Rajesh Parekh

1.1k total citations
34 papers, 604 citations indexed

About

Rajesh Parekh is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Rajesh Parekh has authored 34 papers receiving a total of 604 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 8 papers in Information Systems and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Rajesh Parekh's work include Neural Networks and Applications (11 papers), Data Mining Algorithms and Applications (6 papers) and Machine Learning and Algorithms (5 papers). Rajesh Parekh is often cited by papers focused on Neural Networks and Applications (11 papers), Data Mining Algorithms and Applications (6 papers) and Machine Learning and Algorithms (5 papers). Rajesh Parekh collaborates with scholars based in United States, India and France. Rajesh Parekh's co-authors include Vasant Honavar, Jihoon Yang, Ron Kohavi, Zijian Zheng, Llew Mason, Vineet Chaoji, Rushi Bhatt, Angela Han, Jihoon Yang and Andrew Hatch and has published in prestigious journals such as Machine Learning, Advances in Therapy and Ophthalmology and Therapy.

In The Last Decade

Rajesh Parekh

31 papers receiving 544 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rajesh Parekh United States	13	324	146	92	82	54	34	604
Atsuyoshi Nakamura Japan	8	129 0.4×	152 1.0×	48 0.5×	80 1.0×	52 1.0×	47	384
Bharat Bhasker India	10	191 0.6×	240 1.6×	58 0.6×	39 0.5×	87 1.6×	40	464
Shourya Roy India	16	581 1.8×	269 1.8×	112 1.2×	22 0.3×	39 0.7×	57	789
Anthony J.T. Lee Taiwan	16	200 0.6×	282 1.9×	100 1.1×	38 0.5×	78 1.4×	33	622
Georges Dupret United States	14	283 0.9×	553 3.8×	142 1.5×	41 0.5×	70 1.3×	28	818
Igor V. Cadez United States	6	231 0.7×	221 1.5×	79 0.9×	28 0.3×	15 0.3×	12	495
Tengjiao Wang China	14	405 1.3×	184 1.3×	87 0.9×	19 0.2×	50 0.9×	61	755
Sang‐goo Lee South Korea	16	490 1.5×	379 2.6×	185 2.0×	33 0.4×	68 1.3×	69	857
Yi Fang United States	13	396 1.2×	281 1.9×	98 1.1×	12 0.1×	69 1.3×	53	654
Vikram Pudi India	13	368 1.1×	268 1.8×	102 1.1×	14 0.2×	18 0.3×	54	587

Countries citing papers authored by Rajesh Parekh

Since Specialization

Citations

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

Fields of papers citing papers by Rajesh Parekh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rajesh Parekh

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

All Works

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20 of 20 papers shown

Parekh, Rajesh, et al.. (2024). Safety and Efficacy of Hydroxypropyl Guar-Hyaluronic Acid Dual-Polymer Lubricating Eye Drops in Indian Subjects with Dry Eye: A Phase IV Study. Ophthalmology and Therapy. 14(2). 309–321.

Parekh, Rajesh, Billy R. Hammond, & Chandradhara Divya. (2024). Lutein and Zeaxanthin Supplementation Improves Dynamic Visual and Cognitive Performance in Children: A Randomized, Double-Blind, Parallel, Placebo-Controlled Study. Advances in Therapy. 41(4). 1496–1511. 12 indexed citations

Parekh, Rajesh. (2017). Designing AI at Scale to Power Everyday Life. 27–27. 4 indexed citations

Ghani, Rayid, Ted E. Senator, Paul S. Bradley, et al.. (2013). Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining. 1 indexed citations

Parekh, Rajesh, et al.. (2008). Combining Behavioral and Social Network Data for Online Advertising. 837–846. 27 indexed citations

Kohavi, Ron, Llew Mason, Rajesh Parekh, & Zijian Zheng. (2004). Lessons and Challenges from Mining Retail E-Commerce Data. Machine Learning. 57(1-2). 83–113. 77 indexed citations

Yang, Jihoon, Rajesh Parekh, Vasant Honavar, & Drena Dobbs. (2003). Data-driven theory refinement algorithms for bioinformatics. 6. 4064–4068. 6 indexed citations

Kohavi, Ron & Rajesh Parekh. (2003). Ten Supplementary Analyses to Improve E-commerce Web Sites. 31 indexed citations

Yang, Jihoon, et al.. (2002). DistAl: an inter-pattern distance-based constructive learning algorithm. 3. 2208–2213. 12 indexed citations

10.

Parekh, Rajesh & Vasant Honavar. (2001). Learning DFA from Simple Examples. Machine Learning. 44(1-2). 9–35. 23 indexed citations

11.

Parekh, Rajesh, Jihoon Yang, & Vasant Honavar. (2000). An empirical comparison of the performance so single-layer algorithms for training threshold logic units. Neural, Parallel & Scientific Computations archive. 8(3). 415–438. 2 indexed citations

12.

Parekh, Rajesh, Jihoon Yang, & Vasant Honavar. (2000). Constructive neural-network learning algorithms for pattern classification. IEEE Transactions on Neural Networks. 11(2). 436–451. 136 indexed citations

13.

Parekh, Rajesh & Vasant Honavar. (1999). Simple DFA are Polynomially Probably Exactly Learnable from Simple Examples. International Conference on Machine Learning. 298–306. 3 indexed citations

14.

Parekh, Rajesh, et al.. (1997). A Polynomial Time Incremental Algorithm for Regular Grammar Inference. Iowa State University Digital Repository (Iowa State University). 6 indexed citations

15.

Parekh, Rajesh, Jihoon Yang, & Vasant Honavar. (1997). Constructive Neural Network Learning Algorithms for Multi-Category Real-Valued Pattern Classification. Iowa State University Digital Repository (Iowa State University). 32 indexed citations

16.

Parekh, Rajesh & Vasant Honavar. (1996). An incremental interactive algorithm for grammar inference. 238–249. 12 indexed citations

17.

Parekh, Rajesh, Jihoon Yang, & Vasant Honavar. (1996). Constructive neural network learning algorithms. National Conference on Artificial Intelligence. 1398–1398.

18.

Chen, Chun‐Hsien, Rajesh Parekh, Jihoon Yang, Karthik Balakrishnan, & Vasant Honavar. (1995). Analysis of Decision Boundaries Generated by Constructive Neural Network Learning Algorithms. Iowa State University Digital Repository (Iowa State University). 6 indexed citations

19.

Parekh, Rajesh, Jihoon Yang, & Vasant Honavar. (1995). Constructive Neural Network Learning Algorithms for Multi-Category Pattern Classification. Iowa State University Digital Repository (Iowa State University). 20 indexed citations

20.

Parekh, Rajesh & Vasant Honavar. (1993). Efficient Learning of Regular Languages Using Teacher-Supplied Positive Samples and Learner-Generated Queries. Iowa State University Digital Repository (Iowa State University). 3 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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