Kumar Shridhar
Impact in
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- Topic Modeling
- Natural Language Processing Techniques
- Anomaly Detection Techniques and Applications
- Advanced Graph Neural Networks
- Adversarial Robustness in Machine Learning
- Intelligent Tutoring Systems and Adaptive Learning
Papers in
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- Natural Language Processing Techniques 6
- Topic Modeling 6
- Intelligent Tutoring Systems and Adaptive Learning 2
- Hate Speech and Cyberbullying Detection 2
- Authorship Attribution and Profiling 2
- Gaussian Processes and Bayesian Inference 2
- Adversarial Robustness in Machine Learning 2
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- Spam and Phishing Detection 2
- Co-authors
- Mrinmaya Sachan (8 shared papers)Felix Laumann (2 shared papers)Denis Kleyko (1 shared paper)Akshat Agarwal (1 shared paper)Tanmay Sinha (1 shared paper)Mennatallah El‐Assady (1 shared paper)Manu Kapur (1 shared paper)Bernhard Schoelkopf (1 shared paper)
- Journals
- SZTE Publicatio Repozitórium (University of Szeged) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)CLEF (Working Notes) (1 paper)arXiv (Cornell University) (2 papers)Research at the University of Copenhagen (University of Copenhagen) (1 paper)
- Partner nations
- SwitzerlandUnited StatesSweden
In The Last Decade
Kumar Shridhar
10 papers receiving 93 citations
Peers
Comparison fields: 5 of 43
- Health Informatics 4
- Artificial Intelligence 75
- Computer Science Applications 5
- Computer Vision and Pattern Recognition 14
- Information Systems 10
Countries citing papers authored by Kumar Shridhar
This map shows the geographic impact of Kumar Shridhar'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 Kumar Shridhar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kumar Shridhar more than expected).
Fields of papers citing papers by Kumar Shridhar
This network shows the impact of papers produced by Kumar Shridhar. 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 Kumar Shridhar. The network helps show where Kumar Shridhar may publish in the future.
Co-authors
The 25 scholars most cited alongside Kumar Shridhar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 24 | |
| 2 | 2022 | 19 | |
| 3 | 2020 | 14 | |
| 4 | Bayesian Convolutional Neural Networks | 2018 | 11 |
| 5 | 2023 | 9 | |
| 6 | 2021 | 9 | |
| 7 | Bayesian Convolutional Neural Networks with Variational Inference | 2018 | 7 |
| 8 | 2024 | 2 | |
| 9 | Author Profiling Using Semantic and Syntactic Features : Notebook for PAN at CLEF 2019 | 2019 | 2 |
| 10 | 2025 | 1 | |
| 11 | 2025 | 0 | |
| 12 | Author Profiling using Semantic and Syntactic Features. | 2019 | 0 |
| 13 | 2023 | 0 |
About Kumar Shridhar
Kumar Shridhar is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Molecular Biology, having authored 13 papers that have together received 98 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Topic Modeling (6 papers), Spam and Phishing Detection (2 papers), Intelligent Tutoring Systems and Adaptive Learning (2 papers), Hate Speech and Cyberbullying Detection (2 papers), Authorship Attribution and Profiling (2 papers), Gaussian Processes and Bayesian Inference (2 papers) and Adversarial Robustness in Machine Learning (2 papers). The work is most often cited by research in Health Informatics (4 citations), Artificial Intelligence (75 citations), Computer Science Applications (5 citations), Computer Vision and Pattern Recognition (14 citations) and Information Systems (10 citations). Kumar Shridhar has collaborated with scholars based in Switzerland, United States and Sweden. Frequent co-authors include Mrinmaya Sachan, Felix Laumann, Denis Kleyko, Akshat Agarwal, Tanmay Sinha, Mennatallah El‐Assady, Manu Kapur, Bernhard Schoelkopf, Manzil Zaheer and Marcus Liwicki. Their work appears in journals such as SZTE Publicatio Repozitórium (University of Szeged), Proceedings of the AAAI Conference on Artificial Intelligence, CLEF (Working Notes), arXiv (Cornell University) and Research at the University of Copenhagen (University of Copenhagen).
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.