Shayak Sen
Impact in
- Health Informatics top 5%
- Artificial Intelligence top 5%
- Explainable Artificial Intelligence (XAI)
- Adversarial Robustness in Machine Learning
- Privacy-Preserving Technologies in Data
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
Papers in
-
- Explainable Artificial Intelligence (XAI) 4
- Privacy-Preserving Technologies in Data 3
- Adversarial Robustness in Machine Learning 2
- Security and Verification in Computing 2
- Imbalanced Data Classification Techniques 1
-
- Web Application Security Vulnerabilities 1
- Co-authors
- Anupam Datta (9 shared papers)Yair Zick (1 shared paper)Philippe Bracke (1 shared paper)Matt Fredrikson (4 shared papers)Jeannette M. Wing (1 shared paper)K. Rustan M. Leino (3 shared papers)Piotr Mardziel (1 shared paper)Saikat Guha (1 shared paper)
- Journals
- arXiv (Cornell University) (1 paper)Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) (1 paper)SSRN Electronic Journal (1 paper)MPG.PuRe (Max Planck Society) (1 paper)
- Partner nations
- United StatesGermanyChina
In The Last Decade
Shayak Sen
9 papers receiving 566 citations
Shayak Sen's Hit Papers
Peers
Comparison fields: 5 of 98
- Health Informatics 34
- Artificial Intelligence 414
- Safety Research 97
- Management Science and Operations Research 64
- Information Systems and Management 30
Countries citing papers authored by Shayak Sen
This map shows the geographic impact of Shayak Sen'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 Shayak Sen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shayak Sen more than expected).
Fields of papers citing papers by Shayak Sen
This network shows the impact of papers produced by Shayak Sen. 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 Shayak Sen. The network helps show where Shayak Sen may publish in the future.
Co-authors
The 15 scholars most cited alongside Shayak Sen, 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 | Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems Hit paper breakdown → | 2016 | 354 |
| 2 | 2019 | 97 | |
| 3 | 2014 | 47 | |
| 4 | 2017 | 39 | |
| 5 | 2018 | 26 | |
| 6 | 2020 | 16 | |
| 7 | 2021 | 11 | |
| 8 | 2015 | 6 | |
| 9 | 2018 | 5 |
About Shayak Sen
Shayak Sen is a scholar working on Artificial Intelligence, Information Systems, Signal Processing, Sociology and Political Science and Finance, having authored 9 papers that have together received 601 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (4 papers), Privacy-Preserving Technologies in Data (3 papers), Adversarial Robustness in Machine Learning (2 papers), Security and Verification in Computing (2 papers), Advanced Malware Detection Techniques (2 papers), Imbalanced Data Classification Techniques (1 paper), Web Application Security Vulnerabilities (1 paper) and Wireless Communication Security Techniques (1 paper). The work is most often cited by research in Health Informatics (34 citations), Artificial Intelligence (414 citations), Safety Research (97 citations), Management Science and Operations Research (64 citations) and Information Systems and Management (30 citations). Shayak Sen has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Anupam Datta, Yair Zick, Philippe Bracke, Matt Fredrikson, Jeannette M. Wing, K. Rustan M. Leino, Piotr Mardziel, Saikat Guha, Sriram K. Rajamani and Janice Tsai. Their work appears in journals such as arXiv (Cornell University), Research Showcase @ Carnegie Mellon University (Carnegie Mellon University), SSRN Electronic Journal and MPG.PuRe (Max Planck Society).
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.