Deepu John

1.9k total citations · 1 hit paper
69 papers, 1.2k citations indexed

About

Deepu John is a scholar working on Biomedical Engineering, Cardiology and Cardiovascular Medicine and Cognitive Neuroscience. According to data from OpenAlex, Deepu John has authored 69 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Biomedical Engineering, 41 papers in Cardiology and Cardiovascular Medicine and 25 papers in Cognitive Neuroscience. Recurrent topics in Deepu John's work include ECG Monitoring and Analysis (41 papers), EEG and Brain-Computer Interfaces (23 papers) and Non-Invasive Vital Sign Monitoring (21 papers). Deepu John is often cited by papers focused on ECG Monitoring and Analysis (41 papers), EEG and Brain-Computer Interfaces (23 papers) and Non-Invasive Vital Sign Monitoring (21 papers). Deepu John collaborates with scholars based in Ireland, Singapore and China. Deepu John's co-authors include Yong Lian, Barry Cardiff, Chun-Huat Heng, Soumyabrata Dev, Bharadwaj Veeravalli, Hewei Wang, Wen-Sin Liew, Rajesh C. Panicker, Xiaoyang Zhang and Xiaoyang Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Deepu John

62 papers receiving 1.1k citations

Hit Papers

A predictive analytics approach for stroke prediction usi... 2022 2026 2023 2024 2022 40 80 120
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.

  1. A predictive analytics approach for stroke prediction using machine learning and neural networks
    2022 136 citations Deepu John et al. SHILAP Revista de lepidopterología profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deepu John Ireland 17 623 603 292 186 160 69 1.2k
Dwaipayan Biswas Belgium 20 1.2k 1.9× 758 1.3× 307 1.1× 264 1.4× 123 0.8× 75 1.8k
Fen Miao China 19 872 1.4× 895 1.5× 208 0.7× 63 0.3× 86 0.5× 38 1.4k
Xiaomao Fan China 16 353 0.6× 690 1.1× 529 1.8× 55 0.3× 175 1.1× 67 1.3k
Sumair Aziz Pakistan 22 455 0.7× 416 0.7× 286 1.0× 114 0.6× 123 0.8× 108 1.3k
Muhammad Umar Khan Pakistan 21 426 0.7× 413 0.7× 281 1.0× 116 0.6× 99 0.6× 115 1.2k
Awni Hannun Israel 9 372 0.6× 1.2k 2.0× 634 2.2× 82 0.4× 595 3.7× 16 2.2k
Lakhan Dev Sharma India 21 251 0.4× 574 1.0× 576 2.0× 52 0.3× 148 0.9× 67 1.1k
Feifei Liu China 16 376 0.6× 1.1k 1.8× 654 2.2× 75 0.4× 190 1.2× 48 1.5k
Sukanta Sabut India 22 563 0.9× 546 0.9× 507 1.7× 20 0.1× 232 1.4× 71 1.6k
Yalçın İşler Türkiye 16 156 0.3× 355 0.6× 345 1.2× 71 0.4× 99 0.6× 90 915

