Muhammad Aslam

921 total citations
109 papers, 700 citations indexed

About

Muhammad Aslam is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Muhammad Aslam has authored 109 papers receiving a total of 700 indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Statistics and Probability, 54 papers in Artificial Intelligence and 34 papers in Statistics, Probability and Uncertainty. Recurrent topics in Muhammad Aslam's work include Statistical Distribution Estimation and Applications (81 papers), Bayesian Methods and Mixture Models (53 papers) and Statistical Methods and Bayesian Inference (40 papers). Muhammad Aslam is often cited by papers focused on Statistical Distribution Estimation and Applications (81 papers), Bayesian Methods and Mixture Models (53 papers) and Statistical Methods and Bayesian Inference (40 papers). Muhammad Aslam collaborates with scholars based in Pakistan, Saudi Arabia and Australia. Muhammad Aslam's co-authors include Tabassum Naz Sindhu, Sajid Ali, Muhammad Riaz, Babar Zaman, Zawar Hussain, Muhammad Tahir, Tahir Mehmood, Muhammad Saleem, Nasir Abbas and Aamir Saghir and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Access.

In The Last Decade

Muhammad Aslam

101 papers receiving 663 citations

Peers

Muhammad Aslam

SPU

GPC

CSE

David H. Olwell United States

Wenhao Gui China

Robert N. Rodriguez United States

Ahmad Parsian Iran

Oluwafemi Samson Balogun Finland

Hare Krishna India

Maozai Tian China

Rosângela H. Loschi Brazil

Muhammad Noor‐ul‐Amin Pakistan

Marcelo Bourguignon Brazil

David H. Olwell United States

Muhammad Aslam

317 ×0.6

558 ×1.7

SPU

44 ×0.3

24 ×0.3

GPC

136 ×2.0

CSE

Citations per year, relative to Muhammad Aslam Muhammad Aslam (= 1×) peers David H. Olwell

Countries citing papers authored by Muhammad Aslam

Since Specialization

Citations

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

Fields of papers citing papers by Muhammad Aslam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muhammad Aslam

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

Barboza, Elgar, Rolando Salas López, Jhonsy O. Silva-López, et al.. (2024). Correction: Analyzing Urban Expansion and Land Use Dynamics in Bagua Grande and Chachapoyas Using Cloud Computing and Predictive Modeling. Earth Systems and Environment. 9(4). 3753–3756. 1 indexed citations

Barboza, Elgar, Rolando Salas López, Jhonsy O. Silva-López, et al.. (2024). Analyzing Urban Expansion and Land Use Dynamics in Bagua Grande and Chachapoyas Using Cloud Computing and Predictive Modeling. Earth Systems and Environment. 9(2). 741–757. 15 indexed citations

Aslam, Muhammad, et al.. (2023). An improved adaptive EWMA control chart for monitoring time between events with application in health sector. Quality and Reliability Engineering International. 39(4). 1396–1412. 19 indexed citations

Aslam, Muhammad, et al.. (2023). Investigation of half-normal model using informative priors under Bayesian structure. Statistics in Transition New Series. 24(4). 19–36. 1 indexed citations

Aslam, Muhammad, et al.. (2022). Efficient Auxiliary Information–Based Control Charting Schemes for the Process Dispersion with Application of Glass Manufacturing Industry. Mathematical Problems in Engineering. 2022. 1–21. 3 indexed citations

Aslam, Muhammad, et al.. (2021). A homogeneously weighted moving average control chart for monitoring time between events. Quality and Reliability Engineering International. 38(2). 1013–1044. 5 indexed citations

Aslam, Muhammad, et al.. (2021). A robust hybrid exponentially weighted moving average chart for monitoring time between events. Quality and Reliability Engineering International. 38(2). 895–923. 9 indexed citations

Aslam, Muhammad, et al.. (2021). Bayesian analysis of left-censored data using Weibull mixture model. Soft Computing. 26(1). 375–394. 1 indexed citations

Aslam, Muhammad, et al.. (2020). An improved Bayesian Modified-EWMA location chart and its applications in mechanical and sport industry. PLoS ONE. 15(2). e0229422–e0229422. 37 indexed citations

10.

Aslam, Muhammad, et al.. (2020). Reliability estimation from Topp Leone smixture distribution using optimal progressive censoring schemes: A Bayesian approach. Alexandria Engineering Journal. 59(3). 1539–1556. 4 indexed citations

11.

Aslam, Muhammad, et al.. (2019). The Body Temperature has any Influence or Relation with Snoring. International journal of research studies in biosciences. 7(7). 1 indexed citations

12.

Sindhu, Tabassum Naz, et al.. (2016). Study of the Left Censored Data from the Gumbel Type II Distribution under a Bayesian Approach. Journal of Modern Applied Statistical Methods. 15(2). 112–134. 8 indexed citations

13.

Sindhu, Tabassum Naz, et al.. (2016). Doubly Censored Data from Two-Component Mixture of Inverse Weibull Distributions: Theory and Applications. Journal of Modern Applied Statistical Methods. 15(2). 322–349. 7 indexed citations

14.

Sindhu, Tabassum Naz, et al.. (2014). On Estimation of the Frechet Distribution with Known Shape under Different Sample Schemes. 7(4). 353–368. 2 indexed citations

15.

Sindhu, Tabassum Naz, et al.. (2014). Statistical Inference for Mixed Burr Type II Distribution using a Bayesian Framework. 13(1). 97–107. 4 indexed citations

16.

Aslam, Muhammad, et al.. (2013). On Bayesian Estimation and Predictions for Two-Component Mixture of the Gompertz Distribution. Journal of Modern Applied Statistical Methods. 12(2). 269–292. 5 indexed citations

17.

Aslam, Muhammad, et al.. (2013). Statistical Properties of Two Component Mixture of Topp Leone Distribution under a Bayesian Approach. 6(1). 65–99. 2 indexed citations

18.

Noor, Farzana & Muhammad Aslam. (2012). Bayesian analysis of two parameter Pareto mixture using censoring. International Journal of the Physical Sciences. 7(44). 5878–5891. 1 indexed citations

19.

Aslam, Muhammad, et al.. (2012). Bayesian analysis of exponentiated gamma distribution under type II censored samples. 1(1). 30–39. 8 indexed citations

20.

Aslam, Muhammad, et al.. (2012). Bayesian Estimation of Two-Component Mixture of Gumbel Type II Distribution under Informative Priors, “This paper has been withdrawn”. International Journal of Basic and Applied Sciences. 1(4). 534–556. 7 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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