Mingjun Zhong

4.7k total citations · 2 hit papers
55 papers, 2.6k citations indexed

About

Mingjun Zhong is a scholar working on Artificial Intelligence, Molecular Biology and Signal Processing. According to data from OpenAlex, Mingjun Zhong has authored 55 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 10 papers in Molecular Biology and 10 papers in Signal Processing. Recurrent topics in Mingjun Zhong's work include Smart Grid Energy Management (9 papers), Blind Source Separation Techniques (8 papers) and Bayesian Methods and Mixture Models (5 papers). Mingjun Zhong is often cited by papers focused on Smart Grid Energy Management (9 papers), Blind Source Separation Techniques (8 papers) and Bayesian Methods and Mixture Models (5 papers). Mingjun Zhong collaborates with scholars based in China, United Kingdom and United States. Mingjun Zhong's co-authors include Nigel Goddard, Charles Sutton, Stefano Squartini, Chaoyun Zhang, Mark Girolami, Anatole Lécuyer, Yongjin Guo, Fabien Lotte, Chao Gao and Wenpeng Luan and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Smart Grid and Advanced Science.

In The Last Decade

Mingjun Zhong

51 papers receiving 2.6k citations

Hit Papers

align trajectories

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.

Advances in Neural Information Processing Systems 27 (NIPS 2014)

2014 1.3k citations Mingjun Zhong, Nigel Goddard et al. profile →
Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring

2018 357 citations Chaoyun Zhang, Mingjun Zhong et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mingjun Zhong China	17	826	706	538	365	300	55	2.6k
A. Sherstinsky United States	6	589 0.7×	1.1k 1.5×	436 0.8×	330 0.9×	198 0.7×	10	3.3k
Dongbo Xi China	6	440 0.5×	1.5k 2.2×	813 1.5×	360 1.0×	140 0.5×	6	4.1k
Keyu Duan China	2	434 0.5×	1.5k 2.1×	795 1.5×	357 1.0×	126 0.4×	5	4.0k
Zhiyuan Qi China	7	433 0.5×	1.5k 2.2×	802 1.5×	410 1.1×	124 0.4×	16	4.1k
S. Lecœuche France	20	537 0.7×	1.5k 2.2×	855 1.6×	871 2.4×	140 0.5×	73	4.1k
Marco Wiering Netherlands	31	311 0.4×	1.3k 1.9×	720 1.3×	644 1.8×	284 0.9×	135	3.3k
Yimin Yang China	30	458 0.6×	1.0k 1.5×	870 1.6×	316 0.9×	51 0.2×	149	3.1k
Wenjie Yang China	7	347 0.4×	797 1.1×	927 1.7×	212 0.6×	71 0.2×	17	3.1k
Itamar Arel United States	12	260 0.3×	679 1.0×	389 0.7×	426 1.2×	259 0.9×	34	1.9k
Martin F. Møller Denmark	5	519 0.6×	1.1k 1.6×	507 0.9×	353 1.0×	93 0.3×	6	3.5k

Countries citing papers authored by Mingjun Zhong

Since Specialization

Citations

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

Fields of papers citing papers by Mingjun Zhong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingjun Zhong

This figure shows the co-authorship network connecting the top 25 collaborators of Mingjun Zhong. A scholar is included among the top collaborators of Mingjun Zhong 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 Mingjun Zhong. Mingjun Zhong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Farrow, Luke, Lesley Anderson, & Mingjun Zhong. (2025). Managing class imbalance in the training of a large language model to predict patient selection for total knee arthroplasty: Results from the Artificial intelligence to Revolutionise the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project. The Knee. 54. 1–8. 1 indexed citations

Wan, Hua, Yanfei Wang, Xiang Li, et al.. (2025). Heterozygous TBX2 frameshift variants cause a novel syndromic hearing loss with incompletely penetrant nystagmus. Journal of Medical Genetics. 63(1). 24–33.

