Liang Yu

2.6k total citations · 1 hit paper
47 papers, 1.8k citations indexed

About

Liang Yu is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Control and Systems Engineering. According to data from OpenAlex, Liang Yu has authored 47 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Electrical and Electronic Engineering, 15 papers in Computer Networks and Communications and 13 papers in Control and Systems Engineering. Recurrent topics in Liang Yu's work include Smart Grid Energy Management (25 papers), Building Energy and Comfort Optimization (10 papers) and Cloud Computing and Resource Management (8 papers). Liang Yu is often cited by papers focused on Smart Grid Energy Management (25 papers), Building Energy and Comfort Optimization (10 papers) and Cloud Computing and Resource Management (8 papers). Liang Yu collaborates with scholars based in China, United Kingdom and Hong Kong. Liang Yu's co-authors include Tao Jiang, Yulong Zou, Xiaohong Guan, Yang Cao, Chao Shen, Dong Yue, Di Xie, Zhanbo Xu, Shuqi Qin and Meng Zhang and has published in prestigious journals such as IEEE Access, Sensors and IEEE Transactions on Smart Grid.

In The Last Decade

Liang Yu

41 papers receiving 1.8k citations

Hit Papers

A Review of Deep Reinforcement Learning for Smart Buildin... 2021 2026 2022 2024 2021 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Review of Deep Reinforcement Learning for Smart Building Energy Management
    2021 270 citations Liang Yu, Chao Shen et al. IEEE Internet of Things Journal profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Liang Yu China 20 1.3k 628 611 314 310 47 1.8k
Zhanbo Xu China 24 1.9k 1.4× 1.2k 1.9× 684 1.1× 248 0.8× 84 0.3× 97 2.6k
Bruce Nordman United States 22 1.4k 1.1× 322 0.5× 250 0.4× 1.1k 3.5× 315 1.0× 51 2.1k
Hongxun Hui Macao 26 1.6k 1.2× 1.0k 1.6× 266 0.4× 141 0.4× 75 0.2× 101 1.9k
Ghulam Hafeez Pakistan 27 1.9k 1.4× 1.1k 1.7× 254 0.4× 93 0.3× 67 0.2× 78 2.3k
Shahab Bahrami Canada 25 2.7k 2.0× 1.3k 2.0× 213 0.3× 151 0.5× 94 0.3× 50 2.9k
Wen-Tai Li Singapore 14 570 0.4× 334 0.5× 194 0.3× 181 0.6× 66 0.2× 27 908
Seshadhri Srinivasan India 17 405 0.3× 327 0.5× 250 0.4× 134 0.4× 61 0.2× 117 1.1k
Zhanle Wang Canada 18 971 0.7× 477 0.8× 106 0.2× 140 0.4× 98 0.3× 47 1.4k
Sohail Razzaq Pakistan 17 1.0k 0.8× 528 0.8× 130 0.2× 138 0.4× 67 0.2× 39 1.4k
Hicham Medromi Morocco 16 214 0.2× 199 0.3× 360 0.6× 184 0.6× 155 0.5× 155 1.1k

Countries citing papers authored by Liang Yu

Since Specialization
Citations

This map shows the geographic impact of Liang Yu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Liang Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liang Yu more than expected).

Fields of papers citing papers by Liang Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Liang Yu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Liang Yu. The network helps show where Liang Yu may publish in the future.

Co-authorship network of co-authors of Liang Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Liang Yu. A scholar is included among the top collaborators of Liang Yu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Liang Yu. Liang Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yu, Liang, et al.. (2025). Coordinated Operation Optimization of Grid-Interactive Residential Buildings Based on Neural Network-Assisted Hierarchical Model Predictive Control. IEEE Transactions on Automation Science and Engineering. 22. 13441–13457.
2.
3.
Yu, Liang, et al.. (2025). Load Frequency Control of Multi-Microgrids Based on Deep Deterministic Policy Gradient Integrated With Online Learning. IEEE Transactions on Smart Grid. 16(5). 4266–4278. 1 indexed citations
4.
5.
Yue, Dong, et al.. (2025). Optimization of Energy and Carbon Emissions in Integrated Energy System Based on Deep Reinforcement Learning Assisted by Large Language Model. IEEE Transactions on Industrial Informatics. 21(10). 8186–8197.
6.
7.
Yu, Liang, et al.. (2023). Online Distributed Coordination Operation for Grid-Interactive Efficient Residential Buildings. IEEE Transactions on Smart Grid. 15(4). 3639–3652. 5 indexed citations
8.
Yu, Liang, et al.. (2023). Two-Timescale Coordinated Voltage Regulation for High Renewable-Penetrated Active Distribution Networks Considering Hybrid Devices. IEEE Transactions on Industrial Informatics. 20(3). 3456–3467. 20 indexed citations
9.
10.
Jiang, Xin, Liang Yu, Tingjun Zhang, & Dong Yue. (2023). Interpretable Deep Reinforcement Learning for Voltage Regulation in Active Distribution Networks with High-penetrated Renewables. 2543–2548. 2 indexed citations
11.
Yue, Dong, et al.. (2022). Joint Energy and Workload Scheduling for Fog-Assisted Multimicrogrid Systems: A Deep Reinforcement Learning Approach. IEEE Systems Journal. 17(1). 164–175. 19 indexed citations
12.
Yu, Liang, Zhanbo Xu, Xiaohong Guan, et al.. (2022). Joint Optimization and Learning Approach for Smart Operation of Hydrogen-Based Building Energy Systems. IEEE Transactions on Smart Grid. 14(1). 199–216. 28 indexed citations
13.
Yu, Liang, et al.. (2020). Deep Reinforcement Learning and Blockchain for Peer-to-Peer Energy Trading among Microgrids. 360–365. 11 indexed citations
14.
Yu, Liang, Di Xie, Tao Jiang, Yulong Zou, & Kun Wang. (2017). Distributed Real-Time HVAC Control for Cost-Efficient Commercial Buildings Under Smart Grid Environment. IEEE Internet of Things Journal. 5(1). 44–55. 52 indexed citations
15.
Yu, Liang, Tao Jiang, & Yulong Zou. (2017). Online Temperature Control of a Residential Building in Smart Grid Environment. 1–6. 4 indexed citations
16.
Yu, Liang, Tao Jiang, Yulong Zou, & Zhixin Sun. (2016). Joint Energy Management Strategy for Geo-Distributed Data Centers and Electric Vehicles in Smart Grid Environment. IEEE Transactions on Smart Grid. 7(5). 2378–2392. 41 indexed citations
17.
Yu, Liang, Tao Jiang, & Yulong Zou. (2016). Real-Time Energy Management for Cloud Data Centers in Smart Microgrids. IEEE Access. 4. 941–950. 32 indexed citations
18.
Jiang, Tao, Liang Yu, & Yang Cao. (2015). Energy Management of Internet Data Centers in Smart Grid. Green energy and technology. 17 indexed citations
19.
Yu, Liang, et al.. (2014). POSTER. 1421–1423. 1 indexed citations
20.
Shi, Yan, et al.. (2011). A Unified Utility Framwork for Applications in Heterogeneous Wireless Environment. Advanced materials research. 403-408. 2612–2616. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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