Hana Sulieman

906 total citations
39 papers, 555 citations indexed

About

Hana Sulieman is a scholar working on Artificial Intelligence, Statistics, Probability and Uncertainty and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hana Sulieman has authored 39 papers receiving a total of 555 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 6 papers in Statistics, Probability and Uncertainty and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hana Sulieman's work include Anomaly Detection Techniques and Applications (5 papers), Face and Expression Recognition (4 papers) and Pharmaceutical Practices and Patient Outcomes (4 papers). Hana Sulieman is often cited by papers focused on Anomaly Detection Techniques and Applications (5 papers), Face and Expression Recognition (4 papers) and Pharmaceutical Practices and Patient Outcomes (4 papers). Hana Sulieman collaborates with scholars based in United Arab Emirates, Australia and Russia. Hana Sulieman's co-authors include David C. M. Kong, Colin B Chapman, Firuz Kamalov, Sanah Hasan, Kay Stewart, Ahmad Al‐Issa, Ayman Alzaatreh, David Santandreu Calonge, Mohammed Y. Hasan and Murodbek Safaraliev and has published in prestigious journals such as PLoS ONE, Technometrics and Sensors.

In The Last Decade

Hana Sulieman

37 papers receiving 522 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hana Sulieman United Arab Emirates	14	137	94	85	59	57	39	555
Robert Likić Croatia	17	143 1.0×	93 1.0×	87 1.0×	47 0.8×	74 1.3×	85	1.1k
David John United Kingdom	12	113 0.8×	114 1.2×	14 0.2×	15 0.3×	20 0.4×	51	813
Ali Alshahrani Saudi Arabia	10	46 0.3×	21 0.2×	40 0.5×	13 0.2×	56 1.0×	62	416
Allen Flynn United States	14	252 1.8×	197 2.1×	48 0.6×	5 0.1×	80 1.4×	56	739
Miriam Armstrong United States	10	151 1.1×	136 1.4×	29 0.3×	26 0.4×	26 0.5×	24	425
Thomas H. Payne United States	18	243 1.8×	249 2.6×	85 1.0×	10 0.2×	63 1.1×	33	1.4k
Jean-Baptiste Lamy France	14	31 0.2×	62 0.7×	408 4.8×	23 0.4×	14 0.2×	70	883
Peyman Rezaei‐Hachesu Iran	12	16 0.1×	80 0.9×	135 1.6×	21 0.4×	79 1.4×	55	740
Foster Goss United States	19	67 0.5×	115 1.2×	141 1.7×	22 0.4×	63 1.1×	47	1.1k
Rakesh Kumar Yadav India	19	11 0.1×	35 0.4×	70 0.8×	27 0.5×	43 0.8×	152	1.1k

Countries citing papers authored by Hana Sulieman

Since Specialization

Citations

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

Fields of papers citing papers by Hana Sulieman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hana Sulieman

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

Kamalov, Firuz, et al.. (2025). Mathematical Methods in Feature Selection: A Review. Mathematics. 13(6). 996–996. 4 indexed citations

Kamalov, Firuz, et al.. (2024). Powering Electricity Forecasting with Transfer Learning. Energies. 17(3). 626–626. 11 indexed citations

Sulieman, Hana, et al.. (2024). Relative range for skewed distributions: a tool for outlier detection. Gulf Journal of Mathematics. 16(2). 298–312. 3 indexed citations

Nazir, Amril, et al.. (2023). Suspicious Behavior Detection with Temporal Feature Extraction and Time-Series Classification for Shoplifting Crime Prevention. Sensors. 23(13). 5811–5811. 12 indexed citations

Senyuk, Mihail, et al.. (2023). Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology. Mathematics. 11(3). 525–525. 20 indexed citations

Sulieman, Hana, et al.. (2023). Nested ensemble selection: An effective hybrid feature selection method. Heliyon. 9(9). e19686–e19686. 9 indexed citations

Sulieman, Hana, et al.. (2023). Liposomal Encapsulation of Chemotherapeutics Agents Combined with the Use of Ultrasound in Cancer Treatment. Journal of Biomedical Nanotechnology. 19(7). 1128–1140. 1 indexed citations

Kamalov, Firuz, Said Elnaffar, Hana Sulieman, & Aswani Kumar Cherukuri. (2023). XyGen: Synthetic data generator for feature selection. Software Impacts. 15. 100485–100485. 4 indexed citations

Alzubaidi, Hamzah, Hana Sulieman, Kevin Mc Namara, Catarina Samorinha, & Colette Browning. (2021). The relationship between diabetes distress, medication taking, glycaemic control and self-management. International Journal of Clinical Pharmacy. 44(1). 127–137. 18 indexed citations

10.

Kamalov, Firuz, Hana Sulieman, & David Santandreu Calonge. (2021). Machine learning based approach to exam cheating detection. PLoS ONE. 16(8). e0254340–e0254340. 56 indexed citations

11.

Kamalov, Firuz, Aswani Kumar Cherukuri, Hana Sulieman, Fadi Thabtah, & Akbar Hossain. (2021). Machine learning applications for COVID-19: A state-of-the-art review. arXiv (Cornell University). 7 indexed citations

12.

Alzaatreh, Ayman, et al.. (2021). A Bootstrap Framework for Aggregating within and between Feature Selection Methods. Entropy. 23(2). 200–200. 17 indexed citations

13.

Zhang, Yuanyuan, Stephen Chan, Jeffrey Chu, & Hana Sulieman. (2020). On the Market Efficiency and Liquidity of High-Frequency Cryptocurrencies in a Bull and Bear Market. Journal of risk and financial management. 13(1). 8–8. 30 indexed citations

14.

Alzaatreh, Ayman & Hana Sulieman. (2019). On fitting cryptocurrency log-return exchange rates. Empirical Economics. 60(3). 1157–1174. 9 indexed citations

15.

Sulieman, Hana. (2015). Students’ Conceptions of Statistics: An Exploration of Attitudes across Majors. 3(2). 158–158. 1 indexed citations

16.

Sulieman, Hana. (2012). Shadow Learning in Undergraduate Mathematics: an Exploratory Study. 1(2).

17.

Ali, Gowhar, et al.. (2012). Evaluation of Outcomes Associated with Placement of Elective, Urgent, and Emergency Cerclage. The Journal of Obstetrics and Gynecology of India. 62(6). 660–664. 21 indexed citations

18.

Hasan, Sanah, Hana Sulieman, Kay Stewart, et al.. (2012). Assessing patient satisfaction with community pharmacy in the UAE using a newly-validated tool. Research in Social and Administrative Pharmacy. 9(6). 841–850. 58 indexed citations

19.

Sulieman, Hana, et al.. (2011). Assessment of the current practice of antibiotic skin testing in a tertiary Hospital in United Arab Emirates. The Journal of Infection in Developing Countries. 5(11). 759–764. 4 indexed citations

20.

Hutchinson, Robin A., P. James McLellan, J. O. Ramsay, Hana Sulieman, & D. W. Bacon. (2004). Investigating the impact of operating parameters on molecular weight distributions using functional regression. Macromolecular Symposia. 206(1). 495–508. 5 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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