Das, Resul

About

Resul Das is a full professor in the Department of Software Engineering at the Faculty of Technology, Fırat University. He earned his B.Sc. and M.Sc. degrees in Computer Science from Fırat University in 1999 and 2002, respectively, and completed his Ph.D. in Electrical and Electronics Engineering in 2008. Between 2000 and 2011, he served as a lecturer in the Department of Informatics and worked as a network and system administrator at the University's IT Center. Since 2002, he has been an instructor in the Cisco Networking Academy Program, teaching CCNA and CCNP courses. From September 2017 to June 2018, he researched as a visiting professor at the University of Alberta, Edmonton, Canada, under the TÜBİTAK-BİDEB 2219 Postdoctoral Research Fellowship program. He served as Head of the Department of Software Engineering from March 2020 to April 2023.

Prof. Das has held editorial roles in several prestigious academic journals. He was an Associate Editor for IEEE Access and the Turkish Journal of Electrical Engineering and Computer Science. Currently, he serves as an Associate Editor for Elsevier journals (Internet of Things, Alexandria Engineering Journal, and Telematics and Informatics Reports), IEEE Open Journal of the Communications Society (OJ-COMS), and the International Journal of Grid and Utility Computing (Inderscience).
Globally recognized for his contributions, Prof. Daş has been included in the top 2\% of the "World's Most Influential Scientists" list, compiled by Stanford University researchers, for five consecutive years (2019–2025). His research interests encompass computer networks, cybersecurity, IoT and systems engineering, data science and visualization, software quality assurance, and testing.

Employment

Employment history is unavailable.

Education

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Projects & Funding

Projects & funding information is unavailable.

Publications (147)

• Cybersecurity of data communication networks: A comprehensive survey of threats, challenges, technical solutions, and future research directions
  Computer Networks 2026 DOI: 10.1016/j.comnet.2026.112789
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• Knowledge graph visualization and anomaly detection from cyber threat intelligence dataset using graph neural networks based methods
  Computer Networks 2026 DOI: 10.1016/j.comnet.2026.112632
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• A novel hybrid approach based on self-supervised transformers and explainable AI for multilingual fake text detection
  Expert Systems with Applications 2026 DOI: 10.1016/j.eswa.2026.132678
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• SIMURG: Strategic intelligent framework for realtime3D visualization and high-altitude analysis of global cyber threats
  EAI Endorsed Transactions on Industrial Networks and Intelligent Systems 2026 DOI: 10.4108/eetinis.13.12740
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• Scalable object-relational modeling for synthesizing multi-format visual analytics of STIX-based cyber threat intelligence data
  EAI Endorsed Transactions on Industrial Networks and Intelligent Systems 2026 DOI: 10.4108/eetinis.132.12774
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• A spatio-temporal deep learning-based decision support system for energy awareness in IoT-based smart buildings
  Internet of Things 2026 DOI: 10.1016/j.iot.2025.101856
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• An effective new penetration test approach to detect web attacks on web applications
  Expert Systems with Applications 2026 DOI: 10.1016/j.eswa.2025.129623
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• A new hybrid approach combining transformer-based language models and graph neural networks for cryptocurrency forecasting
  Engineering Applications of Artificial Intelligence 2026 DOI: 10.1016/j.engappai.2025.113179
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• A novel enhanced neural network for anomaly detection in the IoT environment
  Computers and Electrical Engineering 2026 DOI: 10.1016/j.compeleceng.2025.110833
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• Discovery of new anti-HIV candidate molecules with an AI-based multi-stage system approach using molecular docking and ADME predictions
  Chemometrics and Intelligent Laboratory Systems 2025 DOI: 10.1016/j.chemolab.2025.105543
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• Prediction and graph visualization of cyber attacks using graph attention networks
  Computers & Security 2025 DOI: 10.1016/j.cose.2025.104534
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• Deepfake Detection for Digital Image Security using Deep Learning Methods
  Balkan Journal of Electrical and Computer Engineering 2025 DOI: 10.17694/bajece.1624564
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• A survey on data fusion approaches in IoT-based smart cities: Smart applications, taxonomies, challenges, and future research directions
  Information Fusion 2025 DOI: 10.1016/j.inffus.2025.103102
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• A new hybrid approach combining GCN and LSTM for real-time anomaly detection from dynamic computer network data
  Computer Networks 2025 DOI: 10.1016/j.comnet.2025.111372
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• Comparative Review of Graphical User Interface Based Data Visualization Tools
  Türk Doğa ve Fen Dergisi 2025 DOI: 10.46810/tdfd.1628295
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• Green IoT for energy efficiency: Enabling technologies, challenges, and future research directions
  Resul Daş, Iliyasu Yahaya Adam, Hakan Fehmi Oztop
  Thermal Science and Engineering Progress 2025 DOI: 10.1016/j.tsep.2025.103592
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• A novel hybrid model combining Vision Transformers and Graph Convolutional Networks for monkeypox disease effective diagnosis
  Information Fusion 2025 DOI: 10.1016/j.inffus.2024.102858
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• A Novel Approach for Cyber Threat Analysis Systems Using BERT Model from Cyber Threat Intelligence Data
  Symmetry 2025 DOI: 10.3390/sym17040587
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• GAINET: Enhancing drug–drug interaction predictions through graph neural networks and attention mechanisms
  Chemometrics and Intelligent Laboratory Systems 2025 DOI: 10.1016/j.chemolab.2025.105337
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• Blockchain-Integrated Framework for Data Security: An Application Based on IoT Data and Deep Learning
  Balkan Journal of Electrical and Computer Engineering 2025 DOI: 10.17694/bajece.1625208
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