Mohak Shah

1.6k total citations · 2 hit papers
10 papers, 1.0k citations indexed

About

Mohak Shah is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Mohak Shah has authored 10 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Molecular Biology. Recurrent topics in Mohak Shah's work include Machine Learning and Algorithms (3 papers), Imbalanced Data Classification Techniques (3 papers) and Machine Learning and Data Classification (3 papers). Mohak Shah is often cited by papers focused on Machine Learning and Algorithms (3 papers), Imbalanced Data Classification Techniques (3 papers) and Machine Learning and Data Classification (3 papers). Mohak Shah collaborates with scholars based in Canada, United States and Poland. Mohak Shah's co-authors include Nathalie Japkowicz, Mario Marchand, Marina Sokolova, Stan Śzpakowicz, Zahra Karimaghaloo, Douglas L. Arnold, D. Louis Collins, Tal Arbel, Simon J. Francis and François Laviolette and has published in prestigious journals such as Lecture notes in computer science, Group Decision and Negotiation and ePrints Soton (University of Southampton).

In The Last Decade

Mohak Shah

10 papers receiving 995 citations

Hit Papers

Evaluating Learning Algorithms 2011 2026 2016 2021 2011 2011 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohak Shah Canada 7 502 129 127 103 81 10 1.0k
Ioannis D. Zaharakis Greece 9 375 0.7× 124 1.0× 175 1.4× 82 0.8× 84 1.0× 16 1.2k
Shamila Nasreen Pakistan 6 377 0.8× 161 1.2× 92 0.7× 70 0.7× 92 1.1× 7 877
Fethi Jarray Tunisia 7 312 0.6× 95 0.7× 78 0.6× 151 1.5× 55 0.7× 24 937
Jose G. Moreno-Torres Spain 6 717 1.4× 156 1.2× 120 0.9× 54 0.5× 79 1.0× 8 1.1k
Harry Zhang United States 16 732 1.5× 149 1.2× 232 1.8× 106 1.0× 86 1.1× 39 1.6k
Andrea Danyluk United States 11 640 1.3× 277 2.1× 172 1.4× 131 1.3× 85 1.0× 31 1.3k
Basabi Chakraborty Japan 17 522 1.0× 241 1.9× 99 0.8× 57 0.6× 147 1.8× 131 1.0k
Fang Han United States 15 457 0.9× 102 0.8× 82 0.6× 238 2.3× 102 1.3× 50 1.7k
Chongsheng Zhang China 14 487 1.0× 264 2.0× 139 1.1× 51 0.5× 63 0.8× 44 1.0k

Countries citing papers authored by Mohak Shah

Since Specialization
Citations

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

Fields of papers citing papers by Mohak Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohak Shah

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

All Works

10 of 10 papers shown
1.
Shah, Mohak, et al.. (2021). Online Area Covering Robot in Unknown Dynamic Environments. 38–42. 6 indexed citations
2.
Shah, Mohak, et al.. (2016). An architecture for the deployment of statistical models for the big data era. 1377–1384. 10 indexed citations
3.
Japkowicz, Nathalie & Mohak Shah. (2011). Evaluating Learning Algorithms: A Classification Perspective. Medical Entomology and Zoology. 478 indexed citations breakdown →
4.
Japkowicz, Nathalie & Mohak Shah. (2011). Evaluating Learning Algorithms. Cambridge University Press eBooks. 504 indexed citations breakdown →
5.
Karimaghaloo, Zahra, Mohak Shah, Simon J. Francis, et al.. (2010). Detection of Gad-Enhancing Lesions in Multiple Sclerosis Using Conditional Random Fields. Lecture notes in computer science. 13(Pt 3). 41–48. 9 indexed citations
6.
Shah, Mohak. (2007). Sample compression bounds for decision trees. 799–806. 5 indexed citations
7.
Sokolova, Marina, Mohak Shah, & Stan Śzpakowicz. (2006). Comparative Analysis of Text Data in Successful Face-to-Face and Electronic Negotiations. Group Decision and Negotiation. 15(2). 127–140. 8 indexed citations
8.
Laviolette, François, Mario Marchand, & Mohak Shah. (2005). A PAC-Bayes approach to the Set Covering Machine. Neural Information Processing Systems. 18. 731–738. 3 indexed citations
9.
Marchand, Mario & Mohak Shah. (2004). PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data. Neural Information Processing Systems. 17. 881–888. 9 indexed citations
10.
Marchand, Mario, Mohak Shah, John Shawe‐Taylor, & Marina Sokolova. (2003). The set covering machine with data-dependent half-spaces. ePrints Soton (University of Southampton). 520–527. 5 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026