Wang, Xuegang, Mingjun Zhong, Wenjian Li, et al.. (2025). GDC: Integration of Multi‐Omic and Phenotypic Resources to Unravel the Genetic Pathogenesis of Hearing Loss. Advanced Science. 12(29). e2408891–e2408891. 1 indexed citations

Wang, Xuegang, Mingjun Zhong, Yü Huang, et al.. (2024). Genotype-phenotype spectrum and correlation of PHARC Syndrome due to pathogenic ABHD12 variants. BMC Medical Genomics. 17(1). 203–203. 2 indexed citations

Zhong, Mingjun, et al.. (2024). Pharmacovigilance analysis of orlistat adverse events based on the FDA adverse event reporting system (FAERS) database. Heliyon. 10(14). e34837–e34837. 8 indexed citations

Zhong, Mingjun, et al.. (2023). The optimal factoring type with partial credit guarantee in the textile industry:disclosed or undisclosed. Industria Textila. 74(2). 209–216.

Zhong, Mingjun, et al.. (2023). An interpretable machine learning model for real-time sepsis prediction based on basic physiological indicators.. PubMed. 27(10). 4348–4356. 4 indexed citations

Farrow, Luke, G Ashcroft, Mingjun Zhong, & Lesley Anderson. (2022). Using Artificial Intelligence to Revolutionise the Patient Care Pathway in Hip and Knee Arthroplasty (ARCHERY): Protocol for the Development of a Clinical Prediction Model. JMIR Research Protocols. 11(5). e37092–e37092. 12 indexed citations

Lu, Zhenyu, Yurong Cheng, Mingjun Zhong, et al.. (2022). LightNILM. 383–387. 7 indexed citations

10.

Bu, Fengxiao, Mingjun Zhong, Qinyi Chen, et al.. (2022). DVPred: a disease-specific prediction tool for variant pathogenicity classification for hearing loss. Human Genetics. 141(3-4). 401–411. 10 indexed citations

11.

Pullinger, Martin, Jonathan Kilgour, Nigel Goddard, et al.. (2021). The IDEAL household energy dataset, electricity, gas, contextual sensor data and survey data for 255 UK homes. Scientific Data. 8(1). 146–146. 40 indexed citations

12.

Batra, Nipun, et al.. (2019). Towards reproducible state-of-the-art energy disaggregation. 193–202. 78 indexed citations

13.

Jiang, Shouyong, Hongru Li, Mingjun Zhong, et al.. (2019). AREA: An adaptive reference-set based evolutionary algorithm for multiobjective optimisation. Information Sciences. 515. 365–387. 18 indexed citations

14.

Zhang, Chaoyun, et al.. (2018). Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 357 indexed citations breakdown →

15.

Zhong, Mingjun, Nigel Goddard, & Charles Sutton. (2015). Latent Bayesian melding for integrating individual and population models. Neural Information Processing Systems. 28. 3618–3626. 14 indexed citations

16.

Zhong, Mingjun, Nigel Goddard, & Charles Sutton. (2014). Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation. Lincoln Repository (University of Lincoln). 27. 3590–3598. 47 indexed citations

17.

Zhong, Mingjun & Mark Girolami. (2012). A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices. UCL Discovery (University College London). 651–658. 1 indexed citations

18.

Zhong, Mingjun & Mark Girolami. (2009). Reversible Jump MCMC for Non-Negative Matrix Factorization. Cambridge University Engineering Department Publications Database. 663–670. 12 indexed citations

19.

Zhong, Mingjun, Fabien Lotte, Mark Girolami, & Anatole Lécuyer. (2007). Classifying EEG for brain computer interfaces using Gaussian processes. Pattern Recognition Letters. 29(3). 354–359. 70 indexed citations

20.

Zhong, Mingjun. (2005). Neural Networks and Brain, 2005. ICNN B '05. International Conference on. 10 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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