Adelina Aleksieva-Petrova | Secure | Women Researcher Award

Published on by Innovation Technologist

Assoc. Prof. Dr. Adelina Aleksieva-Petrova | Secure | Women Researcher Award

Technical University of Sofia | Bulgaria

Assoc. Prof. Dr. Adelina Aleksieva-Petrova is a Bulgarian computer scientist whose research spans semantic technologies, software engineering, machine learning, cybersecurity, and intelligent systems. According to Scopus, she has authored 42 publications, which have received 185 citations, with an h-index of 6. Her work integrates theoretical and applied research, with notable contributions in deep learning for air pollution prediction, secure data storage systems, learning analytics, and software security. She has published in high-impact international journals such as Sustainability, Remote Sensing, Electronics, and Computers in Human Behavior. Her research is characterized by interdisciplinary collaboration, combining artificial intelligence, data science, and software architecture to address real-world technological and societal challenges.

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Featured Publications


A Hybrid Spatiotemporal Deep Model Based on CNN and LSTM for Air Pollution Prediction

S. Tsokov, M. Lazarova, A. Aleksieva-Petrova – Sustainability, 2022 · 80 citations

Playing Styles Based on Experiential Learning Theory

B. Bontchev, D. Vassileva, A. Aleksieva-Petrova, M. Petrov – Computers in Human Behavior, 2018 · 74 citations

Authentication Mechanisms and Classification: A Literature Survey

I. Chenchev, A. Aleksieva-Petrova, M. Petrov – Intelligent Computing (Computing Conference), 2021 · 30 citations

Using Open Technical E-Learning Standards and Service-Orientation to Support New Forms of E-Assessment

Y. Miao, C. Tattersall, J. Schoonenboom, K. Stevanov, A. Aleksieva-Petrova – 2007 · 19 citations

A Four-Stage Model for Lifelong Competence Development

J. Schoonenboom, C. Tattersall, Y. Miao, K. Stefanov, A. Aleksieva-Petrova – 2007 · 18 citations

Qasem Abu Al-Haija | Defensive Security | Best Researcher Award

Published on by Innovation Technologist

Dr. Qasem Abu Al-Haija | Defensive Security | Best Researcher Award

Department of Cybersecurity at Jordan University of Science and Technology, Jordan

🔍 Dr. Qasem S. Abu Al-Haija is an accomplished educator and researcher in the field of cybersecurity and IoT. With a passion for developing intelligent detection systems and efficient cryptographic methods, he strives to advance the landscape of technology. 🌐✨ His commitment to teaching and mentoring the next generation of engineers is matched only by his dedication to impactful research. 📚🔒

Publication Profile : 

Scopus

🎓 Educational Background :

Dr. Qasem S. Abu Al-Haija holds a PhD in Computer and Information Systems Engineering from Tennessee State University (2020) with a perfect GPA of 4.00. His dissertation focused on intelligent IoT attack detection using non-traditional machine learning methods. He also earned a Master’s degree in Computer Engineering from Jordan University of Science and Technology (2009), specializing in efficient algorithms for ECC cryptography, and a Bachelor’s degree in Electrical and Computer Engineering from Mu’tah University (2005).

💼 Professional Experience :

Dr. Abu Al-Haija is currently an Assistant Professor in the Department of Cybersecurity at Jordan University of Science and Technology, where he conducts research in AI and cybersecurity. Previously, he held similar positions at Princess Sumaya University for Technology and the University of Petra, teaching various cybersecurity and data science courses. His extensive experience includes postdoctoral research at Tennessee State University and a lecturer role at King Faisal University, where he taught numerous engineering courses and supervised many capstone projects. Throughout his career, he has contributed to various funded research projects and has actively engaged in academic committees and training programs.

📚 Research Interests : 

His research interests encompass machine learning, cybersecurity, IoT/CPS modeling, and embedded systems, aiming to enhance the security and efficiency of interconnected systems.

