Ali Lashkaripour

784 total citations
21 papers, 596 citations indexed

About

Ali Lashkaripour is a scholar working on Biomedical Engineering, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Ali Lashkaripour has authored 21 papers receiving a total of 596 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Biomedical Engineering, 11 papers in Electrical and Electronic Engineering and 3 papers in Artificial Intelligence. Recurrent topics in Ali Lashkaripour's work include Innovative Microfluidic and Catalytic Techniques Innovation (13 papers), Microfluidic and Capillary Electrophoresis Applications (11 papers) and Electrowetting and Microfluidic Technologies (9 papers). Ali Lashkaripour is often cited by papers focused on Innovative Microfluidic and Catalytic Techniques Innovation (13 papers), Microfluidic and Capillary Electrophoresis Applications (11 papers) and Electrowetting and Microfluidic Technologies (9 papers). Ali Lashkaripour collaborates with scholars based in United States, Iran and Canada. Ali Lashkaripour's co-authors include Douglas Densmore, David McIntyre, Luis Ortiz, Masoud Goharimanesh, Polly M. Fordyce, Ali Abouei Mehrizi, Noushin Mehdipour, Joshua D. Campbell, Sajad Razavi Bazaz and Ali Akbar Akbari and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Lab on a Chip.

In The Last Decade

Ali Lashkaripour

20 papers receiving 581 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ali Lashkaripour United States 12 497 242 51 42 37 21 596
N. Sujatha India 12 139 0.3× 62 0.3× 13 0.3× 29 0.7× 12 0.3× 60 366
Daniel Stoecklein United States 10 293 0.6× 101 0.4× 18 0.4× 36 0.9× 11 0.3× 12 404
Xinchi Zhou China 8 71 0.1× 171 0.7× 68 1.3× 18 0.4× 46 1.2× 17 524
Carmen Aracil Spain 11 198 0.4× 151 0.6× 24 0.5× 14 0.3× 21 0.6× 33 325
Junho Cho South Korea 14 38 0.1× 174 0.7× 41 0.8× 16 0.4× 31 0.8× 39 507
Xiumei Zhang China 11 71 0.1× 109 0.5× 22 0.4× 24 0.6× 35 0.9× 48 392
Pei Yang China 10 79 0.2× 184 0.8× 19 0.4× 37 0.9× 27 0.7× 33 322
Che-Ming Chang Taiwan 11 112 0.2× 79 0.3× 9 0.2× 59 1.4× 37 1.0× 30 329
Xiaoming He China 8 162 0.3× 59 0.2× 11 0.2× 86 2.0× 50 1.4× 13 334
Takeshi Hashimoto Japan 12 69 0.1× 333 1.4× 63 1.2× 21 0.5× 27 0.7× 71 537

Countries citing papers authored by Ali Lashkaripour

Since Specialization
Citations

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

Fields of papers citing papers by Ali Lashkaripour

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ali Lashkaripour

This figure shows the co-authorship network connecting the top 25 collaborators of Ali Lashkaripour. A scholar is included among the top collaborators of Ali Lashkaripour 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 Ali Lashkaripour. Ali Lashkaripour 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.
Lashkaripour, Ali, et al.. (2024). Design automation of microfluidic single and double emulsion droplets with machine learning. Nature Communications. 15(1). 83–83. 35 indexed citations
2.
McIntyre, David, et al.. (2023). Versatility and stability optimization of flow-focusing droplet generators via quality metric-driven design automation. Lab on a Chip. 23(23). 4997–5008. 4 indexed citations
3.
McIntyre, David, Ali Lashkaripour, Polly M. Fordyce, & Douglas Densmore. (2022). Machine learning for microfluidic design and control. Lab on a Chip. 22(16). 2925–2937. 97 indexed citations
4.
Lashkaripour, Ali, Noushin Mehdipour, David McIntyre, et al.. (2021). Machine learning enables design automation of microfluidic flow-focusing droplet generation. Nature Communications. 12(1). 25–25. 156 indexed citations
5.
McIntyre, David, Ali Lashkaripour, & Douglas Densmore. (2020). Active learning for efficient microfluidic design automation. OpenBU (Boston University). 1 indexed citations
6.
McIntyre, David, Ali Lashkaripour, & Douglas Densmore. (2020). Rapid and inexpensive microfluidic electrode integration with conductive ink. Lab on a Chip. 20(20). 3690–3695. 18 indexed citations
7.
Lashkaripour, Ali, et al.. (2019). Modular microfluidic design automation using machine learning. OpenBU/Boston University Institutional Repository (Boston University). 1 indexed citations
8.
Lashkaripour, Ali, et al.. (2018). SIZE-CONTROLLED DROPLET GENERATION IN A MICROFLUIDIC DEVICE FOR RARE DNA AMPLIFICATION BY OPTIMIZING ITS EFFECTIVE PARAMETERS. Journal of Mechanics in Medicine and Biology. 18(1). 1850002–1850002. 16 indexed citations
9.
Lashkaripour, Ali, et al.. (2018). Desktop micromilled microfluidics. Microfluidics and Nanofluidics. 22(3). 42 indexed citations
10.
Lashkaripour, Ali, Masoud Goharimanesh, Ali Abouei Mehrizi, & Douglas Densmore. (2018). An adaptive neural-fuzzy approach for microfluidic droplet size prediction. Microelectronics Journal. 78. 73–80. 20 indexed citations
11.
Ortiz, Luis, Ali Lashkaripour, & Douglas Densmore. (2018). Automating functional enzyme screening & characterization. 1 indexed citations
12.
Mehrizi, Ali Abouei, et al.. (2018). Multi-criteria optimization of curved and baffle-embedded micromixers for bio-applications. Chemical Engineering and Processing - Process Intensification. 132. 175–186. 39 indexed citations
13.
Lashkaripour, Ali, et al.. (2017). Function-driven, graphical design tool for microfluidic chips: 3DuF. OpenBU/Boston University Institutional Repository (Boston University). 1 indexed citations
14.
Lashkaripour, Ali, et al.. (2017). Design automation based on fluid dynamics. OpenBU/Boston University Institutional Repository (Boston University). 3 indexed citations
15.
Goharimanesh, Masoud, Ali Lashkaripour, & Ali Akbar Akbari. (2016). Optimization of Biodiesel Production Using Multi-Objective Genetic Algorithm. 19(2). 117–124. 6 indexed citations
16.
Mehrizi, Ali Abouei, et al.. (2015). Numerical Study on Low Reynolds Mixing ofT-Shaped Micro-Mixers with Obstacles. SHILAP Revista de lepidopterología. 21 indexed citations
17.
Lashkaripour, Ali, et al.. (2015). Numerical Study of Droplet Generation Process in a Microfluidic Flow Focusing. Applied and Computational Mechanics. 46(2). 167–175. 8 indexed citations
18.
Goharimanesh, Masoud, Ali Lashkaripour, & Ali Abouei Mehrizi. (2015). Fractional Order PID Controller for Diabetes Patients. Applied and Computational Mechanics. 46(1). 69–76. 17 indexed citations
19.
Goharimanesh, Masoud, Ali Lashkaripour, & Ali Akbar Akbari. (2015). A Comparison of Fuzzy Type s 1 and 2 in Diabetics Control, Based on Augmented Minimal Model. 4. 2 indexed citations
20.
Goharimanesh, Masoud, et al.. (2014). Diabetic Control Using Genetic Fuzzy-PI Controller. International Journal of Fuzzy Systems. 16. 24 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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