World's Best Scientists 2026 revealed!
Serkan Kiranyaz

Serkan Kiranyaz

Award Badge
Computer Science
Qatar
2026

D-Index & Metrics

Computer Science

D-Index
53
Citations
19818
World Ranking
4693
National Ranking
4

Research.com Recognitions

  • 2026 - Research.com Computer Science in Qatar Leader Award
  • 2025 - Research.com Computer Science in Qatar Leader Award

Overview

Serkan Kiranyaz is affiliated with Qatar University in Qatar and has contributed extensively to the fields of engineering, computer science, and medicine. Their research spans a diverse range of subfields including computer vision and pattern recognition, radiology, nuclear medicine and imaging, artificial intelligence, cardiology and cardiovascular medicine, as well as biomedical engineering.

The scientist has authored a significant number of publications focused on topics such as COVID-19 diagnosis using AI, ECG monitoring and analysis, EEG and brain-computer interfaces, image and signal denoising methods, non-invasive vital sign monitoring, machine fault diagnosis techniques, and radiomics and machine learning in medical imaging.

Frequent publication venues include:

  • arXiv (Cornell University)
  • Qatar University QSpace (Qatar University)
  • IEEE Access
  • Sensors
  • SSRN Electronic Journal

Among the recent papers authored or co-authored by Serkan Kiranyaz are:

  • "1D convolutional neural networks and applications: A survey," 2022, Qatar University QSpace (Qatar University)
  • "A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications," 2020, Mechanical Systems and Signal Processing
  • "Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images," 2021, Computers in Biology and Medicine
  • "COVID-19 infection localization and severity grading from chest X-ray images," 2022, Qatar University QSpace (Qatar University)
  • "1D convolutional neural networks and applications: A survey," 2020, Mechanical Systems and Signal Processing

Collaborative work features multiple frequent co-authors, including:

  • Moncef Gabbouj
  • Muhammad E. H. Chowdhury
  • Türker İnce
  • Amith Khandakar
  • Junaid Malik

Serkan Kiranyaz's research activity demonstrates engagements in both theoretical and applied aspects of engineering and biomedical sciences. The scientist's work on one-dimensional convolutional neural networks has appeared in venues connected to both Qatar University and Mechanical Systems and Signal Processing, indicating a multidisciplinary approach combining machine learning with real-world applications.

The emphasis on COVID-19-related studies, particularly those focusing on diagnosis and severity grading from medical imaging, aligns with broader trends in medical AI research during recent years. Their contributions also extend into vibration-based structural health monitoring through machine learning techniques, merging engineering disciplines with artificial intelligence.

Best Publications

  • 1D convolutional neural networks and applications: A survey

    Serkan Kiranyaz;Onur Avci;Osama Abdeljaber;Turker Ince

  • Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks

    Serkan Kiranyaz;Turker Ince;Moncef Gabbouj

  • Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks

    Turker Ince;Serkan Kiranyaz;Levent Eren;Murat Askar

  • Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks

    Osama Abdeljaber;Onur Avci;Serkan Kiranyaz;Moncef Gabbouj

  • A review of vibration-based damage detection in civil structures : from traditional methods to Machine Learning and Deep Learning applications

    Onur Avci;Osama Abdeljaber;Serkan Kiranyaz;Mohammed Hussein

  • Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images.

    Tawsifur Rahman;Amith Khandakar;Yazan Qiblawey;Anas Tahir

  • A Generic Intelligent Bearing Fault Diagnosis System Using Compact Adaptive 1D CNN Classifier

    Levent Eren;Turker Ince;Serkan Kiranyaz

  • A Generic and Robust System for Automated Patient-Specific Classification of ECG Signals

    T. Ince;S. Kiranyaz;M. Gabbouj

  • 1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data

    Osama Abdeljaber;Onur Avci;Mustafa Serkan Kiranyaz;Boualem Boashash;Boualem Boashash

  • Real-Time Fault Detection and Identification for MMC Using 1-D Convolutional Neural Networks

    Serkan Kiranyaz;Adel Gastli;Lazhar Ben-Brahim;Nasser Al-Emadi

  • 1-D Convolutional Neural Networks for Signal Processing Applications

    Serkan Kiranyaz;Turker Ince;Osama Abdeljaber;Onur Avci

  • Evolutionary artificial neural networks by multi-dimensional particle swarm optimization

    Serkan Kiranyaz;Turker Ince;Alper Yildirim;Moncef Gabbouj

  • Convolutional Neural Networks for patient-specific ECG classification

    Serkan Kiranyaz;Turker Ince;Ridha Hamila;Moncef Gabbouj

  • Wireless and real-time structural damage detection: A novel decentralized method for wireless sensor networks

    Onur Avci;Osama Abdeljaber;Serkan Kiranyaz;Mohammed Hussein

  • Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition

    Serkan Kiranyaz;Turker Ince;Moncef Gabbouj

  • Integrating Color Features in Polarimetric SAR Image Classification

    Stefan Uhlmann;Serkan Kiranyaz

  • COVID-19 infection localization and severity grading from chest X-ray images.

    Anas M. Tahir;Muhammad E.H. Chowdhury;Amith Khandakar;Tawsifur Rahman

  • Heart sound anomaly and quality detection using ensemble of neural networks without segmentation

    Morteza Zabihi;Ali Bahrami Rad;Serkan Kiranyaz;Moncef Gabbouj

  • Fractional Particle Swarm Optimization in Multidimensional Search Space

    S. Kiranyaz;T. Ince;A. Yildirim;M. Gabbouj

  • 1D Convolutional Neural Networks and Applications: A Survey

    Serkan Kiranyaz;Onur Avci;Osama Abdeljaber;Turker Ince

  • Detection of atrial fibrillation in ECG hand-held devices using a random forest classifier

    Morteza Zabihi;Ali Bahrami Rad;Aggelos K. Katsaggelos;Serkan Kiranyaz

  • Exploring the Effect of Image Enhancement Techniques on COVID-19 Detection using Chest X-rays Images

    Tawsifur Rahman;Amith Khandakar;Yazan Qiblawey;Anas Tahir

Frequent Co-Authors

Moncef Gabbouj
Moncef Gabbouj Tampere University
Alexandros Iosifidis
Alexandros Iosifidis Aarhus University
Mohammad Tariqul Islam
Mohammad Tariqul Islam National University of Malaysia
Aggelos K. Katsaggelos
Aggelos K. Katsaggelos Northwestern University
Mamun Bin Ibne Reaz
Mamun Bin Ibne Reaz National University of Malaysia
Adel Gastli
Adel Gastli Qatar University
Tapio Saramaki
Tapio Saramaki Tampere University
Sébastien Marcel
Sébastien Marcel Idiap Research Institute
Anderson Rocha
Anderson Rocha State University of Campinas
Philippe C. Baveye
Philippe C. Baveye University of Paris-Saclay

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA opens doors to diverse career pathways and advanced study options online. For those aiming to expand both technical and business acumen, consider the most affordable online MBA programs. These programs are designed to fit varying budgets and can strengthen leadership prospects in tech sectors.

Time efficiency is also key in today’s fast-paced market. If you want to upskill swiftly, you might explore 1 year master's programs online, which allow students to earn a recognized credential in a short period. Similarly, students eager to maximize return on their educational investment can consider the quickest degree to get online to jumpstart careers quickly in high-demand fields.

For those interested in cutting-edge technology, pursuing the best ai masters programs online can provide specialized knowledge in artificial intelligence at an accessible cost. Each of these options offers flexibility, making it easier to balance professional growth with personal commitments.

Best Scientists Citing Serkan Kiranyaz

Trending Scientists