Ali Bashashati

18.4k total citations · 1 hit paper
83 papers, 3.8k citations indexed

About

Ali Bashashati is a scholar working on Cognitive Neuroscience, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Ali Bashashati has authored 83 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Cognitive Neuroscience, 22 papers in Molecular Biology and 21 papers in Artificial Intelligence. Recurrent topics in Ali Bashashati's work include EEG and Brain-Computer Interfaces (25 papers), Neuroscience and Neural Engineering (19 papers) and AI in cancer detection (19 papers). Ali Bashashati is often cited by papers focused on EEG and Brain-Computer Interfaces (25 papers), Neuroscience and Neural Engineering (19 papers) and AI in cancer detection (19 papers). Ali Bashashati collaborates with scholars based in Canada, United States and Australia. Ali Bashashati's co-authors include Gary E. Birch, Rabab Ward, Mehrdad Fatourechi, Sohrab P. Shah, Ryan R. Brinkman, S.G. Mason, Samuel Aparício, David G. Huntsman, Jiarui Ding and Gavin Ha and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Ali Bashashati

78 papers receiving 3.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals

2007 623 citations Ali Bashashati, Mehrdad Fatourechi et al. Journal of Neural Engineering profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ali Bashashati Canada	31	1.6k	1.3k	790	669	399	83	3.8k
Jung Kim United States	24	934 0.6×	1.5k 1.2×	773 1.0×	869 1.3×	28 0.1×	77	3.5k
Erik Peterson United States	32	1.7k 1.0×	738 0.6×	768 1.0×	137 0.2×	41 0.1×	97	4.4k
Kongming Wang United States	17	668 0.4×	405 0.3×	324 0.4×	113 0.2×	118 0.3×	39	2.7k
Michael D. Linderman United States	22	264 0.2×	927 0.7×	201 0.3×	167 0.2×	34 0.1×	45	2.4k
Takayuki Itoh Japan	35	56 0.0×	981 0.8×	521 0.7×	122 0.2×	237 0.6×	224	4.2k
Richard A. Young United States	26	438 0.3×	2.6k 2.1×	87 0.1×	203 0.3×	15 0.0×	103	4.1k
Shigeyuki Oba Japan	20	158 0.1×	667 0.5×	68 0.1×	381 0.6×	41 0.1×	53	1.6k
Dawei Dong United States	23	604 0.4×	717 0.6×	212 0.3×	274 0.4×	50 0.1×	55	1.7k
Young H. Kwon United States	39	308 0.2×	1.5k 1.2×	402 0.5×	60 0.1×	149 0.4×	151	5.5k
Xiaopei Liu China	19	614 0.4×	846 0.7×	778 1.0×	278 0.4×	8 0.0×	52	3.2k

Countries citing papers authored by Ali Bashashati

Since Specialization

Citations

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

Fields of papers citing papers by Ali Bashashati

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ali Bashashati

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Farnell, David, et al.. (2025). Benchmarking histopathology foundation models for ovarian cancer bevacizumab treatment response prediction from whole slide images. Discover Oncology. 16(1). 196–196. 1 indexed citations

Wang, Ching‐Wei, Yifan Li, Ali Bashashati, et al.. (2024). ATEC23 Challenge: Automated prediction of treatment effectiveness in ovarian cancer using histopathological images. Medical Image Analysis. 99. 103342–103342. 4 indexed citations

Farahani, Hossein, Maryam Asadi, Matthew O. Wiens, et al.. (2024). AI-based histopathology image analysis reveals a distinct subset of endometrial cancers. Nature Communications. 15(1). 4973–4973. 13 indexed citations

Zhang, Allen, Katy Milne, Steven J.M. Jones, et al.. (2024). VOLTA: an enVironment-aware cOntrastive ceLl represenTation leArning for histopathology. Nature Communications. 15(1). 3942–3942. 4 indexed citations

