Andrew Lensen

865 total citations
22 papers, 340 citations indexed

About

Andrew Lensen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Andrew Lensen has authored 22 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Molecular Biology. Recurrent topics in Andrew Lensen's work include Evolutionary Algorithms and Applications (17 papers), Metaheuristic Optimization Algorithms Research (16 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Andrew Lensen is often cited by papers focused on Evolutionary Algorithms and Applications (17 papers), Metaheuristic Optimization Algorithms Research (16 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Andrew Lensen collaborates with scholars based in New Zealand, Australia and China. Andrew Lensen's co-authors include Bing Xue, Mengjie Zhang, Yi Mei, Qi Chen, Harith Al-Sahaf, Yanan Sun, Binh Tran, Ying Bi, Will N. Browne and Brijesh Verma and has published in prestigious journals such as IEEE Transactions on Cybernetics, IEEE Transactions on Evolutionary Computation and Evolutionary Computation.

In The Last Decade

Andrew Lensen

20 papers receiving 335 citations

Peers

Andrew Lensen

CVPR

IME

CTM

CSE

Emilio Corchado Spain

Urvesh Bhowan New Zealand

Rodrigo Clemente Thom de Souza Brazil

Ghaith Manita Tunisia

Wojciech Kwedlo Poland

Surendra Kumar Shukla India

Sana Jawarneh Saudi Arabia

Nishtha Hooda India

Santos Kumar Baliarsingh India

Gloria Cerasela Crişan Romania

Emilio Corchado Spain

Andrew Lensen

163 ×0.7

55 ×1.4

CVPR

46 ×1.4

IME

38 ×1.2

CTM

33 ×1.4

CSE

Citations per year, relative to Andrew Lensen Andrew Lensen (= 1×) peers Emilio Corchado

Countries citing papers authored by Andrew Lensen

Since Specialization

Citations

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

Fields of papers citing papers by Andrew Lensen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Lensen

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

All Works

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20 of 20 papers shown

Lensen, Andrew, et al.. (2025). Genetic Programming for Explainable Manifold Learning. IEEE Transactions on Emerging Topics in Computational Intelligence. 10(1). 676–688.

Lensen, Andrew, et al.. (2024). Re-Identification of Individual Kākā: An Explainable DINO-Based Model. 1–6. 1 indexed citations

Lensen, Andrew, et al.. (2023). Producing Diverse Rashomon Sets of Counterfactual Explanations with Niching Particle Swarm Optimization Algorithms. Proceedings of the Genetic and Evolutionary Computation Conference. 393–401.

Lensen, Andrew, et al.. (2022). Explainable artificial intelligence for assault sentence prediction in New Zealand. Journal of the Royal Society of New Zealand. 53(1). 133–147. 5 indexed citations

Zeng, Peng, Andrew Lensen, & Yanan Sun. (2022). Large scale image classification using GPU-based genetic programming. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 619–622. 1 indexed citations

Lensen, Andrew, et al.. (2022). Improving the search of learning classifier systems through interpretable feature clustering. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 1752–1756. 1 indexed citations

Mei, Yi, Qi Chen, Andrew Lensen, Bing Xue, & Mengjie Zhang. (2022). Explainable Artificial Intelligence by Genetic Programming: A Survey. IEEE Transactions on Evolutionary Computation. 27(3). 621–641. 78 indexed citations

Lensen, Andrew, et al.. (2022). Evolving Counterfactual Explanations with Particle Swarm Optimization and Differential Evolution. Figshare. 11. 1–8. 1 indexed citations

Lensen, Andrew, et al.. (2021). Using Genetic Programming to Find Functional Mappings for UMAP Embeddings. Figshare. 704–711. 1 indexed citations

10.

Lensen, Andrew, Bing Xue, & Mengjie Zhang. (2021). Genetic Programming for Manifold Learning: Preserving Local Topology. Figshare. 6 indexed citations

11.

Lensen, Andrew, et al.. (2021). Genetic Programming for Evolving Similarity Functions Tailored to Clustering Algorithms. Figshare. 11. 688–695. 2 indexed citations

12.

Lensen, Andrew, Bing Xue, & Mengjie Zhang. (2020). Genetic Programming for Evolving a Front of Interpretable Models for Data Visualization. IEEE Transactions on Cybernetics. 51(11). 5468–5482. 31 indexed citations

13.

Lensen, Andrew, et al.. (2020). Evolving Simpler Constructed Features for Clustering Problems with Genetic Programming. Figshare. 1–8. 3 indexed citations

14.

Al-Sahaf, Harith, Ying Bi, Qi Chen, et al.. (2019). A survey on evolutionary machine learning. Journal of the Royal Society of New Zealand. 49(2). 205–228. 155 indexed citations

15.

Lensen, Andrew, Bing Xue, & Mengjie Zhang. (2019). Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis. Evolutionary Computation. 28(4). 531–561. 14 indexed citations

16.

Lensen, Andrew, Bing Xue, & Mengjie Zhang. (2018). Automatically evolving difficult benchmark feature selection datasets with genetic programming. Proceedings of the Genetic and Evolutionary Computation Conference. 458–465. 2 indexed citations

17.

Lensen, Andrew, et al.. (2018). Particle Swarm Optimisation for Feature Selection and Weighting in High-Dimensional Clustering. 1–8. 11 indexed citations

18.

Lensen, Andrew, Bing Xue, & Mengjie Zhang. (2017). Improving k -means clustering with genetic programming for feature construction. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 237–238. 2 indexed citations

19.

Lensen, Andrew, Bing Xue, & Mengjie Zhang. (2016). Particle swarm optimisation representations for simultaneous clustering and feature selection. 1–8. 13 indexed citations

20.

Lensen, Andrew, Harith Al-Sahaf, Mengjie Zhang, & Brijesh Verma. (2015). Genetic programming for algae detection in river images. 4971. 2468–2475. 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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