📝 Publication Top Notes :

  • Q. Abu Al-Haija, M. Al Fayoumi, “An intelligent identification and classification system for malicious uniform resource locators (URLs),” Neural Computing and Applications (NCAA), Springer, 2023.
  • Q. Abu Al-Haija, M. AlOhaly, M. Odeh, “A Lightweight Double-Stage Scheme to Identify Malicious DNS over HTTPS Traffic Using a Hybrid Learning Approach,” Sensors, MDPI, 2023.
  • Q. Abu Al-Haija, A. Al Badawi, “High-performance intrusion detection system for networked UAVs via deep learning,” Neural Computing and Applications (NCAA), Springer, 2022.
  • Q. Abu Al-Haija, A. Al Badawi, “Boost-Defense for Resilient IoT Networks: A Head-to-Toe Approach,” Expert Systems, Wiley, 2022.
  • Q. Abu Al-Haija, “Top-Down Machine Learning Based Architecture for Cyberattacks Identification and Classification in IoT Communication Networks,” Frontiers in Big Data: Cybersecurity and Privacy, Frontiers, 2022.
  • Q. Abu Al-Haija, M. Krichen, W. Abu Elhaija, “Machine-Learning-Based Darknet Traffic Detection System for IoT Applications,” Electronics, MDPI, Vol. 11(4), 2022.
  • S. Zidi, A. Mihoub, S. Qaisar, M. Krichen, Q. Abu Al-Haija, “Theft detection dataset for benchmarking and machine learning based classification in a smart grid environment,” Journal of King Saud University-Computer and Information Sciences, Elsevier, In Press, 2022.
  • Altamimi, S., Abu Al-Haija, Q. “Maximizing intrusion detection efficiency for IoT networks using extreme learning machine,” Discover Internet of Things, 2024, 4(1), 5. [Open access]
  • Alsulami, A.A., Abu Al-Haija, Q., Alturki, B., Alghamdi, B., Alsemmeari, R.A. “Exploring the efficacy of GRU model in classifying the signal to noise ratio of microgrid model,” Scientific Reports, 2024, 14(1), 15591. [Open access]
  • Abu Al-Haija, Q., Altamimi, S., AlWadi, M. “Analysis of Extreme Learning Machines (ELMs) for intelligent intrusion detection systems: A survey,” Expert Systems with Applications, 2024, 253, 124317. [Review]
  • Al-Fayoumi, M., Alhijawi, B., Al-Haija, Q.A., Armoush, R. “XAI-PhD: Fortifying Trust of Phishing URL Detection Empowered by Shapley Additive Explanations,” International Journal of Online and Biomedical Engineering, 2024, 20(11), pp. 80–101.
  • Khalil, M., Al-Haija, Q.A. “Ethical machine learning for internet of things network,” in Ethical Artificial Intelligence in Power Electronics, 2024, pp. 12–20. [Book Chapter]
  • Al-Haija, Q.A. “Preface,” in Smart and Agile Cybersecurity for IoT and IIoT Environments, 2024, pp. viii–xii. [Editorial]
  • Ayyad, W.R., Al-Haija, Q.A., Al-Masri, H.M.K. “Human factors in cybersecurity,” in Smart and Agile Cybersecurity for IoT and IIoT Environments, 2024, pp. 235–256. [Book Chapter]
  • Al-Haija, Q.A. Smart and Agile Cybersecurity for IoT and IIoT Environments, 2024, pp. 1–397. [Book]
  • Al-Tamimi, S.A., Al-Haija, Q.A. “Supply chain security, technological advancements, and future trends,” in Smart and Agile Cybersecurity for IoT and IIoT Environments, 2024, pp. 211–234. [Book Chapter]
  • Saif, A., Al-Haija, Q.A. “Artificial Intelligence (AI)-powered internet of things (IoT): Smartening Up IoT,” in Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science, 2024, pp. 18–29. [Book Chapter]