Vaibhav Kumar

816 total citations
34 papers, 361 citations indexed

About

Vaibhav Kumar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Vaibhav Kumar has authored 34 papers receiving a total of 361 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 9 papers in Information Systems. Recurrent topics in Vaibhav Kumar's work include Topic Modeling (13 papers), Natural Language Processing Techniques (9 papers) and Recommender Systems and Techniques (7 papers). Vaibhav Kumar is often cited by papers focused on Topic Modeling (13 papers), Natural Language Processing Techniques (9 papers) and Recommender Systems and Techniques (7 papers). Vaibhav Kumar collaborates with scholars based in India, United States and United Kingdom. Vaibhav Kumar's co-authors include Lei Mo, Vasudeva Varma, Dhruv Khattar, Jamie Callan, Mrinal Kanti Dhar, Manish Shrivastava, Manish Gupta, Alan W. Black, Chenyan Xiong and Jeff Dalton and has published in prestigious journals such as Journal of Molecular Liquids, Indian Journal of Science and Technology and ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam).

In The Last Decade

Vaibhav Kumar

27 papers receiving 324 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Vaibhav Kumar India	10	240	130	55	30	21	34	361
Elviawaty Muisa Zamzami Indonesia	9	134 0.6×	156 1.2×	48 0.9×	20 0.7×	14 0.7×	53	360
Solange Nice Alves-Souza Brazil	7	141 0.6×	116 0.9×	28 0.5×	17 0.6×	43 2.0×	30	266
Yanghoon Kim South Korea	10	156 0.7×	84 0.6×	72 1.3×	18 0.6×	8 0.4×	35	298
Enrico Palumbo Italy	8	163 0.7×	133 1.0×	33 0.6×	8 0.3×	31 1.5×	18	250
Anna Tordai Netherlands	8	206 0.9×	110 0.8×	44 0.8×	8 0.3×	31 1.5×	17	267
Johanna Völker Germany	13	335 1.4×	143 1.1×	18 0.3×	28 0.9×	36 1.7×	27	384
Sérgio Canuto Brazil	13	333 1.4×	114 0.9×	45 0.8×	8 0.3×	37 1.8×	25	424
Ludovik Çoba Italy	5	171 0.7×	58 0.4×	28 0.5×	14 0.5×	19 0.9×	13	267
Bogdan Walek Czechia	6	118 0.5×	181 1.4×	53 1.0×	13 0.4×	18 0.9×	33	267
Thomas Roth–Berghofer Germany	9	128 0.5×	64 0.5×	20 0.4×	21 0.7×	18 0.9×	44	223

Countries citing papers authored by Vaibhav Kumar

Since Specialization

Citations

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

Fields of papers citing papers by Vaibhav Kumar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vaibhav Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Vaibhav Kumar. A scholar is included among the top collaborators of Vaibhav Kumar 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 Vaibhav Kumar. Vaibhav Kumar 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

Sharma, Akash, et al.. (2025). Enhancing Education Infrastructure through Machine Learning: A Framework for Classifying and Prioritizing Schools. 1–5.

Sahu, Pooja, et al.. (2024). Large scale molecular dynamics simulations for sea water desalination using nanotube membrane. Journal of Molecular Liquids. 418. 126705–126705. 1 indexed citations

Jung, Dongwon, et al.. (2024). Planning and Editing What You Retrieve for Enhanced Tool Learning. 975–988.

Kumar, Vaibhav, et al.. (2024). Fraud Detection in Financial Transactions Using Credit Card: A Machine Learning Model. International Research Journal on Advanced Engineering Hub (IRJAEH). 2(5). 1427–1434. 2 indexed citations

Liu, Min‐Qian, et al.. (2024). X-Eval: Generalizable Multi-aspect Text Evaluation via Augmented Instruction Tuning with Auxiliary Evaluation Aspects. 8560–8579.

Jain, Rachna, Akshay Aggarwal, & Vaibhav Kumar. (2021). A review of deep learning-based disease detection in Alzheimer's patients. Elsevier eBooks. 1–19. 2 indexed citations

Dalton, Jeff, Chenyan Xiong, Vaibhav Kumar, & Jamie Callan. (2020). CAsT-19: A Dataset for Conversational Information Seeking. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1985–1988. 42 indexed citations

Kumar, Vaibhav, et al.. (2020). Machine Learning based Language Modelling of Code Switched Data. 552–557. 2 indexed citations

Kumar, Vaibhav, et al.. (2020). Traffic density estimation using progressive neural architecture search. Journal of Statistics and Management Systems. 23(2). 481–493. 2 indexed citations

10.

Kumar, Vaibhav & Alan W. Black. (2020). ClarQ: A large-scale and diverse dataset for Clarification Question Generation. 7296–7301. 22 indexed citations

11.

Jain, Deepak Kumar, et al.. (2020). ATT: Attention-based Timbre Transfer. 1–6. 5 indexed citations

12.

Kumar, Vaibhav, et al.. (2019). Multiple Resource Management and Burst Time Prediction using Deep Reinforcement Learning. 9(2). 131–138. 6 indexed citations

13.

Kumar, Vaibhav, et al.. (2019). Text Extraction from Natural Scene Images using OpenCV and CNN. International Journal of Information Technology and Computer Science. 11(9). 48–54. 1 indexed citations

14.

Dhar, Mrinal Kanti, Vaibhav Kumar, & Manish Shrivastava. (2018). Enabling Code-Mixed Translation: Parallel Corpus Creation and MT Augmentation Approach. 131–140. 30 indexed citations

15.

Kumar, Vaibhav & Lei Mo. (2018). Predictive Analytics: A Review of Trends and Techniques. International Journal of Computer Applications. 182(1). 31–37. 76 indexed citations

16.

Khattar, Dhruv, Vaibhav Kumar, Manish Gupta, & Vasudeva Varma. (2018). Neural Content-Collaborative Filtering for News Recommendation.. 45–50. 6 indexed citations

17.

Kumar, Vaibhav, et al.. (2018). Deep learning techniques and their applications: A short review. Bioscience Biotechnology Research Communications. 11(4). 699–709. 4 indexed citations

18.

Kumar, Vaibhav & Lei Mo. (2018). Deep Learning as a Frontier of Machine Learning: A Review. International Journal of Computer Applications. 182(1). 22–30. 15 indexed citations

19.

Kumar, Vaibhav, et al.. (2017). Deep Neural Architecture for News Recommendation.. CLEF (Working Notes). 18 indexed citations

20.

Sharma, Deepak, et al.. (2017). Design of a Fault Tolerant Architecture for Private Cloud Computing Infrastructure. Indian Journal of Science and Technology. 10(4). 2 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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