Shengyu Tao

1.4k total citations · 2 hit papers
35 papers, 783 citations indexed

About

Shengyu Tao is a scholar working on Electrical and Electronic Engineering, Automotive Engineering and Control and Systems Engineering. According to data from OpenAlex, Shengyu Tao has authored 35 papers receiving a total of 783 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Electrical and Electronic Engineering, 26 papers in Automotive Engineering and 4 papers in Control and Systems Engineering. Recurrent topics in Shengyu Tao's work include Advanced Battery Technologies Research (25 papers), Advancements in Battery Materials (15 papers) and Electric Vehicles and Infrastructure (10 papers). Shengyu Tao is often cited by papers focused on Advanced Battery Technologies Research (25 papers), Advancements in Battery Materials (15 papers) and Electric Vehicles and Infrastructure (10 papers). Shengyu Tao collaborates with scholars based in China, United States and Hong Kong. Shengyu Tao's co-authors include Xuan Zhang, Guangmin Zhou, Yaojie Sun, Zhiyuan Han, Ruifei Ma, Runhua Gao, Yeyang Jia, Mengtian Zhang, Shiyi Fu and Tianshuai Wang and has published in prestigious journals such as Journal of the American Chemical Society, Nature Communications and Energy & Environmental Science.

In The Last Decade

Shengyu Tao

33 papers receiving 744 citations

Hit Papers

Machine-learning-assisted design of a binary descriptor t... 2023 2026 2024 2025 2023 2024 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shengyu Tao China 14 612 404 121 103 93 35 783
Paul Gasper United States 14 792 1.3× 711 1.8× 99 0.8× 80 0.8× 124 1.3× 37 971
Nawei Lyu China 13 513 0.8× 376 0.9× 82 0.7× 69 0.7× 26 0.3× 25 610
Mohammad Shahjalal United Kingdom 10 606 1.0× 465 1.2× 161 1.3× 75 0.7× 42 0.5× 16 747
Hossain Mansur Resalat Faruque Bangladesh 7 364 0.6× 290 0.7× 120 1.0× 89 0.9× 28 0.3× 11 546
Tamanna Shams United Kingdom 7 538 0.9× 454 1.1× 144 1.2× 51 0.5× 39 0.4× 9 657
Shashank Sripad United States 11 744 1.2× 701 1.7× 66 0.5× 60 0.6× 43 0.5× 18 920
Ashley Fly United Kingdom 15 799 1.3× 467 1.2× 154 1.3× 47 0.5× 152 1.6× 33 947
Ruben Leithoff Germany 9 856 1.4× 663 1.6× 232 1.9× 40 0.4× 68 0.7× 12 1.0k
Quanwei Chen China 11 576 0.9× 550 1.4× 340 2.8× 44 0.4× 26 0.3× 23 824

Countries citing papers authored by Shengyu Tao

Since Specialization
Citations

This map shows the geographic impact of Shengyu Tao'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 Shengyu Tao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shengyu Tao more than expected).

Fields of papers citing papers by Shengyu Tao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shengyu Tao. 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 Shengyu Tao. The network helps show where Shengyu Tao may publish in the future.

