Amith Khandakar

10.1k total citations · 7 hit papers
163 papers, 6.2k citations indexed

About

Amith Khandakar is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Electrical and Electronic Engineering. According to data from OpenAlex, Amith Khandakar has authored 163 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Biomedical Engineering, 36 papers in Radiology, Nuclear Medicine and Imaging and 30 papers in Electrical and Electronic Engineering. Recurrent topics in Amith Khandakar's work include COVID-19 diagnosis using AI (25 papers), Non-Invasive Vital Sign Monitoring (18 papers) and EEG and Brain-Computer Interfaces (14 papers). Amith Khandakar is often cited by papers focused on COVID-19 diagnosis using AI (25 papers), Non-Invasive Vital Sign Monitoring (18 papers) and EEG and Brain-Computer Interfaces (14 papers). Amith Khandakar collaborates with scholars based in Qatar, Bangladesh and Malaysia. Amith Khandakar's co-authors include Muhammad E. H. Chowdhury, Tawsifur Rahman, Mohammad Tariqul Islam, Muhammad Salman Khan, Zaid Bin Mahbub, Muhammad Abdul Kadir, Khandaker Reajul Islam, Mamun Bin Ibne Reaz, Mohamed Arselene Ayari and Anas Tahir and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Amith Khandakar

150 papers receiving 5.9k citations

Hit Papers

Can AI Help in Screening Viral and COVID-19 Pneumonia? 2020 2026 2022 2024 2020 2021 2020 2020 2021 250 500 750 1000
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. Can AI Help in Screening Viral and COVID-19 Pneumonia?
    2020 1.2k citations Muhammad E. H. Chowdhury, Tawsifur Rahman et al. IEEE Access profile →
  2. Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images
    2021 672 citations Tawsifur Rahman, Amith Khandakar et al. Computers in Biology and Medicine profile →
  3. Transfer Learning with Deep Convolutional Neural Network (CNN) for Pneumonia Detection Using Chest X-ray
    2020 394 citations Tawsifur Rahman, Muhammad E. H. Chowdhury et al. profile →
  4. Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization
    2020 375 citations Tawsifur Rahman, Amith Khandakar et al. IEEE Access profile →
  5. Automatic and Reliable Leaf Disease Detection Using Deep Learning Techniques
    2021 213 citations Muhammad E. H. Chowdhury, Tawsifur Rahman et al. profile →
  6. COVID-19 infection localization and severity grading from chest X-ray images
    2022 116 citations Anas Tahir, Muhammad E. H. Chowdhury et al. Qatar University QSpace (Qatar University) profile →
  7. A hybrid explainable model based on advanced machine learning and deep learning models for classifying brain tumors using MRI images
    2025 17 citations Md. Nahiduzzaman, Amith Khandakar et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Amith Khandakar Qatar 34 3.0k 2.1k 1.0k 801 642 163 6.2k
Muhammad E. H. Chowdhury Qatar 39 3.3k 1.1× 2.3k 1.1× 1.4k 1.4× 949 1.2× 706 1.1× 285 7.6k
Abdulkadir Şengür Türkiye 52 1.6k 0.5× 2.6k 1.2× 740 0.7× 1.6k 2.0× 503 0.8× 229 8.7k
Mizuho Nishio Japan 24 1.8k 0.6× 1.0k 0.5× 563 0.6× 665 0.8× 725 1.1× 67 4.3k
Rikiya Yamashita United States 18 1.6k 0.5× 1.1k 0.5× 499 0.5× 638 0.8× 390 0.6× 49 4.1k
Zafer Cömert Türkiye 31 1.4k 0.5× 1.5k 0.7× 397 0.4× 858 1.1× 459 0.7× 78 3.5k
Özal Yıldırım Türkiye 29 2.4k 0.8× 2.1k 1.0× 1.0k 1.0× 954 1.2× 799 1.2× 77 6.7k
Tawsifur Rahman Qatar 23 2.7k 0.9× 1.7k 0.8× 335 0.3× 583 0.7× 501 0.8× 43 3.8k
Omran Al-Shamma Iraq 12 946 0.3× 1.5k 0.7× 507 0.5× 1.1k 1.4× 170 0.3× 28 5.4k
D. Jude Hemanth India 34 1.0k 0.3× 1.6k 0.8× 447 0.4× 1.5k 1.9× 206 0.3× 219 5.0k
Amjad J. Humaidi Iraq 31 748 0.3× 1.6k 0.8× 909 0.9× 1.4k 1.8× 162 0.3× 177 7.4k

Countries citing papers authored by Amith Khandakar

Since Specialization
Citations

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

Fields of papers citing papers by Amith Khandakar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amith Khandakar

