Esha Sarkar

490 total citations
15 papers, 287 citations indexed

About

Esha Sarkar is a scholar working on Artificial Intelligence, Cancer Research and Molecular Biology. According to data from OpenAlex, Esha Sarkar has authored 15 papers receiving a total of 287 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 4 papers in Cancer Research and 2 papers in Molecular Biology. Recurrent topics in Esha Sarkar's work include Adversarial Robustness in Machine Learning (5 papers), Cryptography and Data Security (3 papers) and Privacy-Preserving Technologies in Data (3 papers). Esha Sarkar is often cited by papers focused on Adversarial Robustness in Machine Learning (5 papers), Cryptography and Data Security (3 papers) and Privacy-Preserving Technologies in Data (3 papers). Esha Sarkar collaborates with scholars based in United States, United Arab Emirates and India. Esha Sarkar's co-authors include Michail Maniatakos, Jairo Giraldo, Álvaro A. Cárdenas, Murat Kantarcıoğlu, Eduardo Chielle, Gamze Gürsoy, Mark Gerstein, Yi Chen, Manaar Alam and Muhammad Shafique and has published in prestigious journals such as Scientific Reports, IEEE Access and IEEE Transactions on Artificial Intelligence.

In The Last Decade

Esha Sarkar

14 papers receiving 274 citations

Peers

Esha Sarkar

CSE

AI

CNC

IS

SP

Luís Rosa Portugal

Marko Schuba Germany

Qais Saif Qassim Malaysia

Natália C. Fernandes Brazil

Silia Maksuti Austria

Thomas Gamer Germany

Saša Mrdović Bosnia and Herzegovina

Ya Xiao United States

Muhammad Faizan Ayub Pakistan

Phuong Hoai Ha Norway

Luís Rosa Portugal

Esha Sarkar

182 ×1.4

CSE

104 ×0.8

AI

235 ×2.1

CNC

97 ×1.3

IS

89 ×1.8

SP

Citations per year, relative to Esha Sarkar Esha Sarkar (= 1×) peers Luís Rosa

Countries citing papers authored by Esha Sarkar

Since Specialization

Citations

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

Fields of papers citing papers by Esha Sarkar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Esha Sarkar

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

All Works

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15 of 15 papers shown

1.

Khan, Afreen, Esha Sarkar, Anu Chandra, et al.. (2024). Serum Insulin, Insulin-Like Growth Factor-1, Testosterone and Lipid Profile Levels in Benign Prostatic Hyperplasia and Prostate Cancer at Diagnosis. Cureus. 16(12). e75342–e75342. 1 indexed citations

2.

Sarkar, Esha, et al.. (2024). A Subspace Projective Clustering Approach for Backdoor Attack Detection and Mitigation in Deep Neural Networks. IEEE Transactions on Artificial Intelligence. 5(7). 3497–3509. 4 indexed citations

3.

Sarkar, Esha, et al.. (2023). TRAPDOOR: Repurposing neural network backdoors to detect dataset bias in machine learning-based genomic analysis. 1–6.

4.

Sarkar, Esha, Eduardo Chielle, Gamze Gürsoy, et al.. (2023). Privacy-preserving cancer type prediction with homomorphic encryption. Scientific Reports. 13(1). 1661–1661. 17 indexed citations

5.

Alam, Manaar, Esha Sarkar, & Michail Maniatakos. (2023). PerDoor: Persistent Backdoors in Federated Learning using Adversarial Perturbations. 1–6. 4 indexed citations

6.

Chandra, Anu, et al.. (2022). PROSTATE CANCER AND DIABETES: BIOLOGY OR DETECTION BIAS?. 9(2). 227–238. 1 indexed citations

7.

Sarkar, Esha, et al.. (2021). FaceHack: Attacking Facial Recognition Systems Using Malicious Facial Characteristics. IEEE Transactions on Biometrics Behavior and Identity Science. 4(3). 361–372. 13 indexed citations

8.

Sarkar, Esha, et al.. (2021). Fast and Scalable Private Genotype Imputation Using Machine Learning and Partially Homomorphic Encryption. IEEE Access. 9. 93097–93110. 23 indexed citations

9.

Sarkar, Esha, et al.. (2021). Remote Non-Intrusive Malware Detection for PLCs based on Chain of Trust Rooted in Hardware. 369–384. 6 indexed citations

10.

Sarkar, Esha, et al.. (2020). Watch your back: Backdoor Attacks in Deep Reinforcement Learning-based Autonomous Vehicle Control Systems.. 3 indexed citations

11.

Sarkar, Esha, et al.. (2020). I came, I saw, I hacked: Automated Generation of Process-independent Attacks for Industrial Control Systems. 744–758. 12 indexed citations

12.

Sarkar, Esha, et al.. (2020). Backdoor Suppression in Neural Networks using Input Fuzzing and Majority Voting. IEEE Design and Test. 37(2). 103–110. 12 indexed citations

13.

Sarkar, Esha, et al.. (2020). Practical Data-in-Use Protection Using Binary Decision Diagrams. IEEE Access. 8. 23847–23862. 1 indexed citations

14.

Sarkar, Esha & Michail Maniatakos. (2019). On automating delayered IC analysis for hardware IP protection. 205–210. 4 indexed citations

15.

Giraldo, Jairo, Esha Sarkar, Álvaro A. Cárdenas, Michail Maniatakos, & Murat Kantarcıoğlu. (2017). Security and Privacy in Cyber-Physical Systems: A Survey of Surveys. IEEE Design and Test. 34(4). 7–17. 186 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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