Abbas Mahdavi

644 total citations · 1 hit paper
24 papers, 479 citations indexed

About

Abbas Mahdavi is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, Abbas Mahdavi has authored 24 papers receiving a total of 479 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Statistics and Probability, 9 papers in Statistics, Probability and Uncertainty and 8 papers in Artificial Intelligence. Recurrent topics in Abbas Mahdavi's work include Statistical Distribution Estimation and Applications (16 papers), Bayesian Methods and Mixture Models (7 papers) and Probabilistic and Robust Engineering Design (7 papers). Abbas Mahdavi is often cited by papers focused on Statistical Distribution Estimation and Applications (16 papers), Bayesian Methods and Mixture Models (7 papers) and Probabilistic and Robust Engineering Design (7 papers). Abbas Mahdavi collaborates with scholars based in Iran, Canada and Taiwan. Abbas Mahdavi's co-authors include Debasis Kundu, Samad Jahandideh, Sedigheh Mahdavi, Shahryar Rahnamayan, Omid Kharazmi, Ahad Jamalizadeh, Tsung‐I Lin, Karim Abbaszadeh, S. H. Ong and N. Balakrishnan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Theoretical Biology and Soft Computing.

In The Last Decade

Abbas Mahdavi

16 papers receiving 452 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.

A new method for generating distributions with an application to exponential distribution

2016 293 citations Abbas Mahdavi, Debasis Kundu Communication in Statistics- Theory and Methods profile →

Peers

Abbas Mahdavi

SP

SPU

GPC

SRRQ

AI

Olçay Arslan Türkiye

S.K. Upadhyay India

Fatemah Alqallaf Kuwait

Ahmad Parsian Iran

Abbas Pak Iran

Omid Kharazmi Iran

Yuzhu Tian China

Isha Dewan India

Zaizai Yan China

Pali Sen United States

Olçay Arslan Türkiye

Abbas Mahdavi

463 ×1.3

SP

162 ×0.7

SPU

44 ×0.6

GPC

21 ×0.3

SRRQ

179 ×2.9

AI

Citations per year, relative to Abbas Mahdavi Abbas Mahdavi (= 1×) peers Olçay Arslan

Countries citing papers authored by Abbas Mahdavi

Since Specialization

Citations

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

Fields of papers citing papers by Abbas Mahdavi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abbas Mahdavi

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

1.

Mahdavi, Abbas, N. Balakrishnan, & Ahad Jamalizadeh. (2024). Robust Classification via Finite Mixtures of Matrix Variate Skew-t Distributions. Mathematics. 12(20). 3260–3260.

2.

Mahdavi, Abbas, N. Balakrishnan, & Ahad Jamalizadeh. (2024). EM algorithm for bounded generalized t mixture model with an application to image segmentation. Computational and Applied Mathematics. 44(2).

3.

Mahdavi, Abbas, Anthony F. Desmond, Ahad Jamalizadeh, & Tsung‐I Lin. (2024). Skew Multiple Scaled Mixtures of Normal Distributions with Flexible Tail Behavior and Their Application to Clustering. Journal of Classification. 41(3). 620–649.

4.

Mahdavi, Abbas, S. H. Ong, & Ahad Jamalizadeh. (2024). Bounded Flexible Scale Mixture of Normal Distributions with Application to Image Segmentation. 25(2). 825–848.

5.

Mahdavi, Abbas, Anthony F. Desmond, & Ahad Jamalizadeh. (2023). An EM algorithm for estimating the parameters of the skew generalized t -normal distribution with application to robust finite mixture modeling. Communications in Statistics - Simulation and Computation. 54(3). 615–632.

6.

Mahdavi, Abbas, et al.. (2021). A Multivariate Flexible Skew-Symmetric-Normal Distribution: Scale-Shape Mixtures and Parameter Estimation via Selection Representation. Symmetry. 13(8). 1343–1343. 8 indexed citations

7.

Mahdavi, Abbas, et al.. (2021). Maximum likelihood estimation for scale-shape mixtures of flexible generalized skew normal distributions via selection representation. Computational Statistics. 36(3). 2201–2230. 8 indexed citations

8.

Mahdavi, Abbas, et al.. (2020). Truncated log-logistic Family of Distributions. SHILAP Revista de lepidopterología. 5 indexed citations

9.

Mahdavi, Abbas, et al.. (2019). A Single Phase Boost Switched-Capacitor Multilevel Inverter Topology. 320–325. 7 indexed citations

10.

Mahdavi, Abbas, et al.. (2018). Alpha-power power distribution. SHILAP Revista de lepidopterología. 4(3). 129–135. 1 indexed citations

11.

Mahdavi, Abbas, et al.. (2017). An extended weighted exponential distribution. Journal of Modern Applied Statistical Methods. 16(1). 296–307. 6 indexed citations

12.

Mahdavi, Abbas. (2017). Generalized Topp-Leone family of distributions. SHILAP Revista de lepidopterología. 3(2). 65–75. 9 indexed citations

13.

Mahdavi, Abbas, et al.. (2017). A Method to Expand Family of Continuous Distributions based on Truncated Distributions. 13(2). 231–247. 7 indexed citations

14.

Mahdavi, Abbas & Debasis Kundu. (2016). A new method for generating distributions with an application to exponential distribution. Communication in Statistics- Theory and Methods. 46(13). 6543–6557. 293 indexed citations breakdown →

15.

Mahdavi, Abbas, et al.. (2016). On the bivariate weighted exponential distribution based on the generalized exponential distribution. Communication in Statistics- Theory and Methods. 46(8). 3641–3648. 2 indexed citations

16.

Mahdavi, Abbas. (2015). Two weighted distributions generated by exponential distribution. SHILAP Revista de lepidopterología. 9. 1–12. 8 indexed citations

17.

Mahdavi, Abbas, et al.. (2014). Robust tests for testing the parameters of a normal population. SHILAP Revista de lepidopterología. 25(3). 273–280.

18.

Mahdavi, Abbas. (2013). Robust Goodness of Fit Test Based on the Forward Search. 1(1). 6–10. 4 indexed citations

19.

Jahandideh, Samad & Abbas Mahdavi. (2012). RFCRYS: Sequence-based protein crystallization propensity prediction by means of random forest. Journal of Theoretical Biology. 306. 115–119. 22 indexed citations

20.

Mahdavi, Abbas & Samad Jahandideh. (2011). Application of density similarities to predict membrane protein types based on pseudo-amino acid composition. Journal of Theoretical Biology. 276(1). 132–137. 21 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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