This figure shows the co-authorship network connecting the top 25 collaborators of Amith Khandakar. A scholar is included among the top collaborators of Amith Khandakar 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 Amith Khandakar. Amith Khandakar 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.
Ahamed, Md. Faysal, et al.. (2025). Explainable deep learning for rainfall prediction: A CNN-XGBoost hybrid approach in the northern region of Bangladesh. Neural Computing and Applications. 37(33). 28125–28160.
2.
3.
Kashem, Saad Bin Abul, et al.. (2024). ECCDN-Net: A deep learning-based technique for efficient organic and recyclable waste classification. Waste Management. 193. 363–375. 6 indexed citations
4.
Hossain, Mohammad Istiaque, et al.. (2024). Exploring the optical and morphological properties of metal oxide thin films produced via reactive electron beam evaporation. Cogent Engineering. 11(1). 4 indexed citations
5.
Chowdhury, Muhammad E. H., Amith Khandakar, Nasser Al‐Emadi, et al.. (2024). GearFaultNet: Novel Network for Automatic and Early Detection of Gearbox Faults. IEEE Access. 12. 188755–188765. 1 indexed citations
6.
Faisal, Md. Ahasan Atick, Muhammad E. H. Chowdhury, Zaid Bin Mahbub, et al.. (2023). NDDNet: a deep learning model for predicting neurodegenerative diseases from gait pattern. Applied Intelligence. 53(17). 20034–20046. 15 indexed citations
7.
Hossain, Md Shafayet, Sakib Mahmud, Amith Khandakar, et al.. (2023). MultiResUNet3+: A Full-Scale Connected Multi-Residual UNet Model to Denoise Electrooculogram and Electromyogram Artifacts from Corrupted Electroencephalogram Signals. Bioengineering. 10(5). 579–579. 18 indexed citations
8.
Chowdhury, Muhammad E. H., et al.. (2023). A Deep Learning-Based Automatic Segmentation and 3D Visualization Technique for Intracranial Hemorrhage Detection Using Computed Tomography Images. Diagnostics. 13(15). 2537–2537. 11 indexed citations
9.
Kashem, Saad Bin Abul, et al.. (2023). GCDN-Net: Garbage classifier deep neural network for recyclable urban waste management. Waste Management. 174. 439–450. 25 indexed citations
10.
Hossain, Amran, Mohammad Tariqul Islam, Sharul Kamal Abdul Rahim, et al.. (2023). A Lightweight Deep Learning Based Microwave Brain Image Network Model for Brain Tumor Classification Using Reconstructed Microwave Brain (RMB) Images. Biosensors. 13(2). 238–238. 34 indexed citations
11.
Faisal, Md. Ahasan Atick, Sakib Mahmud, Muhammad E. H. Chowdhury, et al.. (2023). Robust and novel attention guided MultiResUnet model for 3D ground reaction force and moment prediction from foot kinematics. Neural Computing and Applications. 36(3). 1105–1121. 4 indexed citations
12.
Tahir, Anas, Muhammad E. H. Chowdhury, Amith Khandakar, et al.. (2022). COVID-19 infection localization and severity grading from chest X-ray images. Qatar University QSpace (Qatar University). 116 indexed citations breakdown →
13.
Kıranyaz, Serkan, Türker İnce, Özer Can Devecioğlu, et al.. (2022). Robust R-Peak Detection in Low-Quality Holter ECGs Using 1D Convolutional Neural Network. Qatar University QSpace (Qatar University). 61 indexed citations
14.
Chowdhury, Muhammad E. H., Amith Khandakar, Anas Tahir, et al.. (2022). Robust biometric system using session invariant multimodal EEG and keystroke dynamics by the ensemble of self-ONNs. Computers in Biology and Medicine. 142. 105238–105238. 31 indexed citations
15.
Hosseini, Saleh, Amith Khandakar, Muhammad E. H. Chowdhury, et al.. (2022). Novel and robust machine learning approach for estimating the fouling factor in heat exchangers. Energy Reports. 8. 8767–8776. 35 indexed citations
16.
Chowdhury, Muhammad E. H., Amith Khandakar, Serkan Kıranyaz, et al.. (2022). Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms. Qatar University QSpace (Qatar University). 52 indexed citations
17.
Rahman, Tawsifur, Alex Akinbi, Muhammad E. H. Chowdhury, et al.. (2022). COV-ECGNET: COVID-19 detection using ECG trace images with deep convolutional neural network. Health Information Science and Systems. 10(1). 1–1. 64 indexed citations
18.
Ayari, Mohamed Arselene, et al.. (2022). Constructing an Intelligent Model Based on Support Vector Regression to Simulate the Solubility of Drugs in Polymeric Media. Pharmaceuticals. 15(11). 1405–1405. 6 indexed citations
19.
Qiblawey, Yazan, Anas Tahir, Muhammad E. H. Chowdhury, et al.. (2021). Detection and Severity Classification of COVID-19 in CT Images Using Deep Learning. MDPI (MDPI AG). 88 indexed citations
20.
Khandakar, Amith, et al.. (2019). Portable System for Monitoring and Controlling Driver Behavior and the Use of a Mobile Phone While Driving. Sensors. 19(7). 1563–1563. 28 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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