VLDB 2026 Research / reviewers in the wild / expert

Zhijun Ren

dblp:60/10775 · DBLP profile ↗
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11ranked-venue papers
3as first author
10since 2021 · last 2026
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 6 · 6 since 2021Artificial intelligence and machine learning · 4 · 3 first-author · 4 since 2021Applied, interdisciplinary, general and emerging computing · 1
YearPublicationVenuePosition
2026 A MoE-LLM-based multisensor flexible fusion fault diagnosis method for rotating machinery
Tantao Lin, Zhijun Ren, Hamid Reza Karimi, Yongsheng Zhu, Ke Feng 0004, Jun Hong 0002
 Adv. Eng. Informatics2
2026 Reliability-aware dynamic graph fusion and LLM-based diagnostic assistant for bearing faults
Tantao Lin, Zhijun Ren, Xinzhuo Zhang, Hamid Reza Karimi, Yongsheng Zhu, Jun Hong 0002
 Adv. Eng. Informatics2
2025 A dual-perspective joint domain generalization network for bearing fault diagnosis under unseen working conditions
Zhijun Ren, Tantao Lin, Yongsheng Zhu, Linbo Zhu
 Adv. Eng. Informatics2
2025 Intra-domain self generalization network for intelligent fault diagnosis of bearings under unseen working conditions
Zhijun Ren, Linbo Zhu, Tantao Lin, Yongsheng Zhu, Jin Wan
 Adv. Eng. Informatics2
2025 A novel multi-sensor information fusion method for fault diagnosis of rotating machinery with missing signals
Tantao Lin, Zhijun Ren, Yongsheng Zhu, Hamid Reza Karimi
 Adv. Eng. Informatics2
2024 Neural architecture search for multi-sensor information fusion-based intelligent fault diagnosis
Tantao Lin, Zhijun Ren, Linbo Zhu, Yongsheng Zhu, Jin Wan
 Adv. Eng. Informatics2
2024 Progressive generative adversarial network for generating high-dimensional and wide-frequency signals in intelligent fault diagnosis
Zhijun Ren, Yongsheng Zhu, Ke Feng 0004, Zheng Liu 0002, Hong Fu, Jun Hong 0002, Adam Glowacz
 Eng. Appl. Artif. Intell.1
2023 Generative adversarial networks driven by multi-domain information for improving the quality of generated samples in fault diagnosis
Zhijun Ren, Yongsheng Zhu, Qing Ni, Jun Hong 0002
 Eng. Appl. Artif. Intell.1
2022 Adaptive cost-sensitive learning: Improving the convergence of intelligent diagnosis models under imbalanced data
Zhijun Ren, Yongsheng Zhu, Hong Fu, Qingbo Niu, Jun Hong 0002
 Knowl. Based Syst.1
2021 A novel weak fault diagnosis method for rolling bearings based on LSTM considering quasi-periodicity
Yongsheng Zhu, Zhijun Ren
 Knowl. Based Syst.3
2010 The Research of Service Network Based on Complex Network
abstract
At present the service science and engineering research are mainly focus on service discovery, service composition, service reputation and other key technical of the service computing. However the basic theory of service science, in particular, the basic principle of service and the evolution mechanism of service network only have some preliminary of research and exploration. The atomic services as the network nodes and the relationships of services combination as the network edges constitute the service network based services provision environment. This paper researched the basic characteristics of services and service networks, and proposed a new research method to explore the service network's "small world", "scale-free" characteristics and service network topology, based on the theory of complex network and existing networked software research works. It presents a new research perspective and methods for the service science and engineering research.
Haihong E, Meina Song, Junde Song, Zhijun Ren
 ICSS5