Lan Du

3.7k total citations · 1 hit paper
88 papers, 2.3k citations indexed

About

Lan Du is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Lan Du has authored 88 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Artificial Intelligence, 29 papers in Computer Vision and Pattern Recognition and 5 papers in Molecular Biology. Recurrent topics in Lan Du's work include Topic Modeling (25 papers), Face and Expression Recognition (18 papers) and Natural Language Processing Techniques (15 papers). Lan Du is often cited by papers focused on Topic Modeling (25 papers), Face and Expression Recognition (18 papers) and Natural Language Processing Techniques (15 papers). Lan Du collaborates with scholars based in Australia, China and United States. Lan Du's co-authors include Jianping Gou, Yongzhao Zhan, Xiang‐Jun Shen, Jinfu Chen, Min Wan, Wray Buntine, Mark Johnson, Zheng Bao, Hongwei Liu and Mengdao Xing and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Signal Processing.

In The Last Decade

Lan Du

82 papers receiving 2.3k citations

Hit Papers

Maximum Neighborhood Margin Discriminant Projection for C... 2014 2026 2018 2022 2014 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lan Du Australia 23 1.0k 394 294 214 162 88 2.3k
Oludare Isaac Abiodun Nigeria 12 869 0.9× 225 0.6× 91 0.3× 375 1.8× 241 1.5× 18 3.1k
Yaqing Wang China 20 1.7k 1.6× 657 1.7× 88 0.3× 655 3.1× 331 2.0× 81 3.3k
Yuan-Fang Wang United States 24 732 0.7× 1.2k 3.1× 125 0.4× 112 0.5× 220 1.4× 100 2.3k
Mourad Oussalah Finland 28 1.1k 1.1× 506 1.3× 87 0.3× 309 1.4× 161 1.0× 203 2.3k
Asdrúbal López‐Chau Mexico 12 639 0.6× 374 0.9× 39 0.1× 176 0.8× 109 0.7× 61 2.1k
A. Sherstinsky United States 6 1.1k 1.0× 436 1.1× 124 0.4× 212 1.0× 281 1.7× 10 3.3k
Pedro Antonio Gutiérrez Spain 31 1.4k 1.4× 401 1.0× 159 0.5× 117 0.5× 163 1.0× 164 3.4k
Chiranjib Bhattacharyya India 20 1.6k 1.6× 973 2.5× 58 0.2× 388 1.8× 285 1.8× 90 3.4k
Abiodun Esther Omolara Malaysia 15 883 0.9× 258 0.7× 116 0.4× 455 2.1× 305 1.9× 26 3.2k
Yunqian Ma United States 15 1.0k 1.0× 417 1.1× 93 0.3× 174 0.8× 213 1.3× 46 3.4k

Countries citing papers authored by Lan Du

Since Specialization
Citations

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

Fields of papers citing papers by Lan Du

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lan Du

This figure shows the co-authorship network connecting the top 25 collaborators of Lan Du. A scholar is included among the top collaborators of Lan Du 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 Lan Du. Lan Du 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.
Yang, Xiaohao, et al.. (2025). Neural Topic Modeling with Large Language Models in the Loop. 1377–1401.
2.
Du, Lan, et al.. (2025). Automated citation searching in systematic review production: A simulation study. Research Synthesis Methods. 16(1). 211–227. 1 indexed citations
3.
Yao, Qian, Lan Du, Jinhu Liang, et al.. (2025). Probing the Prediction of High-Temperature Ignition Delay Times of Jet Fuels via Machine Learning Approaches. Results in Engineering. 28. 107420–107420.
4.
Du, Lan, et al.. (2024). Rebalancing network with knowledge stability for class incremental learning. Pattern Recognition. 153. 110506–110506. 5 indexed citations
5.
McIntosh, Jennifer J., Joanne Enticott, Rebecca F. Goldstein, et al.. (2024). Exploring the acceptability of a risk prediction tool for cardiometabolic risk (gestational diabetes and hypertensive disorders of pregnancy) for use in early pregnancy: A qualitative study. Midwifery. 141. 104270–104270. 1 indexed citations
6.
Huang, Zhenhua, Jianping Gou, Lan Du, et al.. (2023). Teacher–student complementary sample contrastive distillation. Neural Networks. 170. 176–189. 5 indexed citations
7.
Gou, Jianping, et al.. (2023). Reconstructed Graph Constrained Auto-Encoders for Multi-View Representation Learning. IEEE Transactions on Multimedia. 26. 1319–1332. 5 indexed citations
8.
Gao, Caroline X., Dominic E. Dwyer, Ye Zhu, et al.. (2023). An overview of clustering methods with guidelines for application in mental health research. Psychiatry Research. 327. 115265–115265. 64 indexed citations
9.
Dipnall, Joanna F., Richard S. Page, Lan Du, et al.. (2021). Predicting fracture outcomes from clinical registry data using artificial intelligence supplemented models for evidence-informed treatment (PRAISE) study protocol. PLoS ONE. 16(9). e0257361–e0257361. 12 indexed citations
10.
Du, Lan, et al.. (2020). Multi-label Few/Zero-shot Learning with Knowledge Aggregated from Multiple Label Graphs. Monash University Research Portal (Monash University). 2935–2943. 21 indexed citations
11.
Zhao, He, Piyush Rai, Lan Du, & Wray Buntine. (2018). Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences. International Conference on Artificial Intelligence and Statistics. 1943–1951. 6 indexed citations
12.
Zhao, He, Lan Du, Wray Buntine, & Mingyuan Zhou. (2018). Inter and Intra Topic Structure Learning with Word Embeddings. Monash University Research Portal (Monash University). 5892–5901. 7 indexed citations
13.
Zhao, He, Lan Du, & Wray Buntine. (2017). A Word Embeddings Informed Focused Topic Model. Asian Conference on Machine Learning. 423–438. 18 indexed citations
14.
Zhao, He, Lan Du, Wray Buntine, & Gang Liu. (2017). MetaLDA: A Topic Model that Efficiently Incorporates Meta Information. 635–644. 24 indexed citations
15.
Du, Lan, et al.. (2016). Managing Mobile Market Users Based on the AARRR Model in the Age of Big Data. International Conference on Management Science and Engineering. 10(1). 58–66. 3 indexed citations
16.
Buntine, Wray, et al.. (2016). Nonparametric Bayesian topic modelling with the hierarchical Pitman–Yor processes. International Journal of Approximate Reasoning. 78. 172–191. 19 indexed citations
17.
Gou, Jianping, Yongzhao Zhan, Min Wan, et al.. (2014). Maximum Neighborhood Margin Discriminant Projection for Classification. The Scientific World JOURNAL. 2014. 1–16. 615 indexed citations breakdown →
18.
Du, Lan. (2012). Study on SOA-based Architecture of Closed-loop Supply Chain Management Information System. 1 indexed citations
19.
Gou, Jianping, Lan Du, Yuhong Zhang, & Taisong Xiong. (2012). A new distance-weighted k-nearest neighbor classifier. Journal of Information and Computational Science. 9(6). 1429–1436. 145 indexed citations
20.
Buntine, Wray, Lan Du, & Petteri Nurmi. (2010). Bayesian Networks on Dirichlet Distributed Vectors. ANU Open Research (Australian National University). 33–40. 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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