Countries citing papers authored by Deepu John

Since Specialization
Citations

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

Fields of papers citing papers by Deepu John

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deepu John

This figure shows the co-authorship network connecting the top 25 collaborators of Deepu John. A scholar is included among the top collaborators of Deepu John 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 Deepu John. Deepu John 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
1.
Spatharakis, Dimitrios, Jun-Bao Fan, Hans Vandierendonck, et al.. (2025). SLED: A Speculative LLM Decoding Framework for Efficient Edge Serving. VTechWorks (Virginia Tech). 1–8. 1 indexed citations
2.
Cardiff, Barry, et al.. (2025). DyCE: Dynamically Configurable Exiting for deep learning compression and real-time scaling. Future Generation Computer Systems. 171. 107837–107837.
3.
Cardiff, Barry, et al.. (2025). Signal‐quality‐aware multisensor fusion for atrial fibrillation detection. Healthcare Technology Letters. 12(1). e12121–e12121. 2 indexed citations
4.
Li, Xiaolin, et al.. (2025). DCentNet: Decentralized multistage biomedical signal classification using early exits. Biomedical Signal Processing and Control. 104. 107468–107468.
5.
Märtens, Olev, et al.. (2024). ECG Classification With Event-Driven Sampling. IEEE Access. 12. 25188–25199. 3 indexed citations
6.
Chen, Shaowu, et al.. (2024). POCKET: Pruning random convolution kernels for time series classification from a feature selection perspective. Knowledge-Based Systems. 300. 112253–112253. 1 indexed citations
7.
John, Deepu, et al.. (2024). FEC-Aided Decision Feedback Blind Mismatch Calibration of TIADCs in Wireless Time-Varying Channel Environments. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 32(7). 1173–1183. 1 indexed citations
8.
Zheng, Hao, et al.. (2024). A Background Jitter Calibration for ADCs Using TDC Phase Information From ADPLL. IEEE Access. 12. 174551–174563.
9.
Shreejith, Shanker, et al.. (2024). ECG Biometric Authentication Using Self-Supervised Learning for IoT Edge Sensors. IEEE Journal of Biomedical and Health Informatics. 28(11). 6606–6618. 8 indexed citations
10.
Kumar, Mohit, et al.. (2024). KWT-Tiny: RISC-V Accelerated, Embedded Keyword Spotting Transformer. arXiv (Cornell University). 1–6.
11.
12.
Märtens, Olev, Antoine Frappé, Mart Min, et al.. (2023). A DSP-Based EBI, ECG, and PPG Measurement Platform. IEEE Transactions on Instrumentation and Measurement. 72. 1–8. 3 indexed citations
13.
John, Deepu, et al.. (2023). NUTS-BSNN: A non-uniform time-step binarized spiking neural network with energy-efficient in-memory computing macro. Neurocomputing. 560. 126838–126838. 5 indexed citations
14.
Doheny, Emer P., et al.. (2023). An evaluation of ECG data fusion algorithms for wearable IoT sensors. Information Fusion. 96. 237–251. 14 indexed citations
15.
Boydell, Oisín, et al.. (2022). Class-Separation Preserving Pruning for Deep Neural Networks. IEEE Transactions on Artificial Intelligence. 5(1). 290–299. 1 indexed citations
16.
Redmond, Stephen J., et al.. (2021). A Multimodal Data Fusion Technique for Heartbeat Detection in Wearable IoT Sensors. IEEE Internet of Things Journal. 9(3). 2071–2082. 37 indexed citations
17.
Panicker, Rajesh C., et al.. (2020). Binary Classifiers for Data Integrity Detection in Wearable IoT Edge Devices. SHILAP Revista de lepidopterología. 1. 88–99. 13 indexed citations
18.
Ullah, Salim, et al.. (2020). An Approximate Binary Classifier for Data Integrity Assessment in IoT Sensors. 1–4. 5 indexed citations
19.
John, Deepu & Yong Lian. (2015). A low complexity lossless compression scheme for wearable ECG sensors. 449–453. 17 indexed citations
20.
John, Deepu, et al.. (2011). A computationally efficient QRS detection algorithm for wearable ECG sensors. PubMed. 2011. 5641–5644. 45 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Dwaipayan Biswas Breakdown of academic impact, for papers by Fen Miao Breakdown of academic impact, for papers by Xiaomao Fan Breakdown of academic impact, for papers by Sumair Aziz Breakdown of academic impact, for papers by Muhammad Umar Khan Breakdown of academic impact, for papers by Awni Hannun Breakdown of academic impact, for papers by Lakhan Dev Sharma Breakdown of academic impact, for papers by Feifei Liu Breakdown of academic impact, for papers by Sukanta Sabut Breakdown of academic impact, for papers by Yalçın İşler
Rankless by CCL
2026