Mohak Shah

1.2k total citations
24 papers, 545 citations indexed

About

Mohak Shah is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Mohak Shah has authored 24 papers receiving a total of 545 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 7 papers in Computer Networks and Communications and 5 papers in Information Systems. Recurrent topics in Mohak Shah's work include Data Stream Mining Techniques (5 papers), Machine Learning and Data Classification (5 papers) and IoT and Edge/Fog Computing (4 papers). Mohak Shah is often cited by papers focused on Data Stream Mining Techniques (5 papers), Machine Learning and Data Classification (5 papers) and IoT and Edge/Fog Computing (4 papers). Mohak Shah collaborates with scholars based in United States, Canada and South Korea. Mohak Shah's co-authors include Unmesh Kurup, Junyao Guo, Douglas L. Arnold, Tal Arbel, Simon Francis, D. Louis Collins, Yiming Xiao, Nagesh K. Subbanna, Samarth Tripathi and Jacques Corbeil and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Intelligent Transportation Systems and Journal of the Franklin Institute.

In The Last Decade

Mohak Shah

24 papers receiving 523 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mohak Shah United States	9	176	159	101	87	62	24	545
A. Ahilan India	15	195 1.1×	264 1.7×	97 1.0×	26 0.3×	101 1.6×	74	835
R. Joshua Samuel Raj India	8	132 0.8×	100 0.6×	111 1.1×	25 0.3×	56 0.9×	28	513
Raed Ibraheem Hamed Iraq	9	142 0.8×	155 1.0×	25 0.2×	48 0.6×	71 1.1×	10	536
Reza Azmi Iran	16	260 1.5×	260 1.6×	163 1.6×	34 0.4×	79 1.3×	86	709
Shabana Habib Saudi Arabia	17	288 1.6×	287 1.8×	183 1.8×	26 0.3×	46 0.7×	53	873
Siyamalan Manivannan Sri Lanka	13	217 1.2×	193 1.2×	111 1.1×	20 0.2×	145 2.3×	38	586
Jamal Riffi Morocco	16	216 1.2×	325 2.0×	54 0.5×	26 0.3×	108 1.7×	76	735
Md Sipon Miah Bangladesh	15	359 2.0×	160 1.0×	131 1.3×	19 0.2×	110 1.8×	64	835
Tianyu Shen China	12	197 1.1×	163 1.0×	19 0.2×	54 0.6×	104 1.7×	45	510
Hameedur Rahman Pakistan	13	195 1.1×	231 1.5×	69 0.7×	11 0.1×	115 1.9×	62	596

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

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

20 of 20 papers shown

1.

Shah, Mohak, et al.. (2021). Efficient Coverage Path Planning in Initially Unknown Environments Using Graph Representation. 1003–1010. 1 indexed citations

2.

Guo, Junyao, et al.. (2021). A Survey of On-Device Machine Learning. 2(3). 1–49. 84 indexed citations

3.

Shah, Mohak, et al.. (2021). Deep Reinforcement Learning Based Online Area Covering Autonomous Robot. 21–25. 7 indexed citations

4.

Cherkassky, Vladimir, et al.. (2019). Multiclass Learning from Contradictions. Neural Information Processing Systems. 32. 8400–8410. 6 indexed citations

5.

Liu, Jiayi, Samarth Tripathi, Unmesh Kurup, & Mohak Shah. (2019). Auptimizer - an Extensible, Open-Source Framework for Hyperparameter Tuning. 339–348. 8 indexed citations

6.

Guo, Junyao, Unmesh Kurup, & Mohak Shah. (2019). Is it Safe to Drive? An Overview of Factors, Metrics, and Datasets for Driveability Assessment in Autonomous Driving. IEEE Transactions on Intelligent Transportation Systems. 21(8). 3135–3151. 143 indexed citations

7.

Yu, Shujian, Zubin Abraham, Heng Wang, et al.. (2019). Concept drift detection and adaptation with hierarchical hypothesis testing. Journal of the Franklin Institute. 356(5). 3187–3215. 39 indexed citations

8.

Shah, Mohak, et al.. (2019). Dynamic Task Offloading in Multi-Agent Mobile Edge Computing Networks. 1–6. 24 indexed citations

9.

Ghani, Rayid, et al.. (2019). Solve for Good. ACM SIGKDD Explorations Newsletter. 21(2). 3–5. 1 indexed citations

10.

Hendawi, Abdeltawab, Ankur Teredesai, Naveen Ramakrishnan, et al.. (2019). Benchmarking large-scale data management for Internet of Things. The Journal of Supercomputing. 75(12). 8207–8230. 7 indexed citations

11.

Hendawi, Abdeltawab, et al.. (2018). Distributed NoSQL Data Stores: Performance Analysis and a Case Study. 1937–1944. 7 indexed citations

12.

Zhang, Shengdong, et al.. (2017). Deep learning on symbolic representations for large-scale heterogeneous time-series event prediction. 5970–5974. 15 indexed citations

13.

Ramakrishnan, Naveen, et al.. (2015). ADMM based scalable machine learning on Spark. 1174–1182. 10 indexed citations

14.

Deb, Budhaditya, et al.. (2013). Towards systems level prognostics in the Cloud. 1–6. 3 indexed citations

15.

Hamou‐Lhadj, Abdelwahab, et al.. (2011). Exploiting text mining techniques in the analysis of execution traces. 223–232. 14 indexed citations

16.

Shah, Mohak, Yiming Xiao, Nagesh K. Subbanna, et al.. (2010). Evaluating intensity normalization on MRIs of human brain with multiple sclerosis. Medical Image Analysis. 15(2). 267–282. 116 indexed citations

17.

Shah, Mohak, et al.. (2009). Hold-out Risk Bounds for Classifier Performance Evaluation. 2 indexed citations

18.

Shah, Mohak & Jacques Corbeil. (2009). A General Framework for Analyzing Data from Two Short Time-Series Microarray Experiments. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 8(1). 14–26. 6 indexed citations

19.

Shah, Mohak. (2008). Risk Bounds for Randomized Sample Compressed Classifiers. Neural Information Processing Systems. 21. 1449–1456. 1 indexed citations

20.

Shah, Mohak, Marina Sokolova, & Stan Śzpakowicz. (2006). Process-Specific Information for Learning Electronic Negotiation Outcomes. Fundamenta Informaticae. 74(2-3). 351–373. 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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