Co-authorship network of co-authors of Shengyu Tao

This figure shows the co-authorship network connecting the top 25 collaborators of Shengyu Tao. A scholar is included among the top collaborators of Shengyu Tao 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 Shengyu Tao. Shengyu Tao 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.
Tao, Shengyu, Dong Keun Lee, Scott Moura, et al.. (2025). Immediate remaining capacity estimation of heterogeneous second-life lithium-ion batteries via deep generative transfer learning. Energy & Environmental Science. 18(15). 7413–7426. 17 indexed citations
2.
Tao, Shengyu, et al.. (2025). Data sufficiency for transferable lithium-ion battery periodical SOH estimation under resource constraints. Cell Reports Physical Science. 6(10). 102901–102901. 2 indexed citations
3.
Tao, Shengyu, et al.. (2025). Robust and generalizable lithium-ion battery health estimation using multi-scale field data decomposition and fusion. Journal of Power Sources. 642. 236939–236939. 6 indexed citations
4.
Zhang, Xuan, Daniel M. Kammen, Jiahao Wang, et al.. (2025). Energy efficiency and carbon savings via a body grid. Communications Engineering. 4(1). 27–27. 2 indexed citations
5.
Lu, Gongxun, Lei Shi, Zhilong Wang, et al.. (2025). Decoding single-crystal lithium growth through solid electrolyte interphase omics. Nature Communications. 16(1). 9323–9323. 2 indexed citations
6.
Wu, Qiuwei, Zepeng Li, Shengyu Tao, et al.. (2025). Federated Multi-Agent Deep Reinforcement Learning-Based Competitive Pricing Strategy for Charging Station Operators. 3(3). 363–375. 1 indexed citations
7.
Zhang, Kui, Shengyu Tao, Xuan Zhang, et al.. (2025). Robust Health Monitoring for Lithium-Ion Batteries Under Guidance of Proxy Labels: A Deep Multitask Learning Approach. IEEE Transactions on Power Electronics. 40(8). 10272–10285. 9 indexed citations
8.
Tao, Shengyu, Yeyang Jia, Mengtian Zhang, et al.. (2025). Data-Driven Insight into the Universal Structure–Property Relationship of Catalysts in Lithium–Sulfur Batteries. Journal of the American Chemical Society. 147(26). 22851–22863. 11 indexed citations
9.
Xu, Yinliang, et al.. (2024). Feature-enhanced deep learning method for electric vehicle charging demand probabilistic forecasting of charging station. Applied Energy. 371. 123751–123751. 15 indexed citations
10.
Tao, Shengyu, Ruifei Ma, Zheng Liang, et al.. (2024). Rapid and sustainable battery health diagnosis for recycling pretreatment using fast pulse test and random forest machine learning. Journal of Power Sources. 597. 234156–234156. 53 indexed citations
11.
Fu, Shiyi, Shengyu Tao, Hongtao Fan, et al.. (2023). Data-driven capacity estimation for lithium-ion batteries with feature matching based transfer learning method. Applied Energy. 353. 121991–121991. 74 indexed citations
12.
Han, Zhiyuan, Runhua Gao, Tianshuai Wang, et al.. (2023). Machine-learning-assisted design of a binary descriptor to decipher electronic and structural effects on sulfur reduction kinetics. Nature Catalysis. 6(11). 1073–1086. 229 indexed citations breakdown →
13.
Tao, Shengyu, Haizhou Liu, Chongbo Sun, et al.. (2023). Collaborative and privacy-preserving retired battery sorting for profitable direct recycling via federated machine learning. Nature Communications. 14(1). 8032–8032. 73 indexed citations
14.
Tao, Shengyu, Chongbo Sun, Shiyi Fu, et al.. (2023). Battery Cross-Operation-Condition Lifetime Prediction via Interpretable Feature Engineering Assisted Adaptive Machine Learning. ACS Energy Letters. 8(8). 3269–3279. 46 indexed citations
15.
He, Kun, Shengyu Tao, Shiyi Fu, et al.. (2023). A Novel Quick Screening Method for the Second Usage of Parallel-connected Lithium-ion Cells Based on the Current Distribution. Journal of The Electrochemical Society. 170(3). 30514–30514. 8 indexed citations
16.
Tao, Shengyu, et al.. (2021). Behavioral Economics Optimized Renewable Power Grid: A Case Study of Household Energy Storage. Energies. 14(14). 4154–4154. 10 indexed citations
17.
Tao, Shengyu, et al.. (2021). Reliability Evaluation of Photovoltaic System Considering Inverter Thermal Characteristics. Electronics. 10(15). 1763–1763. 7 indexed citations
18.
19.
Tao, Shengyu, et al.. (2021). V2G Multi-Objective Dispatching Optimization Strategy Based on User Behavior Model. Frontiers in Energy Research. 9. 28 indexed citations
20.
Tao, Shengyu, et al.. (2021). Non-Intrusive Load Monitoring for Residential Appliances with Ultra-Sparse Sample and Real-Time Computation. Sensors. 21(16). 5366–5366. 19 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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