Shayak Sen

1.3k total citations · 1 hit paper
9 papers, 583 citations indexed

About

Shayak Sen is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Shayak Sen has authored 9 papers receiving a total of 583 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 3 papers in Information Systems and 2 papers in Signal Processing. Recurrent topics in Shayak Sen's work include Explainable Artificial Intelligence (XAI) (4 papers), Privacy-Preserving Technologies in Data (3 papers) and Security and Verification in Computing (2 papers). Shayak Sen is often cited by papers focused on Explainable Artificial Intelligence (XAI) (4 papers), Privacy-Preserving Technologies in Data (3 papers) and Security and Verification in Computing (2 papers). Shayak Sen collaborates with scholars based in United States, India and Germany. Shayak Sen's co-authors include Anupam Datta, Yair Zick, Philippe Bracke, Matt Fredrikson, Piotr Mardziel, K. Rustan M. Leino, Janice Tsai, Sriram K. Rajamani, Saikat Guha and Jeannette M. Wing and has published in prestigious journals such as arXiv (Cornell University) and SSRN Electronic Journal.

In The Last Decade

Shayak Sen

9 papers receiving 548 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems

2016 346 citations Anupam Datta, Shayak Sen et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shayak Sen United States	7	410	98	77	62	55	9	583
Emanuela Raffinetti Italy	12	219 0.5×	22 0.2×	57 0.7×	146 2.4×	49 0.9×	37	580
Yair Zick Singapore	11	333 0.8×	103 1.1×	47 0.6×	179 2.9×	32 0.6×	42	613
Dylan Slack United States	5	334 0.8×	57 0.6×	26 0.3×	16 0.3×	13 0.2×	6	478
Sophie Hilgard United States	4	302 0.7×	45 0.5×	19 0.2×	14 0.2×	30 0.5×	4	431
Johan Huysmans Belgium	7	302 0.7×	14 0.1×	91 1.2×	34 0.5×	6 0.1×	12	427
Arash Bahrammirzaee France	3	140 0.3×	19 0.2×	43 0.6×	167 2.7×	13 0.2×	6	394
Emily Jia United States	2	279 0.7×	39 0.4×	16 0.2×	13 0.2×	10 0.2×	4	399
Waddah Saeed Malaysia	4	254 0.6×	20 0.2×	26 0.3×	27 0.4×	10 0.2×	5	423
Dimitar Trajanov North Macedonia	10	187 0.5×	9 0.1×	72 0.9×	109 1.8×	21 0.4×	58	448
Mansooreh Karami United States	6	235 0.6×	13 0.1×	105 1.4×	18 0.3×	143 2.6×	8	424

Countries citing papers authored by Shayak Sen

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Shayak Sen

This figure shows the co-authorship network connecting the top 25 collaborators of Shayak Sen. A scholar is included among the top collaborators of Shayak Sen 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 Shayak Sen. Shayak Sen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Datta, Anupam, et al.. (2021). Machine Learning Explainability and Robustness. 4035–4036. 10 indexed citations

2.

Tschantz, Michael Carl, Shayak Sen, & Anupam Datta. (2020). SoK: Differential Privacy as a Causal Property. 354–371. 16 indexed citations

3.

Bracke, Philippe, et al.. (2019). Machine Learning Explainability in Finance: An Application to Default Risk Analysis. SSRN Electronic Journal. 89 indexed citations

4.

Leino, K. Rustan M., Shayak Sen, Anupam Datta, Matt Fredrikson, & Linyi Li. (2018). Influence-Directed Explanations for Deep Convolutional Networks. 1–8. 25 indexed citations

5.

Leino, K. Rustan M., et al.. (2018). Feature-Wise Bias Amplification. arXiv (Cornell University). 5 indexed citations

6.

Datta, Anupam, et al.. (2017). Use Privacy in Data-Driven Systems. 1193–1210. 39 indexed citations

7.

Datta, Anupam, Shayak Sen, & Yair Zick. (2016). Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems. 598–617. 346 indexed citations breakdown →

8.

Jia, Limin, Shayak Sen, Deepak Garg, & Anupam Datta. (2015). A Logic of Programs with Interface-Confined Code. 512–525. 6 indexed citations

9.

Sen, Shayak, Saikat Guha, Anupam Datta, et al.. (2014). Bootstrapping Privacy Compliance in Big Data Systems. 327–342. 47 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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