Bappaditya Dey

472 total citations
48 papers, 238 citations indexed

About

Bappaditya Dey is a scholar working on Electrical and Electronic Engineering, Industrial and Manufacturing Engineering and Surfaces, Coatings and Films. According to data from OpenAlex, Bappaditya Dey has authored 48 papers receiving a total of 238 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Electrical and Electronic Engineering, 24 papers in Industrial and Manufacturing Engineering and 13 papers in Surfaces, Coatings and Films. Recurrent topics in Bappaditya Dey's work include Industrial Vision Systems and Defect Detection (24 papers), Advancements in Photolithography Techniques (21 papers) and Integrated Circuits and Semiconductor Failure Analysis (21 papers). Bappaditya Dey is often cited by papers focused on Industrial Vision Systems and Defect Detection (24 papers), Advancements in Photolithography Techniques (21 papers) and Integrated Circuits and Semiconductor Failure Analysis (21 papers). Bappaditya Dey collaborates with scholars based in Belgium, United States and Egypt. Bappaditya Dey's co-authors include Sandip Halder, Magdy Bayoumi, Kasem Khalil, Ashok Kumar, Stefan De Gendt, Philippe Leray, Wannes Meert, Omar Eldash, Gian F. Lorusso and Bartel Van Waeyenberge and has published in prestigious journals such as IEEE Access, Japanese Journal of Applied Physics and IEEE Internet of Things Journal.

In The Last Decade

Bappaditya Dey

44 papers receiving 228 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bappaditya Dey Belgium 10 135 81 55 45 43 48 238
Emile Sahouria United States 8 140 1.0× 24 0.3× 35 0.6× 109 2.4× 21 0.5× 32 290
Azade Nova United States 3 169 1.3× 44 0.5× 95 1.7× 28 0.6× 6 324
H. Fatih Uğurdağ Türkiye 10 137 1.0× 46 0.6× 39 0.7× 30 0.7× 55 291
Juejian Wu China 7 266 2.0× 29 0.4× 63 1.1× 14 0.3× 16 334
Amlan Ganguly United States 12 226 1.7× 21 0.3× 71 1.3× 46 1.0× 43 359
Rongjian Liang United States 10 165 1.2× 36 0.4× 29 0.5× 19 0.4× 35 264
Pei Luo United States 10 58 0.4× 33 0.4× 159 2.9× 73 1.6× 23 231
Ismail Bustany United States 11 430 3.2× 58 0.7× 24 0.4× 28 0.6× 24 468
Sumit K. Mandal United States 10 206 1.5× 11 0.1× 46 0.8× 58 1.3× 31 310
Jian Kuang Hong Kong 13 457 3.4× 75 0.9× 24 0.4× 43 1.0× 1 0.0× 37 558

Countries citing papers authored by Bappaditya Dey

Since Specialization
Citations

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

Fields of papers citing papers by Bappaditya Dey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bappaditya Dey

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

All Works

20 of 20 papers shown
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Khalil, Kasem, Bappaditya Dey, & Magdy Bayoumi. (2024). S²RNN: Self-Supervised Reconfigurable Neural Network Hardware Accelerator for Machine Learning Applications. IEEE Internet of Things Journal. 12(6). 6708–6720. 1 indexed citations
3.
Chen, Ying-Lin, Bappaditya Dey, Víctor Blanco, et al.. (2024). Exploring Machine Learning for Semiconductor Process Optimization: A Systematic Review. IEEE Transactions on Artificial Intelligence. 5(12). 5969–5989. 8 indexed citations
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Chen, Ying-Lin, et al.. (2024). Towards improved semiconductor defect inspection for high-NA EUVL based on SEMI-SuperYOLO-NAS. Ghent University Academic Bibliography (Ghent University). 30–30. 1 indexed citations
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Dey, Bappaditya, et al.. (2023). SEMI-CenterNet: a machine learning facilitated approach for semiconductor defect inspection. Ghent University Academic Bibliography (Ghent University). 15–15. 5 indexed citations
10.
Hermans, Yannick, Chen Wu, Filip Schleicher, et al.. (2023). BEOL N2: M2 through SAxP process from MP21 to MP26: 193i SAQP vs EUV SADP. 57–57. 1 indexed citations
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Lorusso, Gian F., et al.. (2023). e-beam metrology of thin resist for high NA EUVL. Japanese Journal of Applied Physics. 62(SG). SG0808–SG0808. 1 indexed citations
13.
Dey, Bappaditya, et al.. (2022). Deep learning-based defect classification and detection in SEM images. arXiv (Cornell University). 83–83. 16 indexed citations
14.
Ngo, Anh T., Bappaditya Dey, Sandip Halder, Stefan De Gendt, & Changhai Wang. (2022). Machine Learning-Based Edge Placement Error Analysis and Optimization: A Systematic Review. IEEE Transactions on Semiconductor Manufacturing. 36(1). 1–13. 5 indexed citations
15.
Dey, Bappaditya, et al.. (2022). Code Generation Using Machine Learning: A Systematic Review. IEEE Access. 10. 82434–82455. 31 indexed citations
16.
Dey, Bappaditya, et al.. (2022). Deep learning based defect classification and detection in SEM images: a mask R-CNN approach. Lirias (KU Leuven). 43–43. 9 indexed citations
17.
Dey, Bappaditya, Danilo De Simone, Sandip Halder, et al.. (2022). Extraction of roughness measurements from thin resists with low signal-to-noise-ratio (SNR) SEM images by applying deep learning denoiser. Lirias. 29–29. 3 indexed citations
18.
Dey, Bappaditya, Sandip Halder, Kasem Khalil, et al.. (2021). SEM image denoising with unsupervised machine learning for better defect inspection and metrology. 33–33. 16 indexed citations
19.
Dey, Bappaditya, Kasem Khalil, Ashok Kumar, & Magdy Bayoumi. (2020). A Reversible-Logic based Architecture for Artificial Neural Network. 505–508. 9 indexed citations
20.
Khalil, Kasem, Omar Eldash, Bappaditya Dey, Ashok Kumar, & Magdy Bayoumi. (2019). A Novel Reconfigurable Hardware Architecture of Neural Network. 618–621. 11 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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