Mohammadjafar Hadad

2.3k total citations
47 papers, 1.8k citations indexed

About

Mohammadjafar Hadad is a scholar working on Mechanical Engineering, Biomedical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Mohammadjafar Hadad has authored 47 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Mechanical Engineering, 30 papers in Biomedical Engineering and 29 papers in Electrical and Electronic Engineering. Recurrent topics in Mohammadjafar Hadad's work include Advanced machining processes and optimization (39 papers), Advanced Surface Polishing Techniques (30 papers) and Advanced Machining and Optimization Techniques (28 papers). Mohammadjafar Hadad is often cited by papers focused on Advanced machining processes and optimization (39 papers), Advanced Surface Polishing Techniques (30 papers) and Advanced Machining and Optimization Techniques (28 papers). Mohammadjafar Hadad collaborates with scholars based in Iran, Germany and Qatar. Mohammadjafar Hadad's co-authors include Behzad Sadeghi, Taghi Tawakoli, M. H. Sadeghi, Mohammad Sadeghi, Farshad Rabiei, Abdolreza Rahimi, Amir Daneshi, Mohsen Davazdah Emami, M. Hossein Sehhat and Farshid Jafarian and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and International Journal of Machine Tools and Manufacture.

In The Last Decade

Mohammadjafar Hadad

44 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammadjafar Hadad Iran 20 1.8k 1.1k 1.0k 217 152 47 1.8k
Luiz Eduardo de Ângelo Sanchez Brazil 24 1.5k 0.8× 1.1k 1.0× 960 1.0× 193 0.9× 121 0.8× 97 1.6k
Taghi Tawakoli Germany 20 2.0k 1.1× 1.2k 1.1× 1.5k 1.5× 166 0.8× 147 1.0× 54 2.1k
Raju Pawade India 17 1.4k 0.8× 888 0.8× 722 0.7× 168 0.8× 215 1.4× 78 1.5k
José Cláudio Lopes Brazil 29 1.7k 1.0× 1.3k 1.1× 1.1k 1.1× 143 0.7× 129 0.8× 74 1.7k
C.C. Tsao Taiwan 17 1.4k 0.8× 1.1k 1.0× 936 0.9× 95 0.4× 151 1.0× 25 1.5k
Durul Ulutan United States 20 2.1k 1.2× 1.1k 1.0× 1.2k 1.2× 315 1.5× 289 1.9× 34 2.2k
D. Chakradhar India 25 1.6k 0.9× 1.0k 0.9× 651 0.6× 441 2.0× 150 1.0× 68 1.8k
Ulvi Şeker Türkiye 21 1.4k 0.8× 735 0.6× 650 0.6× 291 1.3× 181 1.2× 89 1.6k
Anders Wretland Sweden 20 1.1k 0.6× 595 0.5× 538 0.5× 243 1.1× 118 0.8× 44 1.3k
Wisley Falco Sales Brazil 22 1.5k 0.9× 838 0.7× 653 0.7× 313 1.4× 175 1.2× 41 1.7k

Countries citing papers authored by Mohammadjafar Hadad

Since Specialization
Citations

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

Fields of papers citing papers by Mohammadjafar Hadad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammadjafar Hadad

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammadjafar Hadad. A scholar is included among the top collaborators of Mohammadjafar Hadad 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 Mohammadjafar Hadad. Mohammadjafar Hadad 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
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Hadad, Mohammadjafar, et al.. (2025). Applying Acoustic Signals to Monitor Hybrid Electrical Discharge-Turning with Artificial Neural Networks. Micromachines. 16(3). 274–274.
3.
Hadad, Mohammadjafar, et al.. (2024). Exploring New Parameters to Advance Surface Roughness Prediction in Grinding Processes for the Enhancement of Automated Machining. Journal of Manufacturing and Materials Processing. 8(1). 41–41. 13 indexed citations
4.
Soleymani, Mehdi, et al.. (2024). Multilabel artificial intelligence model for online monitoring of electrical discharge turning by audio-based signals. The International Journal of Advanced Manufacturing Technology. 136(3-4). 1467–1482.
5.
Javadi, M., et al.. (2024). Predicting Surface Roughness and Grinding Forces in UNS S34700 Steel Grinding: A Machine Learning and Genetic Algorithm Approach to Coolant Effects. SHILAP Revista de lepidopterología. 4(4). 495–523. 11 indexed citations
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Sehhat, M. Hossein, et al.. (2022). Formability Investigation for Perforated Steel Sheets. SAE International Journal of Materials and Manufacturing. 15(2). 175–186. 8 indexed citations
11.
Hadad, Mohammadjafar, et al.. (2021). Experimental investigation of the effects of dressing and coolant-lubricant conditions on grinding of Nickel-based superalloy-Inconel 738. Environmental Engineering Science. 9(1). 27–36. 2 indexed citations
12.
Hadad, Mohammadjafar, Seyed Mohammad Ebrahimi, & Alireza Araee. (2021). Experimental and numerical investigation of the effects of preheating temperature on cutting force, chip shape and surface roughness in hot turning of AISI630 hardened stainless steel. Environmental Engineering Science. 9(2). 145–158. 2 indexed citations
13.
Hadad, Mohammadjafar, et al.. (2020). Investigation and comparison of the effect of graphene nanoplates and carbon nanotubes on the improvement of mechanical properties in the stir casting process of aluminum matrix nanocomposites. The International Journal of Advanced Manufacturing Technology. 109(9-12). 2535–2547. 9 indexed citations
14.
Hadad, Mohammadjafar, et al.. (2019). Towards sustainable machining of 17-4 PH stainless steel using hybrid MQL-hot turning process. Environmental Engineering Science. 7(4). 339–352. 2 indexed citations
15.
Ebrahimi, Seyed Mohammad, Alireza Araee, & Mohammadjafar Hadad. (2019). Investigation of the effects of constitutive law on numerical analysis of turning processes to predict the chip morphology, tool temperature, and cutting force. The International Journal of Advanced Manufacturing Technology. 105(10). 4245–4264. 20 indexed citations
16.
Ahmadi, Pouria, et al.. (2019). Environmental Impact Assessment of replacing Conventional Taxis with Hybrid Electric Vehicles in Tehran, Iran. 9(4). 3125–3131. 1 indexed citations
17.
Hadad, Mohammadjafar, et al.. (2017). Experimental investigation of the effects of tool initial surface roughness on the electrical discharge machining (EDM) performance. The International Journal of Advanced Manufacturing Technology. 95(5-8). 2093–2104. 28 indexed citations
18.
Hadad, Mohammadjafar, et al.. (2016). Thermal Aspects of Environmentally Friendly-MQL Grinding Process. Procedia CIRP. 40. 509–515. 43 indexed citations
19.
Rabiei, Farshad, et al.. (2014). Performance improvement of minimum quantity lubrication (MQL) technique in surface grinding by modeling and optimization. Journal of Cleaner Production. 86. 447–460. 116 indexed citations
20.
Rabiei, Farshad, et al.. (2013). INVESTIGATION OF THE EFFECT OF MINIMUM QUANTITY LUBRICATION TECHNIQUE ON PERFORMANCE OF THE GRINDING OF HSS. 13(4). 1–12. 3 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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