling method,” Inf. Process. Manag., vol. 62, no. 1, p. 103906, Jan. 2025, doi: 10.1016/j.ipm.2024.103906

[8] D. Zhou, S. Li, L. Dong, R. Chen, X. Peng, and H. Yao, “C-KGE: Curriculum learning-based Knowledge Graph Embedding,” Comput. Speech Lang., vol. 89, p. 101689, 2025, doi: 10.1016/j.csl.2024.101689.

[9]  T. Li, R. Chen, Y. Duan, H. Yao, S. Li, and X. Li, “HGeoKG: A hierarchical geographic knowledge graph for geographic knowledge reasoning,” ISPRS Int. J. Geo-Inf., vol. 14, no. 1, pp. 1-26, Jan. 2025, doi: 10.3390/ijgi14010018.

[10]   Li, Shengwen, Suzhen Huang, Xuyang Cheng, Renyao Chen, Yi Zhou, Shunping Zhou, Hong Yao, and Junfang Gong. "Transfer Learning-Based Region Statistical Data Completion via Double Graphs." IEEE Transactions on Emerging Topics in Computational Intelligence 9, no. 1 (2024): 729-739.

[11] D. Zhou, S. Li, Q. Chen, and H. Yao, "Improving few-shot named entity recognition via Semantics induced Optimal Transport," Neurocomputing, vol. 597, p. 127938, 2024. doi: 10.1016/j.neucom.2024.127938.

[12] R. Chen, J. Lei, H. Yao, T. Li and S. Li, "Anchor-Enhanced Geographical Entity Representation Learning," in IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 1, pp. 924-938, Jan. 2025, doi: 10.1109/TNNLS.2023.3329822.

[13] S. Li, Y. Zhou, J. Cheng, and H. Yao, "Delay-aware karst spring discharge prediction," Journal of Hydrology, vol. 626, pt. A, p. 130250, 2023. doi: 10.1016/j.jhydrol.2023.130250.

[14]  Q. Chen, H. Yao, S. Li, X. Li, X. Kang, W. Lai, and J. Kuang, "Fact-condition statements and super relation extraction for geothermic knowledge graphs construction," Geoscience Frontiers, vol. 14, no. 5, p. 101412, 2023. doi: 10.1016/j.gsf.2022.101412.

[15]  L. Dong, D. Zhao, X. Zhang, X. Li, X. Kang and H. Yao, "Anchors-Based Incremental Embedding for Growing Knowledge Graphs," in IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 4, pp. 3458-3470, 1 April 2023, doi: 10.1109/TKDE.2021.3136482.

[16] Q. Chen, H. Yao, D. Zhou, S. Li, and L. Dong, “Extracting fact-condition relation from geological papers via deep structured semantic model with multi-grained representation,” Computers & Geosciences, vol. 178, p. 105416, 2023. doi: 10.1016/j.cageo.2023.105416.

[17]  X. Kang, X. Li, H. Yao, D. Li, B. Jiang, X. Peng, T. Wu, S. Qi, and L. Dong, "Dynamic hypergraph neural networks based on key hyperedges," Information Sciences, vol. 616, pp. 37–51, 2022. doi: 10.1016/j.ins.2022.10.006.

[18] S. Li, R. Chen, C. Sun, H. Yao, X. Cheng, Z. Li, T. Li, and X. Kang, “Region-aware neural graph collaborative filtering for personalized recommendation,” Int. J. Digit. Earth, vol. 15, no. 1, pp. 1446–1462, 2022. doi: 10.1080/17538947.2022.2113463.

[19] S. Li, C. Sun, R. Chen, X. Li, Q. Liang, J. Gong, and H. Yao, "Location-aware neural graph collaborative filtering," Int. J. Geogr. Inf. Sci., vol. 36, no. 8, pp. 1550–1574, 2022. doi: 10.1080/13658816.2022.2073594.

[20] L. Dong, H. Yao, D. Li, Y. Wang, S. Li, and Q. Liang, “Improving graph neural network via complex-network-based anchor structure,” Knowl.-Based Syst., vol. 233, p. 107528, 2021. doi: 10.1016/j.knosys.2021.107528.