Karimi, Davood, Jane Wang, Ladan Fazli, et al.. (2024). Prostate Cancer Risk Stratification by Digital Histopathology and Deep Learning. JCO Clinical Cancer Informatics. 8(8). e2300184–e2300184. 4 indexed citations

Zhang, Allen, Alberto Contreras‐Sanz, Martin Köbel, et al.. (2024). Learning generalizable AI models for multi-center histopathology image classification. npj Precision Oncology. 8(1). 151–151. 12 indexed citations

Farahani, Hossein, et al.. (2024). Benchmarking bulk and single-cell variant-calling approaches on Chromium scRNA-seq and scATAC-seq libraries. Genome Research. 34(8). 1196–1210. 1 indexed citations

Bashashati, Ali, et al.. (2023). Artificial Intelligence and Pathomics. Urologic Clinics of North America. 51(1). 15–26. 12 indexed citations

Naso, Julia, Adrian Levine, Hossein Farahani, et al.. (2021). Deep-learning based classification distinguishes sarcomatoid malignant mesotheliomas from benign spindle cell mesothelial proliferations. Modern Pathology. 34(11). 2028–2035. 15 indexed citations

10.

Chafe, Shawn C., Paul C. McDonald, Saeed Saberi, et al.. (2019). Targeting Hypoxia-Induced Carbonic Anhydrase IX Enhances Immune-Checkpoint Blockade Locally and Systemically. Cancer Immunology Research. 7(7). 1064–1078. 126 indexed citations

11.

Araki, Shinsuke, Momoko Ohori, Amal M. El-Naggar, et al.. (2019). Pharmacological systems analysis defines EIF4A3 functions in cell-cycle and RNA stress granule formation. Communications Biology. 2(1). 165–165. 30 indexed citations

12.

Funnell, Tyler, Allen W. Zhang, Diljot Grewal, et al.. (2019). Integrated structural variation and point mutation signatures in cancer genomes using correlated topic models. PLoS Computational Biology. 15(2). e1006799–e1006799. 32 indexed citations

13.

Cybulska, Paulina, Arnaud Da Cruz Paula, Jill Tseng, et al.. (2019). Molecular profiling and molecular classification of endometrioid ovarian carcinomas. Gynecologic Oncology. 154(3). 516–523. 65 indexed citations

14.

Taghiyar, M. Jafar, Jamie Rosner, Diljot Grewal, et al.. (2017). Kronos: a workflow assembler for genome analytics and informatics. GigaScience. 6(7). 1–10. 5 indexed citations

15.

Cochrane, Dawn R., Michael S. Anglesio, Yi Kan Wang, et al.. (2017). LINE-1 retrotransposon-mediated DNA transductions in endometriosis associated ovarian cancers. Gynecologic Oncology. 147(3). 642–647. 13 indexed citations

16.

Ha, Gavin, Andrew Roth, Daniel Lai, et al.. (2012). Integrative analysis of genome-wide loss of heterozygosity and monoallelic expression at nucleotide resolution reveals disrupted pathways in triple-negative breast cancer. Genome Research. 22(10). 1995–2007. 152 indexed citations

17.

Bashashati, Ali, et al.. (2007). Effect of eye-blinks on a self-paced brain interface design. Clinical Neurophysiology. 118(7). 1639–1647. 10 indexed citations

18.

Bashashati, Ali, Mehrdad Fatourechi, Rabab Ward, & Gary E. Birch. (2007). A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals. Journal of Neural Engineering. 4(2). R32–R57. 623 indexed citations breakdown →

19.

Fatourechi, Mehrdad, Ali Bashashati, Rabab Ward, & Gary E. Birch. (2006). EMG and EOG artifacts in brain computer interface systems: A survey. Clinical Neurophysiology. 118(3). 480–494. 426 indexed citations

20.

Borisoff, Jaimie, S.G. Mason, Ali Bashashati, & Gary E. Birch. (2004). Brain–Computer Interface Design for Asynchronous Control Applications: Improvements to the LF-ASD Asynchronous Brain Switch. IEEE Transactions on Biomedical Engineering. 51(6). 985–992. 132 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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