K. Ch. Chatzisavvas

1.3k total citations · 1 hit paper
23 papers, 915 citations indexed

About

K. Ch. Chatzisavvas is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, K. Ch. Chatzisavvas has authored 23 papers receiving a total of 915 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Electrical and Electronic Engineering and 6 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in K. Ch. Chatzisavvas's work include Statistical Mechanics and Entropy (5 papers), Energy Load and Power Forecasting (4 papers) and Smart Grid Energy Management (3 papers). K. Ch. Chatzisavvas is often cited by papers focused on Statistical Mechanics and Entropy (5 papers), Energy Load and Power Forecasting (4 papers) and Smart Grid Energy Management (3 papers). K. Ch. Chatzisavvas collaborates with scholars based in Greece, India and Germany. K. Ch. Chatzisavvas's co-authors include Konstantinos Diamantaras, Thanasis Vafeiadis, C. P. Panos, Ch. C. Moustakidis, Athena Vakali, Μαρία Γιάτσογλου, Manolis G. Vozalis, Georgios C. Christoforidis, K. D. Sen and Stavros Lazarou and has published in prestigious journals such as Physical Review A, Energy Policy and Expert Systems with Applications.

In The Last Decade

K. Ch. Chatzisavvas

23 papers receiving 870 citations

Hit Papers

A comparison of machine l... 2015 2026 2018 2022 2015 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K. Ch. Chatzisavvas Greece 11 328 241 139 106 105 23 915
Daniel Schall Austria 21 292 0.9× 30 0.1× 472 3.4× 83 0.8× 103 1.0× 109 1.8k
M. J. Berry United States 14 293 0.9× 233 1.0× 257 1.8× 494 4.7× 6 0.1× 19 1.7k
Minghui Kong China 10 49 0.1× 41 0.2× 38 0.3× 178 1.7× 40 0.4× 21 539
Chiranjeeb Buragohain United States 9 151 0.5× 82 0.3× 59 0.4× 139 1.3× 13 0.1× 11 1.2k
Andrew D. Bailey United States 18 119 0.4× 17 0.1× 81 0.6× 77 0.7× 76 0.7× 53 857
Eric Johnson United States 12 89 0.3× 228 0.9× 115 0.8× 90 0.8× 8 0.1× 29 631
John E. Fogarty United States 8 46 0.1× 100 0.4× 20 0.1× 12 0.1× 19 0.2× 16 1.7k
Peng Zhu China 17 189 0.6× 151 0.6× 337 2.4× 5 0.0× 140 1.3× 62 997
Hideaki Aoyama Japan 19 94 0.3× 13 0.1× 30 0.2× 143 1.3× 55 0.5× 88 1.4k
Richard Watt New Zealand 17 84 0.3× 145 0.6× 51 0.4× 70 0.7× 23 0.2× 88 796

Countries citing papers authored by K. Ch. Chatzisavvas

Since Specialization
Citations

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

Fields of papers citing papers by K. Ch. Chatzisavvas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K. Ch. Chatzisavvas. 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 K. Ch. Chatzisavvas. The network helps show where K. Ch. Chatzisavvas may publish in the future.

