Hamid Shahriari

865 total citations
54 papers, 667 citations indexed

About

Hamid Shahriari is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability and Control and Systems Engineering. According to data from OpenAlex, Hamid Shahriari has authored 54 papers receiving a total of 667 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Statistics, Probability and Uncertainty, 28 papers in Statistics and Probability and 15 papers in Control and Systems Engineering. Recurrent topics in Hamid Shahriari's work include Advanced Statistical Process Monitoring (32 papers), Advanced Statistical Methods and Models (24 papers) and Optimal Experimental Design Methods (12 papers). Hamid Shahriari is often cited by papers focused on Advanced Statistical Process Monitoring (32 papers), Advanced Statistical Methods and Models (24 papers) and Optimal Experimental Design Methods (12 papers). Hamid Shahriari collaborates with scholars based in Iran, Indonesia and United States. Hamid Shahriari's co-authors include Abdollah Aghaie, Rasoul Shafaei, Mona Shahriari, Fu‐Kwun Wang, Norma F. Hubele, Adel Hatami‐Marbini, Seyed Taghi Akhavan Niaki, Per J. Agrell, Emad Roghanian and Hassan Sadeghi and has published in prestigious journals such as International Journal of Production Research, Reliability Engineering & System Safety and The International Journal of Advanced Manufacturing Technology.

In The Last Decade

Hamid Shahriari

50 papers receiving 644 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hamid Shahriari Iran	14	437	276	169	152	69	54	667
Su‐Fen Yang Taiwan	17	836 1.9×	485 1.8×	123 0.7×	201 1.3×	170 2.5×	74	1.0k
Bahram Sadeghpour Gildeh Iran	15	476 1.1×	395 1.4×	304 1.8×	103 0.7×	53 0.8×	96	702
John R. English United States	14	246 0.6×	103 0.4×	98 0.6×	86 0.6×	72 1.0×	48	613
Chao‐Yu Chou Taiwan	17	690 1.6×	324 1.2×	216 1.3×	99 0.7×	98 1.4×	82	850
Amitava Mukherjee India	23	1.4k 3.2×	954 3.5×	216 1.3×	343 2.3×	37 0.5×	101	1.6k
Muhammad Azam Pakistan	21	1.2k 2.8×	701 2.5×	416 2.5×	212 1.4×	85 1.2×	79	1.4k
Kerstin Vännman Sweden	16	713 1.6×	375 1.4×	316 1.9×	101 0.7×	16 0.2×	45	802
Majid Khedmati Iran	15	205 0.5×	114 0.4×	137 0.8×	140 0.9×	17 0.2×	56	571
Yanhong Wu United States	13	348 0.8×	293 1.1×	92 0.5×	53 0.3×	214 3.1×	54	617
Hashem Mahlooji Iran	12	116 0.3×	64 0.2×	82 0.5×	61 0.4×	32 0.5×	24	366

Countries citing papers authored by Hamid Shahriari

Since Specialization

Citations

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

Fields of papers citing papers by Hamid Shahriari

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hamid Shahriari

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

Shahriari, Hamid, et al.. (2024). Reliability modeling of systems with random failure threshold subjected to cumulative shocks using machine learning method. Quality and Reliability Engineering International. 40(5). 2547–2569. 6 indexed citations

Shahriari, Hamid, et al.. (2021). Robust process capability indices for multiple linear profiles. Quality and Reliability Engineering International. 37(8). 3568–3579. 14 indexed citations

Aghaie, Abdollah, et al.. (2020). Robust T² control chart using median‐based estimators. Quality and Reliability Engineering International. 36(6). 2187–2201. 10 indexed citations

Roghanian, Emad, et al.. (2020). Reliability optimization for non-repairable series-parallel systems with a choice of redundancy strategies and heterogeneous components: Erlang time-to-failure distribution. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability. 235(3). 509–528. 9 indexed citations

Shahriari, Hamid, et al.. (2018). A robust wavelet based profile monitoring and change point detection using S-estimator and clustering. Journal of industrial and systems engineering.. 11(3). 167–189. 5 indexed citations

Roghanian, Emad, et al.. (2017). Cold standby redundancy optimization for nonrepairable series-parallel systems: Erlang time to failure distribution. Journal of industrial and systems engineering.. 10. 1–16. 1 indexed citations

Shahriari, Hamid, et al.. (2016). Bayesian Estimation of Change Point in Phase One Risk Adjusted Control Charts. Journal of industrial and systems engineering.. 9(2). 20–37. 1 indexed citations

Shahriari, Hamid, et al.. (2015). Robust estimation of the mean vector for high-dimensional data set using robust clustering. Journal of Applied Statistics. 42(6). 1183–1205. 5 indexed citations

Shahriari, Hamid, et al.. (2014). An Integrated Model with Conservative Levels to Evaluate the DMUs Efficiencies for Uncertain Data. 5(1). 29–46. 2 indexed citations

10.

Shahriari, Hamid, et al.. (2014). Parameter Estimation of Autoregressive Models Using the Iteratively Robust Filtered Fast-τ Method. Communication in Statistics- Theory and Methods. 43(21). 4445–4470. 4 indexed citations

11.

Shahriari, Hamid, et al.. (2013). Robust Estimation of Parameters in Simple Linear Profiles Using M-Estimators. Communication in Statistics- Theory and Methods. 43(20). 4308–4323. 15 indexed citations

12.

Aghaie, Abdollah, et al.. (2012). Using frailty models to account for heterogeneity in multistage manufacturing and service processes. Quality & Quantity. 48(2). 593–604. 11 indexed citations

13.

Shahriari, Hamid, et al.. (2011). A two-step robust estimation of the process mean using M-estimator. Journal of Applied Statistics. 38(6). 1289–1301. 9 indexed citations

14.

Shahriari, Hamid, et al.. (2010). A ROBUST MULTI-OBJECTIVE LEAD TIME CONTROL PROBLEM IN COMPLEX ASSEMBLY SYSTEMS. 21(2). 23–35. 1 indexed citations

15.

Shahriari, Hamid, et al.. (2010). A Robust Optimization Approach to Resources Allocation in Maintained Systems. 21(1). 25–33. 1 indexed citations

16.

Shahriari, Hamid, et al.. (2010). A TWO-PHASE ROBUST ESTIMATION OF PROCESS DISPERSION USING M-ESTIMATOR. Journal of industrial and systems engineering.. 4(1). 47–58. 7 indexed citations

17.

Shahriari, Hamid, et al.. (2009). A ROBUST DISPERSION CONTROL CHART BASED ON M-ESTIMATE. Journal of industrial and systems engineering.. 2(4). 297–307. 22 indexed citations

18.

Shahriari, Hamid, et al.. (2009). INTERPRETATION OF MULTIVARIATE CONTROL CHART BASED ON PAIRED DECOMPOSITION OF T2. 20(1). 23–31. 1 indexed citations

19.

Aghaie, Abdollah, et al.. (2009). Monitoring dependent process steps using robust cause‐selecting control charts. Quality and Reliability Engineering International. 25(7). 851–874. 24 indexed citations

20.

Shahriari, Hamid. (2007). PRIVACY AND INFORMATION SOCIETY. 8(343132). 101–125.

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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