Vikram Pudi

1.3k citations
54 papers · 587 · h-index 13

Impact in

    • Data Mining Algorithms and Applications
    • Recommender Systems and Techniques
    • Topic Modeling
    • Adversarial Robustness in Machine Learning
    • Imbalanced Data Classification Techniques
    • Natural Language Processing Techniques

Papers in

    • Topic Modeling 17
    • Natural Language Processing Techniques 12
    • Advanced Text Analysis Techniques 5
    • Fuzzy Logic and Control Systems 4
    • Data Mining Algorithms and Applications 14

Vikram Pudi

52 papers receiving 522 citations

Peers

Vikram Pudi
Comparison fields: 5 of 81
  • Information Systems 268
  • Artificial Intelligence 368
  • Signal Processing 81
  • Computational Theory and Mathematics 89
  • Computer Vision and Pattern Recognition 102
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Citations per field
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Citations per year

Countries citing papers authored by Vikram Pudi

Since Specialization
Citations

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

Fields of papers citing papers by Vikram Pudi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Vikram Pudi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Vikram Pudi Line = papers co-authored together Vikram Pudi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201960
2 201756
3 202152
4 200950
5
Data Mining: Concepts and Techniques
200943
6
Predicting the Outcome of ODI Cricket Matches: A Team Composition Based Approach.
201639
7 202119
8 201119
9 201119
10 201617
11 200014
12
ARMOR: Association Rule Mining based on ORacle.
200314
13 201014
14 202110
15 201010
16
Dynamic Winner Prediction in Twenty20 Cricket: Based on Relative Team Strengths.
20179
17 20049
18 20119
19 20178
20 20108

About Vikram Pudi

Vikram Pudi is a scholar working on Artificial Intelligence, Information Systems, Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Signal Processing, having authored 54 papers that have together received 587 indexed citations. Recurring topics across this work include Topic Modeling (17 papers), Data Mining Algorithms and Applications (14 papers), Natural Language Processing Techniques (12 papers), Rough Sets and Fuzzy Logic (10 papers), Data Management and Algorithms (5 papers), Complex Network Analysis Techniques (5 papers), Advanced Text Analysis Techniques (5 papers) and Fuzzy Logic and Control Systems (4 papers). The work is most often cited by research in Information Systems (268 citations), Artificial Intelligence (368 citations), Signal Processing (81 citations), Computational Theory and Mathematics (89 citations) and Computer Vision and Pattern Recognition (102 citations). Vikram Pudi has collaborated with scholars based in India, United States and Hong Kong. Frequent co-authors include Jayant R. Haritsa, Giuseppe Manco, Ettore Ritacco, Pratibha Rani, Dipti Misra Sharma, Vishal Garg, Rajesh Parekh, Mohammed J. Zaki, P. Radha Krishna and Vasudeva Varma. Their work appears in journals such as International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, Information Systems, International Journal of Business Intelligence and Data Mining, International Journal of Data Science and Analytics and Lecture notes in computer science.

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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