Azadeh Haghighi

753 total citations
26 papers, 529 citations indexed

About

Azadeh Haghighi is a scholar working on Industrial and Manufacturing Engineering, Mechanical Engineering and Automotive Engineering. According to data from OpenAlex, Azadeh Haghighi has authored 26 papers receiving a total of 529 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Industrial and Manufacturing Engineering, 18 papers in Mechanical Engineering and 17 papers in Automotive Engineering. Recurrent topics in Azadeh Haghighi's work include Additive Manufacturing and 3D Printing Technologies (17 papers), Manufacturing Process and Optimization (15 papers) and Additive Manufacturing Materials and Processes (12 papers). Azadeh Haghighi is often cited by papers focused on Additive Manufacturing and 3D Printing Technologies (17 papers), Manufacturing Process and Optimization (15 papers) and Additive Manufacturing Materials and Processes (12 papers). Azadeh Haghighi collaborates with scholars based in United States, Sweden and United Kingdom. Azadeh Haghighi's co-authors include Lihui Wang, Yiran Yang, Mohammad Givehchi, Lin Li, Mohammad Reza Khosravani, Lin Li, Wei Ji, Meysam Faegh, Sarah J. Wolff and Benjamin Gould and has published in prestigious journals such as Sustainability, Additive manufacturing and Journal of Manufacturing Systems.

In The Last Decade

Azadeh Haghighi

23 papers receiving 505 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Azadeh Haghighi United States 13 323 281 268 85 35 26 529
Li Yi Germany 13 360 1.1× 212 0.8× 241 0.9× 55 0.6× 20 0.6× 52 572
Hyunwoong Ko United States 10 246 0.8× 279 1.0× 309 1.2× 38 0.4× 11 0.3× 23 451
Moritz Glatt Germany 15 426 1.3× 151 0.5× 133 0.5× 58 0.7× 39 1.1× 68 641
Uzair Khaleeq uz Zaman Pakistan 11 313 1.0× 207 0.7× 281 1.0× 76 0.9× 15 0.4× 45 563
Yufan Zheng Canada 13 226 0.7× 162 0.6× 191 0.7× 49 0.6× 33 0.9× 23 466
Anhua Peng China 7 139 0.4× 153 0.5× 167 0.6× 29 0.3× 44 1.3× 16 342
Christopher Sacco United States 8 288 0.9× 161 0.6× 95 0.4× 36 0.4× 43 1.2× 10 573
Cezary Grabowik Poland 11 358 1.1× 234 0.8× 212 0.8× 51 0.6× 19 0.5× 67 566
Khaled Benfriha France 12 177 0.5× 149 0.5× 231 0.9× 70 0.8× 26 0.7× 51 398
Yann Ledoux France 13 184 0.6× 225 0.8× 123 0.5× 34 0.4× 15 0.4× 41 417

Countries citing papers authored by Azadeh Haghighi

Since Specialization
Citations

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

Fields of papers citing papers by Azadeh Haghighi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Azadeh Haghighi

This figure shows the co-authorship network connecting the top 25 collaborators of Azadeh Haghighi. A scholar is included among the top collaborators of Azadeh Haghighi 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 Azadeh Haghighi. Azadeh Haghighi 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.
Hebert, Rainer J., et al.. (2024). Towards intelligent cooperative robotics in additive manufacturing: Past, present, and future. Robotics and Computer-Integrated Manufacturing. 93. 102925–102925. 13 indexed citations
3.
Faegh, Meysam & Azadeh Haghighi. (2024). Generative Adversarial Networks With Domain Knowledge Fusion for Metal Additive Manufacturing. 1 indexed citations
4.
Faegh, Meysam, et al.. (2024). A review on physics-informed machine learning for process-structure-property modeling in additive manufacturing. Journal of Manufacturing Processes. 133. 524–555. 13 indexed citations
5.
Haghighi, Azadeh, et al.. (2024). Kinematics-guided data-driven energy surrogate model for robotic additive manufacturing. Manufacturing Letters. 41. 133–142.
6.
Mohammed, Abdullah, et al.. (2023). Energy-efficient and quality-aware part placement in robotic additive manufacturing. Journal of Manufacturing Systems. 68. 644–650. 10 indexed citations
7.
Faegh, Meysam, et al.. (2023). Architecture-Driven Physics-Informed Deep Learning for Temperature Prediction in Laser Powder Bed Fusion Additive Manufacturing With Limited Data. Journal of Manufacturing Science and Engineering. 145(8). 14 indexed citations
8.
9.
Khosravani, Mohammad Reza & Azadeh Haghighi. (2022). Large-Scale Automated Additive Construction: Overview, Robotic Solutions, Sustainability, and Future Prospect. Sustainability. 14(15). 9782–9782. 48 indexed citations
10.
Gould, Benjamin, et al.. (2021). Model-based deep learning for additive manufacturing: New frontiers and applications. Manufacturing Letters. 29. 94–98. 6 indexed citations
11.
Haghighi, Azadeh, Abdullah Mohammed, & Lihui Wang. (2021). Energy Efficient Multi-Robotic 3D Printing for Large-Scale Construction – Framework, Challenges, and a Systematic Approach. ORCA Online Research @Cardiff (Cardiff University). 4 indexed citations
12.
Haghighi, Azadeh & Lin Li. (2020). A hybrid physics-based and data-driven approach for characterizing porosity variation and filament bonding in extrusion-based additive manufacturing. Additive manufacturing. 36. 101399–101399. 22 indexed citations
13.
Li, Lin, Azadeh Haghighi, & Yiran Yang. (2018). Theoretical modelling and prediction of surface roughness for hybrid additive–subtractive manufacturing processes. IISE Transactions. 51(2). 124–135. 26 indexed citations
14.
Haghighi, Azadeh & Lin Li. (2018). Study of the relationship between dimensional performance and manufacturing cost in fused deposition modeling. Rapid Prototyping Journal. 24(2). 395–408. 26 indexed citations
15.
Ji, Wei, Lihui Wang, Azadeh Haghighi, Mohammad Givehchi, & Xianli Liu. (2017). An enriched machining feature based approach to cutting tool selection. International Journal of Computer Integrated Manufacturing. 31(1). 1–10. 25 indexed citations
16.
Givehchi, Mohammad, Azadeh Haghighi, & Lihui Wang. (2016). Cloud-DPP for distributed process planning of mill-turn machining operations. Robotics and Computer-Integrated Manufacturing. 47. 76–84. 17 indexed citations
17.
Ji, Wei, Lihui Wang, Azadeh Haghighi, Mohammad Givehchi, & Xianli Liu. (2016). A reachability based approach for machining feature sequencing. Journal of Manufacturing Systems. 40. 96–104. 20 indexed citations
18.
Wang, Lihui & Azadeh Haghighi. (2016). Combined strength of holons, agents and function blocks in cyber-physical systems. Journal of Manufacturing Systems. 40. 25–34. 90 indexed citations
19.
Givehchi, Mohammad, Azadeh Haghighi, & Lihui Wang. (2015). Adaptive Distributed Process Planning and Executions for Multi-tasking Machining Centers with Special Functionalities. 2. 288–295. 2 indexed citations
20.
Haghighi, Azadeh, et al.. (2011). A Multi-Objective Optimization Model To TheIntegrating Flexible Process Planning AndScheduling Based On Modified Particle SwarmOptimization Algorithm (Mpso). Zenodo (CERN European Organization for Nuclear Research). 1 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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