Masoud Asgharian

1.3k total citations
29 papers, 952 citations indexed

About

Masoud Asgharian is a scholar working on Statistics and Probability, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Masoud Asgharian has authored 29 papers receiving a total of 952 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Statistics and Probability, 13 papers in Artificial Intelligence and 4 papers in Economics and Econometrics. Recurrent topics in Masoud Asgharian's work include Statistical Methods and Inference (19 papers), Statistical Methods and Bayesian Inference (13 papers) and Bayesian Methods and Mixture Models (8 papers). Masoud Asgharian is often cited by papers focused on Statistical Methods and Inference (19 papers), Statistical Methods and Bayesian Inference (13 papers) and Bayesian Methods and Mixture Models (8 papers). Masoud Asgharian collaborates with scholars based in Canada, United States and Iran. Masoud Asgharian's co-authors include David B. Wolfson, Cyr Emile M’lan, David B. Hogan, Christina Wolfson, Truls Østbye, Kenneth Rockwood, Xun Zhang, Marco Carone, Ashkan Ertefaie and David A. Stephens and has published in prestigious journals such as New England Journal of Medicine, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.

In The Last Decade

Masoud Asgharian

26 papers receiving 914 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Masoud Asgharian Canada 10 459 201 128 111 102 29 952
Cyr Emile M’lan Canada 9 245 0.5× 191 1.0× 64 0.5× 106 1.0× 79 0.8× 9 864
Xiaojuan Mi United States 25 79 0.2× 47 0.2× 18 0.1× 70 0.6× 205 2.0× 54 2.4k
W. Molenaar Netherlands 8 56 0.1× 91 0.5× 26 0.2× 52 0.5× 65 0.6× 18 540
Célia Touraine France 10 57 0.1× 130 0.6× 8 0.1× 65 0.6× 75 0.7× 26 444
Iván Díaz United States 22 353 0.8× 21 0.1× 50 0.4× 31 0.3× 153 1.5× 97 1.3k
Virginia Chiocchia United Kingdom 12 40 0.1× 95 0.5× 76 0.6× 63 0.6× 94 0.9× 26 1.0k
Yousung Park South Korea 9 89 0.2× 18 0.1× 35 0.3× 188 1.7× 24 0.2× 41 772
V. Gilleron France 9 26 0.1× 251 1.2× 14 0.1× 147 1.3× 38 0.4× 23 591
Carla Moreira Portugal 15 139 0.3× 29 0.1× 58 0.5× 24 0.2× 8 0.1× 28 388
Hien Vu Australia 11 87 0.2× 16 0.1× 27 0.2× 34 0.3× 58 0.6× 22 676

Countries citing papers authored by Masoud Asgharian

Since Specialization
Citations

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

Fields of papers citing papers by Masoud Asgharian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masoud Asgharian

This figure shows the co-authorship network connecting the top 25 collaborators of Masoud Asgharian. A scholar is included among the top collaborators of Masoud Asgharian 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 Masoud Asgharian. Masoud Asgharian 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.
2.
Ghaffari, Alireza, Masoud Asgharian, & Yvon Savaria. (2023). Statistical Hardware Design With Multimodel Active Learning. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 43(2). 562–572. 3 indexed citations
3.
Oberman, Adam M., et al.. (2023). EuclidNets: An Alternative Operation for Efficient Inference of Deep Learning Models. SN Computer Science. 4(5). 2 indexed citations
4.
Doosti, Hassan, et al.. (2023). Uniform confidence bands for hazard functions from censored prevalent cohort survival data. Electronic Journal of Statistics. 17(2). 1 indexed citations
5.
Ghaffari, Alireza, et al.. (2023). Towards Fine-tuning Pre-trained Language Models with Integer Forward and Backward Propagation. 1912–1921. 2 indexed citations
6.
Zhang, Dongliang, Abbas Khalili, & Masoud Asgharian. (2022). Post-model-selection inference in linear regression models: An integrated review. 16(none). 20 indexed citations
7.
Heydari, Shahram, Masoud Asgharian, Frank J. Kelly, & Rahul Goel. (2022). Potential health benefits of eliminating traffic emissions in urban areas. PLoS ONE. 17(3). e0264803–e0264803. 3 indexed citations
8.
Asgharian, Masoud, et al.. (2017). Inference under biased sampling and right censoring for a change point in the hazard function. Bernoulli. 23(4A). 5 indexed citations
9.
Khalili, Abbas, et al.. (2016). Simultaneous variable selection and de-coarsening in multi-path change-point models. Journal of Multivariate Analysis. 147. 202–217. 1 indexed citations
10.
Ertefaie, Ashkan, Masoud Asgharian, & David A. Stephens. (2014). Propensity score estimation in the presence of length‐biased sampling: a non‐parametric adjustment approach. Stat. 3(1). 83–94. 4 indexed citations
11.
Eimar, Hazem, Benedetto Marelli, Showan N. Nazhat, et al.. (2013). Trace elements can influence the physical properties of tooth enamel. SpringerPlus. 2(1). 499–499. 60 indexed citations
12.
Carone, Marco, Masoud Asgharian, & Nicholas P. Jewell. (2013). Estimating the Lifetime Risk of Dementia in the Canadian Elderly Population Using Cross-Sectional Cohort Survival Data. Journal of the American Statistical Association. 109(505). 24–35. 26 indexed citations
13.
Ning, Jing, Jing Qin, Masoud Asgharian, & Yu Shen. (2012). Empirical likelihood‐based confidence intervals for length‐biased data. Statistics in Medicine. 32(13). 2278–2291. 7 indexed citations
14.
Carone, Marco, et al.. (2012). Nonparametric incidence estimation from prevalent cohort survival data. Biometrika. 99(3). 599–613. 7 indexed citations
15.
Noorbaloochi, Siamak, David Nelson, & Masoud Asgharian. (2010). Balancing and Elimination of Nuisance Variables. The International Journal of Biostatistics. 6(2). Article 6–Article 6. 3 indexed citations
16.
Asgharian, Masoud, et al.. (2008). Covariate Bias Induced by Length-Biased Sampling of Failure Times. Journal of the American Statistical Association. 103(482). 737–742. 33 indexed citations
17.
Asgharian, Masoud, David B. Wolfson, & Xun Zhang. (2005). Checking stationarity of the incidence rate using prevalent cohort survival data. Statistics in Medicine. 25(10). 1751–1767. 51 indexed citations
18.
Asgharian, Masoud & David B. Wolfson. (2005). Asymptotic behavior of the unconditional NPMLE of the length-biased survivor function from right censored prevalent cohort data. The Annals of Statistics. 33(5). 86 indexed citations
19.
Asgharian, Masoud, Cyr Emile M’lan, & David B. Wolfson. (2002). Length-Biased Sampling With Right Censoring. Journal of the American Statistical Association. 97(457). 201–209. 160 indexed citations
20.
Wolfson, Christina, David B. Wolfson, Masoud Asgharian, et al.. (2001). A Reevaluation of the Duration of Survival after the Onset of Dementia. New England Journal of Medicine. 344(15). 1111–1116. 405 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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