Co-authorship network of co-authors of K. Ch. Chatzisavvas

This figure shows the co-authorship network connecting the top 25 collaborators of K. Ch. Chatzisavvas. A scholar is included among the top collaborators of K. Ch. Chatzisavvas 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 K. Ch. Chatzisavvas. K. Ch. Chatzisavvas 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.
Chatzisavvas, K. Ch., et al.. (2023). Deep learning forecasting tool facilitating the participation of photovoltaic systems into day-ahead and intra-day electricity markets. Sustainable Energy Grids and Networks. 36. 101149–101149. 5 indexed citations
2.
Varlamis, Iraklis, et al.. (2023). Efficient intent classification and entity recognition for university administrative services employing deep learning models. Intelligent Systems with Applications. 19. 200247–200247. 13 indexed citations
3.
Vrysis, Lazaros, et al.. (2023). Mobile software aids for people with low vision. Multimedia Tools and Applications. 83(10). 30919–30936. 1 indexed citations
4.
Topouzis, Fotis, Georgios Labiris, Theodoros Dardavesis, et al.. (2023). Development and Validation of the Life for Low Vision Questionnaire (LIFE4LVQ) Using Rasch Analysis: A Questionnaire Evaluating Ability and Independence. Journal of Clinical Medicine. 12(7). 2549–2549. 3 indexed citations
5.
Chatzisavvas, K. Ch., et al.. (2022). Efficient 24-hour ahead PV energy production forecasting employing a transformer-based model. 1–6. 4 indexed citations
6.
Evangelopoulos, Panagiotis, et al.. (2019). A Machine Learning Approach for NILM based on Odd Harmonic Current Vectors. University of Thessaly Institutional Repository (University of Thessaly). 1–6. 10 indexed citations
7.
Bouhouras, Aggelos S., et al.. (2017). Load Signature Formulation for Non-Intrusive Load Monitoring Based on Current Measurements. Energies. 10(4). 538–538. 31 indexed citations
8.
Bouhouras, Aggelos S., et al.. (2017). Load signatures development via harmonic current vectors. 123. 1–6. 4 indexed citations
9.
Γιάτσογλου, Μαρία, et al.. (2016). Sentiment analysis leveraging emotions and word embeddings. Expert Systems with Applications. 69. 214–224. 244 indexed citations
10.
Vafeiadis, Thanasis, et al.. (2015). A comparison of machine learning techniques for customer churn prediction. Simulation Modelling Practice and Theory. 55. 1–9. 312 indexed citations breakdown →
11.
Chatzisavvas, K. Ch., Spyros Tserkis, C. P. Panos, & Ch. C. Moustakidis. (2014). Systematic Study of Information Measures, Statistical Complexity and Atomic Structure Properties. International Journal of Theoretical Physics. 54(5). 1481–1491. 3 indexed citations
12.
Christoforidis, Georgios C., et al.. (2013). Covenant of Mayors initiative—Public perception issues and barriers in Greece. Energy Policy. 60. 643–655. 39 indexed citations
13.
Papadopoulos, Theofilos A., Grigoris K. Papagiannis, K. Ch. Chatzisavvas, & Georgios C. Christoforidis. (2012). Harmonic Level Measurements and Analysis at Higher Education Buildings. 50–50. 1 indexed citations
14.
Christoforidis, Georgios C., K. Ch. Chatzisavvas, Theofilos A. Papadopoulos, & Grigoris K. Papagiannis. (2012). Identifying non-technological barriers to Wind power: Local communities. 1–8. 1 indexed citations
15.
Moustakidis, Ch. C., et al.. (2010). Statistical measure of complexity and correlated behavior of Fermi systems. Physical Review E. 81(1). 11104–11104. 3 indexed citations
16.
Panos, C. P., et al.. (2009). A simple method for the evaluation of the information content and complexity in atoms. A proposal for scalability. Physics Letters A. 373(27-28). 2343–2350. 61 indexed citations
17.
Chatzisavvas, K. Ch., et al.. (2009). Complexity and neutron star structure. Physics Letters A. 373(43). 3901–3909. 68 indexed citations
18.
Chatzisavvas, K. Ch., et al.. (2009). Improving quantum gate fidelities using optimized Euler angles. Physical Review A. 80(5). 2 indexed citations
19.
Panos, C. P., et al.. (2006). Comparison of SDL and LMC measures of complexity: Atoms as a testbed. Physics Letters A. 363(1-2). 78–83. 40 indexed citations
20.
Sen, K. D., C. P. Panos, K. Ch. Chatzisavvas, & Ch. C. Moustakidis. (2006). Net Fisher information measure versus ionization potential and dipole polarizability in atoms. Physics Letters A. 364(3-4). 286–290. 50 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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