Siham Hachi

756 total citations
9 papers, 548 citations indexed

About

Siham Hachi is a scholar working on Biomedical Engineering, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Siham Hachi has authored 9 papers receiving a total of 548 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Biomedical Engineering, 4 papers in Molecular Biology and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Siham Hachi's work include Neuroscience and Neural Engineering (3 papers), Pluripotent Stem Cells Research (3 papers) and 3D Printing in Biomedical Research (3 papers). Siham Hachi is often cited by papers focused on Neuroscience and Neural Engineering (3 papers), Pluripotent Stem Cells Research (3 papers) and 3D Printing in Biomedical Research (3 papers). Siham Hachi collaborates with scholars based in Luxembourg, France and Netherlands. Siham Hachi's co-authors include Ronan M. T. Fleming, Edinson Lucumi Moreno, Jens C. Schwamborn, Kathrin Hemmer, Javier Jarazo, Anna S. Monzel, Jonas Walter, Silvia Bolognin, Ibrahim Boussaad and Emanuel Berger and has published in prestigious journals such as Scientific Reports, Lab on a Chip and Stem Cell Reports.

In The Last Decade

Siham Hachi

8 papers receiving 542 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Siham Hachi Luxembourg	5	325	307	193	93	63	9	548
Edinson Lucumi Moreno Luxembourg	8	421 1.3×	366 1.2×	256 1.3×	108 1.2×	109 1.7×	8	724
Lisa M. Smits Luxembourg	8	416 1.3×	194 0.6×	253 1.3×	124 1.3×	139 2.2×	10	630
Marcella Birtele Sweden	14	357 1.1×	167 0.5×	199 1.0×	134 1.4×	55 0.9×	23	576
George M. Gibbons United Kingdom	5	403 1.2×	189 0.6×	188 1.0×	133 1.4×	104 1.7×	8	653
Julie Lévi‐Strauss France	4	443 1.4×	218 0.7×	128 0.7×	146 1.6×	26 0.4×	9	600
Magdalena Sutcliffe United Kingdom	5	570 1.8×	252 0.8×	185 1.0×	188 2.0×	31 0.5×	7	796
Alexander William Phillips Austria	5	426 1.3×	267 0.9×	138 0.7×	124 1.3×	20 0.3×	7	599
Sarah Nickels Luxembourg	12	359 1.1×	163 0.5×	209 1.1×	114 1.2×	161 2.6×	16	633
Nicolas Daviaud United States	8	264 0.8×	107 0.3×	145 0.8×	130 1.4×	29 0.5×	11	463
Daniel Reumann Austria	8	584 1.8×	312 1.0×	161 0.8×	153 1.6×	35 0.6×	11	840

Countries citing papers authored by Siham Hachi

Since Specialization

Citations

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

Fields of papers citing papers by Siham Hachi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Siham Hachi

This figure shows the co-authorship network connecting the top 25 collaborators of Siham Hachi. A scholar is included among the top collaborators of Siham Hachi 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 Siham Hachi. Siham Hachi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

Hachi, Siham, et al.. (2024). Development of an Explainable AI (XAI) system for the interpretation of ViT in the diagnosis of medical images. 1–8.

Moreno, Edinson Lucumi, Siham Hachi, Javier Jarazo, et al.. (2019). Automated microfluidic cell culture of stem cell derived dopaminergic neurons. Scientific Reports. 9(1). 1796–1796. 84 indexed citations

Moreno, Edinson Lucumi, Siham Hachi, Roland Sanctuary, et al.. (2018). Determination of the rheological properties of Matrigel for optimum seeding conditions in microfluidic cell cultures. AIP Advances. 8(12). 30 indexed citations

Monzel, Anna S., Lisa M. Smits, Kathrin Hemmer, et al.. (2017). Derivation of Human Midbrain-Specific Organoids from Neuroepithelial Stem Cells. Stem Cell Reports. 8(5). 1144–1154. 304 indexed citations

Lazard, Diane S., Muriel Lefort, Siham Hachi, et al.. (2017). Sonographic Dynamic Description of the Laryngeal Tract: Definition of Quantitative Measures to Characterize Vocal Fold Motion and Estimation of Their Normal Values. Journal of Ultrasound in Medicine. 36(5). 1037–1044. 4 indexed citations

Mao, Longfei, et al.. (2015). A constraint-based modelling approach to metabolic dysfunction in Parkinson's disease. Computational and Structural Biotechnology Journal. 13. 484–491. 6 indexed citations

Lefort, Muriel, Siham Hachi, Andrew Li, et al.. (2015). Detection of recurrent nerve paralysis: Development of a Computer Aided Diagnosis system. IRBM. 36(6). 367–374. 4 indexed citations

Lefort, Muriel, Siham Hachi, Ang Li, et al.. (2015). Quantification of vocal fold motion using echography: application to recurrent nerve paralysis detection. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9414. 94142M–94142M. 1 indexed citations

Moreno, Edinson Lucumi, Siham Hachi, Kathrin Hemmer, et al.. (2015). Differentiation of neuroepithelial stem cells into functional dopaminergic neurons in 3D microfluidic cell culture. Lab on a Chip. 15(11). 2419–2428. 115 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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