Robert Keight

624 total citations
13 papers, 381 citations indexed

About

Robert Keight is a scholar working on Artificial Intelligence, Computer Science Applications and Genetics. According to data from OpenAlex, Robert Keight has authored 13 papers receiving a total of 381 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Computer Science Applications and 3 papers in Genetics. Recurrent topics in Robert Keight's work include Imbalanced Data Classification Techniques (5 papers), Online Learning and Analytics (4 papers) and Hemoglobinopathies and Related Disorders (3 papers). Robert Keight is often cited by papers focused on Imbalanced Data Classification Techniques (5 papers), Online Learning and Analytics (4 papers) and Hemoglobinopathies and Related Disorders (3 papers). Robert Keight collaborates with scholars based in United Kingdom, Iraq and United Arab Emirates. Robert Keight's co-authors include Raghad Al-Shabandar, Abir Hussain, Abir Hussain, Panos Liatsis, Andy Laws, Mohammed Khalaf, Paul Fergus, Dhiya Al‐Jumeily, Naeem Radi and Wasiq Khan and has published in prestigious journals such as IEEE Access, Neurocomputing and Liverpool John Moores University.

In The Last Decade

Robert Keight

13 papers receiving 359 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robert Keight United Kingdom 11 188 149 54 44 38 13 381
Yuwen Zhou China 7 91 0.5× 120 0.8× 12 0.2× 10 0.2× 100 2.6× 33 344
Ammar Almasri Jordan 6 44 0.2× 116 0.8× 6 0.1× 27 0.6× 24 0.6× 14 287
Ramin Ghorbani Netherlands 5 73 0.4× 143 1.0× 5 0.1× 76 1.7× 46 1.2× 11 272
Tarid Wongvorachan Canada 7 43 0.2× 111 0.7× 21 0.4× 28 0.6× 36 0.9× 17 252
Prakhar Bhardwaj India 4 39 0.2× 232 1.6× 15 0.3× 13 0.3× 18 0.5× 5 563
Derek H. Sleeman United Kingdom 8 45 0.2× 179 1.2× 18 0.3× 19 0.4× 50 1.3× 15 408
Serkan Savaş Türkiye 11 9 0.0× 108 0.7× 10 0.2× 32 0.7× 35 0.9× 37 372
Lilik Anifah Indonesia 8 14 0.1× 39 0.3× 40 0.7× 16 0.4× 50 1.3× 71 277
Deema Mohammed Alsekait Saudi Arabia 8 9 0.0× 67 0.4× 18 0.3× 34 0.8× 39 1.0× 46 240
Megha Bhushan India 14 27 0.1× 200 1.3× 2 0.0× 112 2.5× 74 1.9× 39 488

Countries citing papers authored by Robert Keight

Since Specialization
Citations

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

Fields of papers citing papers by Robert Keight

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert Keight

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

All Works

13 of 13 papers shown
1.
Al-Shabandar, Raghad, Abir Hussain, Robert Keight, & Wasiq Khan. (2020). Students Performance Prediction in Online Courses Using Machine Learning Algorithms. Liverpool John Moores University. 1–7. 44 indexed citations
2.
Al-Shabandar, Raghad, Abir Hussain, Panos Liatsis, & Robert Keight. (2019). Detecting At-Risk Students With Early Interventions Using Machine Learning Techniques. IEEE Access. 7. 149464–149478. 40 indexed citations
3.
Al-Shabandar, Raghad, Abir Hussain, Robert Keight, Andy Laws, & Thar Baker. (2018). The Application of Gaussian Mixture Models for the Identification of At-Risk Learners in Massive Open Online Courses. Liverpool John Moores University. 1–8. 18 indexed citations
4.
Hussain, Abir, et al.. (2018). Predicting Freezing of Gait in Parkinsons Disease Patients Using Machine Learning. 1–8. 29 indexed citations
5.
Al-Shabandar, Raghad, Abir Hussain, Panos Liatsis, & Robert Keight. (2018). Analyzing Learners Behavior in MOOCs: An Examination of Performance and Motivation Using a Data-Driven Approach. IEEE Access. 6. 73669–73685. 38 indexed citations
6.
Khalaf, Mohammed, Abir Hussain, Dhiya Al‐Jumeily, et al.. (2018). A Data Science Methodology Based on Machine Learning Algorithms for Flood Severity Prediction. Liverpool John Moores University. 1–8. 30 indexed citations
7.
Khalaf, Mohammed, Abir Hussain, Robert Keight, et al.. (2017). Recurrent Neural Network Architectures for Analysing Biomedical Data Sets. 232–237. 17 indexed citations
8.
Keight, Robert, et al.. (2017). Towards the discrimination of primary and secondary headache: An intelligent systems approach. 2768–2775. 7 indexed citations
9.
Al-Shabandar, Raghad, et al.. (2017). Machine learning approaches to predict learning outcomes in Massive open online courses. 713–720. 84 indexed citations
10.
Khalaf, Mohammed, Abir Hussain, Robert Keight, et al.. (2016). The utilisation of composite machine learning models for the classification of medical datasets for sickle cell disease. 38. 37–41. 11 indexed citations
11.
Khalaf, Mohammed, Abir Hussain, Robert Keight, et al.. (2016). Machine learning approaches to the application of disease modifying therapy for sickle cell using classification models. Neurocomputing. 228. 154–164. 32 indexed citations
12.
Khalaf, Mohammed, Abir Hussain, Dhiya Al‐Jumeily, et al.. (2015). Applied Difference Techniques of Machine Learning Algorithm and Web-Based Management System for Sickle Cell Disease. 122. 231–235. 6 indexed citations
13.
Fergus, Paul, et al.. (2015). Artificial Intelligence for Detecting Preterm Uterine Activity in Gynecology and Obstetric Care. Liverpool John Moores University. 215–220. 25 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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