Arjun Nitin Bhagoji
- Artificial Intelligence top 5%
- Adversarial Robustness in Machine Learning 11
- Anomaly Detection Techniques and Applications 8
- Internet Traffic Analysis and Secure E-voting 6
- Privacy-Preserving Technologies in Data 2
- Hate Speech and Cyberbullying Detection 1
- Signal Processing top 10%
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- Network Security and Intrusion Detection 7
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- Spam and Phishing Detection 1
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- Bacillus and Francisella bacterial research 1
- Co-authors
- Prateek MittalDaniel CullinaSeraphin CaloSupriyo ChakrabortyVikash SehwagShinan LiuHai-Tao ZhengMung Chiang
- Journals
- ACM SIGMETRICS Performance Evaluation Review (1 paper)Proceedings of the ACM on Measurement and Analysis of Computing Systems (1 paper)USENIX Security Symposium (1 paper)
- Partner nations
- United StatesFranceChina
In The Last Decade
Arjun Nitin Bhagoji
16 papers receiving 235 citations
Peers
Comparison fields: 5 of 46
- Artificial Intelligence 218
- Signal Processing 54
- Computer Science Applications 18
- Computer Networks and Communications 52
- Computational Mathematics 1
Countries citing papers authored by Arjun Nitin Bhagoji
This map shows the geographic impact of Arjun Nitin Bhagoji'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 Arjun Nitin Bhagoji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arjun Nitin Bhagoji more than expected).
Fields of papers citing papers by Arjun Nitin Bhagoji
This network shows the impact of papers produced by Arjun Nitin Bhagoji. 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 Arjun Nitin Bhagoji. The network helps show where Arjun Nitin Bhagoji may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Arjun Nitin Bhagoji, 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 | 2025 | 0 | |
| 2 | 2024 | 17 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 6 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 0 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 7 | |
| 9 | PatchGuard: A provably robust defense against adversarial patches via small receptive fields and masking | 2021 | 2 |
| 10 | 2021 | 19 | |
| 11 | The Role of Data Geometry in Adversarial Machine Learning | 2020 | 1 |
| 12 | Analyzing Federated Learning through an Adversarial Lens | 2019 | 86 |
| 13 | 2019 | 5 | |
| 14 | 2019 | 29 | |
| 15 | PAC-learning in the presence of adversaries | 2018 | 13 |
| 16 | Black-box attacks on deep neural networks via gradient estimation | 2018 | 2 |
| 17 | 2018 | 4 | |
| 18 | Dimensionality Reduction as a Defense against Evasion Attacks on Machine Learning Classifiers. | 2017 | 51 |
About Arjun Nitin Bhagoji
Arjun Nitin Bhagoji is a scholar working on Artificial Intelligence, Computer Networks and Communications and Toxicology, having authored 18 papers that have together received 249 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (11 papers), Anomaly Detection Techniques and Applications (8 papers), Network Security and Intrusion Detection (7 papers), Internet Traffic Analysis and Secure E-voting (6 papers), Privacy-Preserving Technologies in Data (2 papers), Hate Speech and Cyberbullying Detection (1 paper), Spam and Phishing Detection (1 paper) and Bacillus and Francisella bacterial research (1 paper). The work is most often cited by research in Artificial Intelligence (218 citations), Signal Processing (54 citations) and Computer Science Applications (18 citations). Arjun Nitin Bhagoji has collaborated with scholars based in United States, France and China. Frequent co-authors include Prateek Mittal, Daniel Cullina, Seraphin Calo, Supriyo Chakraborty, Vikash Sehwag, Shinan Liu, Hai-Tao Zheng, Mung Chiang, Paul Schmitt and Nick Feamster. Their work appears in journals such as ACM SIGMETRICS Performance Evaluation Review, Proceedings of the ACM on Measurement and Analysis of Computing Systems and USENIX Security Symposium.
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.