Mehreen Saeed

1.6k total citations · 2 hit papers
26 papers, 1.1k citations indexed

About

Mehreen Saeed is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Mehreen Saeed has authored 26 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Molecular Biology. Recurrent topics in Mehreen Saeed's work include Metaheuristic Optimization Algorithms Research (5 papers), Face and Expression Recognition (5 papers) and Bayesian Methods and Mixture Models (4 papers). Mehreen Saeed is often cited by papers focused on Metaheuristic Optimization Algorithms Research (5 papers), Face and Expression Recognition (5 papers) and Bayesian Methods and Mixture Models (4 papers). Mehreen Saeed collaborates with scholars based in Pakistan, United States and Spain. Mehreen Saeed's co-authors include Irfan Younas, Qamar Askari, Kashif Javed, H.A. Babri, Abdur Rehman, Isabelle Guyon, Aamir Wali, Kristin P. Bennett, Alexander Statnikov and Bisakha Ray and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and Neurocomputing.

In The Last Decade

Mehreen Saeed

26 papers receiving 1.0k citations

Hit Papers

Political Optimizer: A novel socio-inspired meta-heuristi... 2020 2026 2022 2024 2020 2020 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mehreen Saeed Pakistan 9 705 257 166 160 124 26 1.1k
Irfan Younas Pakistan 12 643 0.9× 303 1.2× 211 1.3× 187 1.2× 140 1.1× 38 1.1k
Ahmad Nickabadi Iran 9 503 0.7× 205 0.8× 191 1.2× 128 0.8× 162 1.3× 31 906
Priyanka Anand India 14 747 1.1× 249 1.0× 192 1.2× 259 1.6× 158 1.3× 37 1.2k
Fei Han China 21 880 1.2× 273 1.1× 305 1.8× 185 1.2× 171 1.4× 69 1.4k
Prachi Agrawal India 12 529 0.8× 158 0.6× 220 1.3× 99 0.6× 87 0.7× 39 967
Hassan Shaban Egypt 10 564 0.8× 221 0.9× 194 1.2× 175 1.1× 96 0.8× 19 1.0k
Shaoqiu Zheng China 14 516 0.7× 220 0.9× 162 1.0× 125 0.8× 111 0.9× 20 899
Seyed Hamid Zahiri Iran 17 416 0.6× 145 0.6× 119 0.7× 177 1.1× 106 0.9× 81 865
Mohd. Asyraf Mansor Malaysia 21 785 1.1× 130 0.5× 230 1.4× 150 0.9× 104 0.8× 89 1.1k

Countries citing papers authored by Mehreen Saeed

Since Specialization
Citations

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

Fields of papers citing papers by Mehreen Saeed

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mehreen Saeed

This figure shows the co-authorship network connecting the top 25 collaborators of Mehreen Saeed. A scholar is included among the top collaborators of Mehreen Saeed 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 Mehreen Saeed. Mehreen Saeed 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.
Afzal, Muhammad, et al.. (2021). Characterization, antibiotic sensitivity assay and phylogenetic analysis of bacterial isolates of river water. Journal of Bacteriology & Mycology Open Access. 9(1). 1 indexed citations
2.
Askari, Qamar, Irfan Younas, & Mehreen Saeed. (2020). Critical evaluation of sine cosine algorithm and a few recommendations. 319–320. 5 indexed citations
3.
Askari, Qamar, Mehreen Saeed, & Irfan Younas. (2020). Heap-based optimizer inspired by corporate rank hierarchy for global optimization. Expert Systems with Applications. 161. 113702–113702. 297 indexed citations breakdown →
4.
Askari, Qamar, Irfan Younas, & Mehreen Saeed. (2020). Political Optimizer: A novel socio-inspired meta-heuristic for global optimization. Knowledge-Based Systems. 195. 105709–105709. 447 indexed citations breakdown →
5.
Seijo-Pardo, Borja, Amparo Alonso‐Betanzos, Kristin P. Bennett, et al.. (2019). Biases in feature selection with missing data. Neurocomputing. 342. 97–112. 13 indexed citations
6.
Seijo-Pardo, Borja, Amparo Alonso‐Betanzos, Kristin P. Bennett, et al.. (2018). Analysis of imputation bias for feature selection with missing data.. The European Symposium on Artificial Neural Networks. 1 indexed citations
7.
Wali, Aamir & Mehreen Saeed. (2018). m-CALP – Yet another way of generating handwritten data through evolution for pattern recognition. Biosystems. 175. 24–29. 6 indexed citations
8.
Wali, Aamir & Mehreen Saeed. (2018). Biologically inspired cellular automata learning and prediction model for handwritten pattern recognition. Biologically Inspired Cognitive Architectures. 24. 77–86. 7 indexed citations
9.
Zulqarnain, Rana Muhammad & Mehreen Saeed. (2017). A New Decision Making Method on Interval Valued Fuzzy Soft Matrix (IVFSM). British Journal of Mathematics & Computer Science. 20(5). 1–17. 8 indexed citations
10.
Saeed, Mehreen, et al.. (2017). Gaussian Cellular Automata Model for the Classification of Points Inside 2D Grid Patterns. 30. 350–355. 1 indexed citations
11.
Guyon, Isabelle, Kristin P. Bennett, Gavin C. Cawley, et al.. (2015). Design of the 2015 ChaLearn AutoML challenge. UEA Digital Repository (University of East Anglia). 1–8. 59 indexed citations
12.
Rehman, Abdur, Kashif Javed, H.A. Babri, & Mehreen Saeed. (2014). Relative discrimination criterion – A novel feature ranking method for text data. Expert Systems with Applications. 42(7). 3670–3681. 58 indexed citations
13.
Guyon, Isabelle, Demian Battaglia, Vincent Lemaire, et al.. (2014). Design of the first neuronal connectomics challenge: From imaging to connectivity. 2600–2607. 2 indexed citations
14.
Javed, Kashif, H.A. Babri, & Mehreen Saeed. (2014). Impact of a metric of association between two variables on performance of filters for binary data. Neurocomputing. 143. 248–260. 10 indexed citations
15.
Orlandi, Javier G., Bisakha Ray, Demian Battaglia, et al.. (2014). First Connectomics Challenge: From Imaging to Connectivity. MPG.PuRe (Max Planck Society). 46. 1–22. 4 indexed citations
16.
Saeed, Mehreen, Kashif Javed, & H.A. Babri. (2013). Machine learning using Bernoulli mixture models: Clustering, rule extraction and dimensionality reduction. Neurocomputing. 119. 366–374. 18 indexed citations
17.
Javed, Kashif, Mehreen Saeed, & H.A. Babri. (2013). The correctness problem: evaluating the ordering of binary features in rankings. Knowledge and Information Systems. 39(3). 543–563. 6 indexed citations
18.
Javed, Kashif, H.A. Babri, & Mehreen Saeed. (2011). Feature Selection Based on Class-Dependent Densities for High-Dimensional Binary Data. IEEE Transactions on Knowledge and Data Engineering. 24(3). 465–477. 84 indexed citations
19.
Saeed, Mehreen. (2008). The Use of Bernoulli Mixture Models for Identifying Corners of a Hypercube and Extracting Boolean Rules From Data. Neural Information Processing Systems. 225–236. 3 indexed citations
20.
Martin, Trevor, et al.. (1999). Automatic computer lip-reading using fuzzy set theory. AVSP. 14. 4 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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