[21] H. Yao, M. Xiong, H. Li, L. Gu, and D. Zeng, “Joint optimization of function mapping and preemptive scheduling for service chains in network function virtualization,” Future Gener. Comput. Syst., vol. 108, pp. 1112–1118, 2020. doi: 10.1016/j.future.2017.12.021.

[22] D. Zeng, L. Gu, and H. Yao, "Towards energy efficient service composition in green energy powered Cyber–Physical Fog Systems," Future Gener. Comput. Syst., vol. 105, pp. 757-765, 2020. doi: 10.1016/j.future.2018.01.060.D.

[23] L. Dong, X. Kang, M. Pan, M. Zhao, F. Zhang, and H. Yao, “B-matching-based optimization model for energy allocation in sea surface monitoring,” Energy, vol. 192, p. 116618, 2020. doi: 10.1016/j.energy.2019.116618.

[24] H. Yao, M. Xiong, D. Zeng, and J. Gong, “Mining multiple spatial–temporal paths from social media data,” Future Gener. Comput. Syst., vol. 87, pp. 782–791, 2018. doi: 10.1016/j.future.2017.08.003.

[25] H. Yao, M. Xiong, C. Liu, and Q. Liang, "Encounter probability aware task assignment in mobile crowdsensing," Mobile Netw. Appl., vol. 22, no. 2, pp. 275–286, 2017. doi: 10.1007/s11036-016-0794-5.

[26] H. Yao, C. Bai, M. Xiong, D. Zeng, and Z. Fu, "Heterogeneous cloudlet deployment and user-cloudlet association toward cost effective fog computing," Concurrency and Computation: Practice and Experience, vol. 29, no. 16, p. e3975, 2017, doi: 10.1002/cpe.3975.

[27]  H. Yao, J. Xu, Z. Luo, and D. Zeng, "MEMoMR: Accelerate MapReduce via reuse of intermediate results," Concurrency and Computation: Practice and Experience, vol. 28, no. 14, pp. 3814–3829, 2016, doi: 10.1002/cpe.3702.

[28] H. Yao, C. Bai, D. Zeng, Q. Liang, and Y. Fan, "Migrate or not? Exploring virtual machine migration in roadside cloudlet-based vehicular cloud," Concurrency and Computation: Practice and Experience, vol. 27, no. 18, pp. 5780–5792, 2015, doi: 10.1002/cpe.3642.

[29] H. Yao, D. Zeng, H. Huang, S. Guo, A. Barnawi, and I. Stojmenovic, “Opportunistic offloading of deadline-constrained bulk cellular traffic in vehicular DTNs,” IEEE Trans. Comput., vol. 64, no. 12, pp. 3515–3527, Dec. 2015, doi: 10.1109/TC.2015.2401012.

[30] H. Yao, H. Huang, D. Zeng, B. Li, and S. Guo, “An energy-aware deadline-constrained message delivery in delay-tolerant networks,” Wireless Netw., vol. 20, no. 7, pp. 1981–1993, Oct. 2014, doi: 10.1007/s11276-014-0720-3.

Full List:

https://scholar.google.com/citations?user=eYoOdnwAAAAJ&hl=en

Grants

[1]   "A collaborative intelligent mineral exploration prediction model driven by knowledge and multimodal data", (2025ZD1006004-06), National Science and Technology Major Project-Deep Earth Exploration and Mineral Resources Exploration (Deep Earth) Project, PI, 2025.08-2030.07;

[2]      "Adaptive Representation Learning for Interpretable Geographic Entities", the National Natural Science Foundation of China (42571543), PI, 2026.01-2030.12;

[3]      “Knowledge Graph and Text Jointly Dynamic Representation Learning in Hyperbolic Space”, the National Natural Science Foundation of China (No. 61972365), PI, 2020.1-2023.12.

[4]      “Resource Management and Task Scheduling in Hybrid Cloud and Fog Computing Environments”, the National Natural Science Foundation of China (No. 61672474), PI, 2017.1-2020.12.

[5]      “Study on Directional Routing and Incentive Schemes for Vehicular Ad-Hoc Network”, the National Natural Science Foundation of China (No. 61272470), PI, 2013.1-2016.12.