Cheston Tan

1.5k total citations · 1 hit paper
48 papers, 799 citations indexed

About

Cheston Tan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Cheston Tan has authored 48 papers receiving a total of 799 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Vision and Pattern Recognition, 19 papers in Artificial Intelligence and 13 papers in Cognitive Neuroscience. Recurrent topics in Cheston Tan's work include Visual Attention and Saliency Detection (9 papers), Multimodal Machine Learning Applications (9 papers) and Human Pose and Action Recognition (7 papers). Cheston Tan is often cited by papers focused on Visual Attention and Saliency Detection (9 papers), Multimodal Machine Learning Applications (9 papers) and Human Pose and Action Recognition (7 papers). Cheston Tan collaborates with scholars based in Singapore, United States and China. Cheston Tan's co-authors include Tomaso Poggio, Hongyuan Zhu, Jiafei Duan, Samson Yu, Hui Li Tan, T. Serre, Sharat Chikkerur, Joo‐Hwee Lim, Vijay Chandrasekhar and Shijian Lu and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.

In The Last Decade

Cheston Tan

45 papers receiving 778 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.

A Survey of Embodied AI: From Simulators to Research Tasks

2022 176 citations Hongyuan Zhu, Cheston Tan et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Cheston Tan Singapore	13	476	182	175	76	52	48	799
Pietro Morerio Italy	17	552 1.2×	280 1.5×	100 0.6×	123 1.6×	23 0.4×	62	849
Stefano Nichele Norway	10	214 0.4×	218 1.2×	324 1.9×	56 0.7×	26 0.5×	49	889
Venkatesh K. Subramanian India	14	572 1.2×	214 1.2×	48 0.3×	44 0.6×	87 1.7×	47	879
Tiantian Wang China	13	936 2.0×	150 0.8×	285 1.6×	96 1.3×	81 1.6×	40	1.2k
Xosé M. Pardo Spain	13	503 1.1×	73 0.4×	142 0.8×	107 1.4×	84 1.6×	38	684
Kerstin Schill Germany	14	239 0.5×	75 0.4×	342 2.0×	74 1.0×	84 1.6×	57	745
Hilary Buxton United Kingdom	19	790 1.7×	302 1.7×	245 1.4×	64 0.8×	95 1.8×	68	1.2k
Gemma Roig Germany	15	412 0.9×	246 1.4×	140 0.8×	31 0.4×	42 0.8×	51	864

Countries citing papers authored by Cheston Tan

Since Specialization

Citations

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

Fields of papers citing papers by Cheston Tan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheston Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Cheston Tan. A scholar is included among the top collaborators of Cheston Tan 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 Cheston Tan. Cheston Tan 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

1.

Tian, Stephen, Tobias Pfaff, Cheston Tan, et al.. (2025). A review of learning-based dynamics models for robotic manipulation. Science Robotics. 10(106). eadt1497–eadt1497.

2.

Tan, Cheston, et al.. (2025). FedHPD: Heterogeneous Federated Reinforcement Learning via Policy Distillation. 2568–2570.

3.

Chen, Ruirui, Chengwei Qin, Cheston Tan, et al.. (2024). LLM-Based Multi-Hop Question Answering with Knowledge Graph Integration in Evolving Environments. 14438–14451. 3 indexed citations

4.

Jaiswal, Shantanu, et al.. (2024). Zero-Shot Visual Reasoning by Vision-Language Models: Benchmarking and Analysis. 1–8. 1 indexed citations

5.

Tan, Cheston, et al.. (2021). A nonlinear hidden layer enables actor–critic agents to learn multiple paired association navigation. Cerebral Cortex. 32(18). 3917–3936. 2 indexed citations

6.

Ma, Yining, et al.. (2021). Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee. Neural Information Processing Systems. 34. 4 indexed citations

7.

Huang, Ziqi, Hongyuan Zhu, Ying Sun, et al.. (2021). A Diagnostic Study Of Visual Question Answering With Analogical Reasoning. 2463–2467. 3 indexed citations

8.

Xu, Qianli, Jiayi Zhang, Joanes Grandjean, et al.. (2020). Neural correlates of retrieval-based enhancement of autobiographical memory in older adults. Scientific Reports. 10(1). 1447–1447. 5 indexed citations

9.

Chua, Yansong & Cheston Tan. (2017). Multiple Plasticity Mechanisms Enhance Associative Memory Retrieval in a Spiking Network Model of the Hippocampus.. National Conference on Artificial Intelligence. 1 indexed citations

10.

Li, Liyuan, Qianli Xu, Tian Gan, Cheston Tan, & Joo‐Hwee Lim. (2017). A Probabilistic Model of Social Working Memory for Information Retrieval in Social Interactions. IEEE Transactions on Cybernetics. 48(5). 1540–1552. 6 indexed citations

11.

Tan, Cheston, Stéphane Lallée, & Garrick Orchard. (2015). Benchmarking neuromorphic vision: lessons learnt from computer vision. Frontiers in Neuroscience. 9. 374–374. 24 indexed citations

12.

Tan, Cheston, et al.. (2015). The effect of repetition priming on spatial memory during backtracking in a novel environment. Cognitive Processing. 16(S1). 319–322. 1 indexed citations

13.

Chandrasekhar, Vijay, et al.. (2014). Incremental Graph Clustering for Efficient Retrieval from Streaming Egocentric Video Data. 2631–2636. 7 indexed citations

14.

Tan, Cheston, et al.. (2013). Neural representation of action sequences: how far can a simple snippet-matching model take us?. DSpace@MIT (Massachusetts Institute of Technology). 26. 593–601. 5 indexed citations

15.

Tan, Cheston, et al.. (2013). Visual Recognition using a Combination of Shape and Color Features. Cognitive Science. 35(35). 7 indexed citations

16.

Tan, Cheston, et al.. (2013). Encoding Co-occurrence of Features in the HMAX Model. Cognitive Science. 35(35). 2 indexed citations

17.

Lu, Shijian, et al.. (2013). Robust and Efficient Saliency Modeling from Image Co-Occurrence Histograms. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36(1). 195–201. 52 indexed citations

18.

Tan, Cheston, et al.. (2013). Classification of marine organisms in underwater images using CQ-HMAX biologically inspired color approach. National University of Singapore. 88. 1–8. 7 indexed citations

19.

Li, Xiaoli, Cheston Tan, & See-Kiong Ng. (2006). Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method. BMC Bioinformatics. 7(S4). S23–S23. 23 indexed citations

20.

Li, Xiaoli, Cheston Tan, & See-Kiong Ng. (2006). Systematic Gene Function Prediction Using a Fuzzy Nearest-Cluster Method on Gene Expression Data. 171–178. 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.

Explore authors with similar magnitude of impact