Maria Kaselimi

1.2k total citations · 1 hit paper
42 papers, 820 citations indexed

About

Maria Kaselimi is a scholar working on Electrical and Electronic Engineering, Aerospace Engineering and Civil and Structural Engineering. According to data from OpenAlex, Maria Kaselimi has authored 42 papers receiving a total of 820 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Electrical and Electronic Engineering, 9 papers in Aerospace Engineering and 7 papers in Civil and Structural Engineering. Recurrent topics in Maria Kaselimi's work include Smart Grid Energy Management (12 papers), Water Systems and Optimization (7 papers) and GNSS positioning and interference (7 papers). Maria Kaselimi is often cited by papers focused on Smart Grid Energy Management (12 papers), Water Systems and Optimization (7 papers) and GNSS positioning and interference (7 papers). Maria Kaselimi collaborates with scholars based in Greece, Malta and United Kingdom. Maria Kaselimi's co-authors include Nikolaos Doulamis, Athanasios Voulodimos, Eftychios Protopapadakis, Anastasios Doulamis, Anastasios Doulamis, Nikos Temenos, Ioannis Rallis, Vladimir Stanković, Lina Stanković and George Kopsiaftis and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and IEEE Access.

In The Last Decade

Maria Kaselimi

41 papers receiving 800 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.

Interpretable Deep Learning Framework for Land Use and Land Cover Classification in Remote Sensing Using SHAP

2023 101 citations Nikos Temenos, Maria Kaselimi et al. IEEE Geoscience and Remote Sensing Letters profile →

Peers

Maria Kaselimi

EEE

BC

CSE

AI

AA

Kai‐Wei Chiang Taiwan

Antonio Angrisano Italy

Jiahong Chen China

Lihui Wang China

K.K. Li Hong Kong

Xiaoxing He China

Guo Wei China

Brice Vallès New Zealand

Vassilis Gikas Greece

Abdelmajid Badri Morocco

Kai‐Wei Chiang Taiwan

Maria Kaselimi

519 ×1.2

EEE

69 ×0.4

BC

66 ×0.5

CSE

396 ×3.4

AI

39 ×0.5

AA

Citations per year, relative to Maria Kaselimi Maria Kaselimi (= 1×) peers Kai‐Wei Chiang

Countries citing papers authored by Maria Kaselimi

Since Specialization

Citations

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

Fields of papers citing papers by Maria Kaselimi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maria Kaselimi

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

Kaselimi, Maria, et al.. (2025). Geometric deep learning for ionospheric TEC modeling using a temporal graph convolutional network. Neural Computing and Applications. 37(22). 17179–17192.

2.

Kaselimi, Maria, et al.. (2024). GameVibe: a multimodal affective game corpus. Scientific Data. 11(1). 1306–1306. 3 indexed citations

3.

Kaselimi, Maria, et al.. (2023). Excess Attenuation Detection in Satellite Communication Channel Measurements with Deep Learning Architectures. 1–4. 1 indexed citations

4.

Kopsiaftis, George, Maria Kaselimi, Eftychios Protopapadakis, et al.. (2023). Performance comparison of physics-based and machine learning assisted multi-fidelity methods for the management of coastal aquifer systems. Frontiers in Water. 5. 5 indexed citations

5.

Temenos, Nikos, et al.. (2023). Interpretable Deep Learning Framework for Land Use and Land Cover Classification in Remote Sensing Using SHAP. IEEE Geoscience and Remote Sensing Letters. 20. 1–5. 101 indexed citations breakdown →

6.

Rallis, Ioannis, et al.. (2022). Tensor-Based Learning for Detecting Abnormalities on Digital Mammograms. Diagnostics. 12(10). 2389–2389. 1 indexed citations

7.

Kaselimi, Maria, Eftychios Protopapadakis, Anastasios Doulamis, & Nikolaos Doulamis. (2022). A review of non-invasive sensors and artificial intelligence models for diabetic foot monitoring. Frontiers in Physiology. 13. 924546–924546. 21 indexed citations

8.

Kaselimi, Maria, et al.. (2022). Novel Insights in Spatial Epidemiology Utilizing Explainable AI (XAI) and Remote Sensing. Remote Sensing. 14(13). 3074–3074. 30 indexed citations

9.

Kaselimi, Maria, et al.. (2022). A First Approach using Graph Neural Networks on Non-Intrusive-Load-Monitoring. 601–607. 8 indexed citations

10.

Kaselimi, Maria, et al.. (2022). An Efficient Deep Bidirectional Transformer Model for Energy Disaggregation. 2022 30th European Signal Processing Conference (EUSIPCO). 1536–1540. 2 indexed citations

11.

Rallis, Ioannis, Ioannis Georgoulas, George Kopsiaftis, et al.. (2022). Interpretation of net promoter score attributes using explainable AI. 113–117. 2 indexed citations

12.

Protopapadakis, Eftychios, et al.. (2022). Unsupervised diabetic foot monitoring techniques. 608–614. 1 indexed citations

13.

Kaselimi, Maria, et al.. (2022). COVID-19 Spatio-Temporal Evolution Using Deep Learning at a European Level. Sensors. 22(10). 3658–3658. 6 indexed citations

14.

Kaselimi, Maria, et al.. (2022). Spatio-Temporal Interpretation of The Covid-19 Risk Factors Using Explainable Ai. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. abs 1802 3888. 7705–7708. 2 indexed citations

15.

Kaselimi, Maria, et al.. (2021). Bioinformatics systems for monitoring and mitigating epidemics: The STAMINA Paradigm. 426–430. 2 indexed citations

16.

Kaselimi, Maria, et al.. (2021). Deep Recurrent Neural Networks for Ionospheric Variations Estimation Using GNSS Measurements. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–15. 36 indexed citations

17.

Kaselimi, Maria, Athanasios Voulodimos, Eftychios Protopapadakis, Nikolaos Doulamis, & Anastasios Doulamis. (2020). EnerGAN: A GENERATIVE ADVERSARIAL NETWORK FOR ENERGY DISAGGREGATION. 1578–1582. 26 indexed citations

18.

Kaselimi, Maria, et al.. (2020). Air Quality Data Time Series Modeling Using Deep Recurrent Neural Networks on Sentinel-5p Products. AGU Fall Meeting Abstracts. 2020. 1 indexed citations

19.

Kaselimi, Maria, Nikolaos Doulamis, Athanasios Voulodimos, Anastasios Doulamis, & Eftychios Protopapadakis. (2020). EnerGAN++: A Generative Adversarial Gated Recurrent Network for Robust Energy Disaggregation. IEEE Open Journal of Signal Processing. 2. 1–16. 41 indexed citations

20.

Kaselimi, Maria, Eftychios Protopapadakis, Athanasios Voulodimos, Nikolaos Doulamis, & Anastasios Doulamis. (2019). Multi-Channel Recurrent Convolutional Neural Networks for Energy Disaggregation. IEEE Access. 7. 81047–81056. 64 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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