Ting Hu

5.5k total citations · 1 hit paper
149 papers, 3.1k citations indexed

About

Ting Hu is a scholar working on Molecular Biology, Pollution and Genetics. According to data from OpenAlex, Ting Hu has authored 149 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Molecular Biology, 31 papers in Pollution and 21 papers in Genetics. Recurrent topics in Ting Hu's work include Pharmaceutical and Antibiotic Environmental Impacts (23 papers), Bioinformatics and Genomic Networks (20 papers) and Composting and Vermicomposting Techniques (15 papers). Ting Hu is often cited by papers focused on Pharmaceutical and Antibiotic Environmental Impacts (23 papers), Bioinformatics and Genomic Networks (20 papers) and Composting and Vermicomposting Techniques (15 papers). Ting Hu collaborates with scholars based in China, Canada and United States. Ting Hu's co-authors include Xiaojuan Wang, Jie Gu, Jiyue Ma, Huiling Peng, Qianzhi Wang, Xiaodong Liang, Yu Zhang, Mohammad Zawad Ali, Md Nasmus Sakib Khan Shabbir and Ranran Zhang and has published in prestigious journals such as Cell, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Ting Hu

135 papers receiving 3.0k citations

Hit Papers

Machine Learning-Based Fault Diagnosis for Single- and Mu... 2019 2026 2021 2023 2019 50 100 150 200
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. Machine Learning-Based Fault Diagnosis for Single- and Multi-Faults in Induction Motors Using Measured Stator Currents and Vibration Signals
    2019 244 citations Ting Hu et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ting Hu China 30 936 855 524 289 233 149 3.1k
Rui Wang China 39 1.5k 1.6× 555 0.6× 394 0.8× 493 1.7× 387 1.7× 212 4.5k
Jun Meng China 27 563 0.6× 416 0.5× 282 0.5× 129 0.4× 367 1.6× 114 3.2k
Hang Wang China 41 427 0.5× 1.5k 1.7× 472 0.9× 746 2.6× 1.1k 4.7× 251 5.4k
Juan Wang China 29 218 0.2× 736 0.9× 437 0.8× 327 1.1× 1.1k 4.6× 189 3.3k
Shuying Li China 37 535 0.6× 1.4k 1.6× 39 0.1× 313 1.1× 469 2.0× 339 5.2k
Sang‐Ryong Lee South Korea 24 214 0.2× 424 0.5× 174 0.3× 91 0.3× 196 0.8× 134 2.8k
Shaojie Wang China 32 509 0.5× 577 0.7× 398 0.8× 268 0.9× 654 2.8× 151 3.1k
Jun Chen China 34 915 1.0× 1.0k 1.2× 97 0.2× 730 2.5× 600 2.6× 176 4.7k
Peter Meinicke Germany 28 294 0.3× 2.0k 2.4× 154 0.3× 844 2.9× 919 3.9× 54 4.1k
Zhenyan Zhang China 39 1.7k 1.8× 711 0.8× 224 0.4× 673 2.3× 1.2k 5.1× 142 5.2k

Countries citing papers authored by Ting Hu

Since Specialization
Citations

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

Fields of papers citing papers by Ting Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ting Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Ting Hu. A scholar is included among the top collaborators of Ting Hu 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 Ting Hu. Ting Hu 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.
Qu, Yan, Haoling Zhang, Ting Hu, & Wangzheqi Zhang. (2025). A unified framework of cell death: Energy interdependence and multimodal interactions in disease pathogenesis. 116–121.
2.
3.
Hu, Ting, Shaojie Zheng, Qingqing Liu, et al.. (2024). Melatonin treatment maintains the quality properties and storability of carambola fruit by modulating energy metabolism. Food Chemistry. 464(Pt 2). 141661–141661. 9 indexed citations
4.
Hu, Ting, Hong Zheng, Yi‐Lin Wu, et al.. (2024). Contagion of depression: a double-edged sword. Translational Psychiatry. 14(1). 396–396. 1 indexed citations
5.
Bacardit, Jaume, Alexander E. I. Brownlee, Stefano Cagnoni, et al.. (2024). Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems. IEEE Transactions on Evolutionary Computation. 29(5). 2213–2228. 6 indexed citations
6.
Hu, Ting, Yuxin Guo, Ying Liu, et al.. (2024). Age and urban–rural disparities in cutaneous melanoma mortality rates in the United States during the COVID‐19 pandemic. Pigment Cell & Melanoma Research. 37(6). 783–792.
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Xie, Jun, Jie Gu, Xiaojuan Wang, et al.. (2023). Response characteristics of denitrifying bacteria and denitrifying functional genes to woody peat during pig manure composting. Bioresource Technology. 374. 128801–128801. 21 indexed citations
9.
Hu, Ting, et al.. (2023). Non-coding RNAs are key players and promising therapeutic targets in atherosclerosis. Frontiers in Cell and Developmental Biology. 11. 1237941–1237941.
10.
Wang, Xianxun, et al.. (2023). The Effect of Down-Cascade Re-Regulation on Alleviating the Flow Regime Alteration Induced by an Up-Cascade Reservoir. Water. 15(12). 2166–2166. 1 indexed citations
11.
Chen, Yuanzhu, et al.. (2023). NSPA: characterizing the disease association of multiple genetic interactions at single-subject resolution. Bioinformatics Advances. 3(1). vbad010–vbad010. 1 indexed citations
12.
Chen, Tiexi, Wenping Yuan, Shuci Liu, et al.. (2023). Estimating Global GPP From the Plant Functional Type Perspective Using a Machine Learning Approach. Journal of Geophysical Research Biogeosciences. 128(4). 20 indexed citations
13.
14.
Choudhury, Salimur, et al.. (2022). Comparison of Genetic Operators for the Multiobjective Pickup and Delivery Problem. Mathematics. 10(22). 4308–4308.
15.
Chen, Yuanzhu, et al.. (2021). Hunting for vital nodes in complex networks using local information. Scientific Reports. 11(1). 9190–9190. 14 indexed citations
16.
Hu, Ting, et al.. (2018). Ensemble learning for detecting gene-gene interactions in colorectal cancer. PeerJ. 6. e5854–e5854. 19 indexed citations
17.
18.
Zhen, Lisha, et al.. (2015). Kinetics of petroleum hydrocarbon degradation in soil and diversity of microbial community during composting.. Nongye gongcheng xuebao. 31(15). 231–238. 4 indexed citations
19.
Wang, Yun, Shenglian Guo, Guang Yang, Xingjun Hong, & Ting Hu. (2014). Optimal early refill rules for Danjiangkou Reservoir. SHILAP Revista de lepidopterología. 13 indexed citations
20.
Huang, Huanfang, Shihua Qi, Chengkai Qu, et al.. (2014). [Distribution characteristics and risk assessment of organochlorine pesticides in soil from Jiufeng Mountain Range in Fujian, China].. PubMed. 35(7). 2691–7. 3 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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