Touhid Bhuiyan | Cybersecurity | Outstanding Scientist Award

Published on by Innovation Technologist

Prof. Dr. Touhid Bhuiyan | Cybersecurity | Outstanding Scientist Award

Professor at Washington University of Science and Technology, United States

Dr. T. Bhuiyan is a distinguished academic and consultant in Cyber Security, with extensive experience in teaching, research, and industry. His contributions span several continents and include a wealth of publications and keynotes, focusing on the transformative role of technology in education and security. 🌍🔐📖

Publication Profile : 

Orcid

 

🎓 Educational Background :

Dr. T. Bhuiyan is a seasoned professional in Cyber Security, Software Engineering, and Databases, with over 27 years of experience in teaching and research across the USA, Australia, and Bangladesh. He holds a PhD in Computer Science from Queensland University of Technology, Australia, along with an MSc from The American University in London and a BSc (Hons) in Computing & Information Systems from the University of London. His education is complemented by numerous certifications, including Certified Information System Auditor (CISA) and Certified Ethical Hacker (CEH).

💼 Professional Experience :

In his professional journey, Dr. Bhuiyan has served as a Professor of Cyber Security at Washington University of Science and Technology, and previously held leadership roles at Daffodil International University and Polytechnic Institute Australia. His consulting experience includes a significant role as a National Consultant for Cyber Security with the UNDP and the Government of Bangladesh, where he led initiatives to enhance cyber security measures for government portals. Dr. Bhuiyan has delivered keynote speeches at international conferences and has authored multiple influential publications, including books on intelligent recommendation systems and cyber security. His research interests lie at the intersection of information security, trust management, and e-Learning, exploring how technology can enhance educational practices and health informatics.

📚 Research Interests : 

🔍 Information Security
🌐 Social Networks
🔒 Trust Management
💻 Database Management
🏥 e-Health
📚 e-Learning

📝 Publication Top Notes :

  1. Hossain, M.A., Rahman, M.Z., Bhuiyan, T., Moni, M.A. (2024). Identification of Biomarkers and Molecular Pathways Implicated in Smoking and COVID-19 Associated Lung Cancer Using Bioinformatics and Machine Learning Approaches. International Journal of Environmental Research and Public Health, 21(11), 1392.
  2. Hanip, A., Sarower, A.H., Bhuiyan, T. (2024). The Transformative Role of Generative AI in Education: Challenges and Opportunities for Enhancing Student Learning and Assessment Through Mass Integration. International Journal of Advanced Research in Engineering and Technology, 15(5), 161-175.
  3. Mahmud, A., Sarower, A.H., Sohel, A., Assaduzzaman, M., Bhuiyan, T. (2024). Adoption of ChatGPT by university students for academic purposes: Partial least square, artificial neural network, deep neural network and classification algorithms approach. Array, 21, 100339.
  4. Zannah, T.B., Abdulla-Hil-Kafi, M., Sheakh, M.A., Hasan, M.Z., Shuva, T.F., Bhuiyan, T., Rahman, M.T., Khan, R.T., Kaiser, M.S., Whaiduzzaman, M. (2024). Bayesian Optimized Machine Learning Model for Automated Eye Disease Classification from Fundus Images. Computation, 12(190).
  5. Bishshash, P., Nirob, M.A.S., Shikder, M.H., Sarower, M.A.H., Bhuiyan, T., Noori, S.R.H. (2024). A Comprehensive Cotton Leaf Disease Dataset for Enhanced Detection and Classification. Data in Brief, 57, 110913.
  6. Tamal, M.A., Islam, M.K., Bhuiyan, T., Sattar, A., Prince, N.U. (2024). Unveiling suspicious phishing attacks: enhancing detection with an optimal feature vectorization algorithm and supervised machine learning. Frontiers in Computer Science, 6, 1428013.
  7. Tamal, M.A., Islam, M.K., Bhuiyan, T., Sattar, A. (2024). Dataset of suspicious phishing URL detection. Frontiers in Computer Science, 6, 1308634.
  8. Sholi, R.T., Sarker, …, Bhuiyan, T., Shakil, S.M.K.A., Ahmed, M.F. (2024). Application of Computer Vision and Mobile Systems in Education: A Systematic Review. International Journal of Interactive Mobile Technologies, 18(1), 168-187.
  9. Ahad, M.T., Li, Y., Song, B., Bhuiyan, T. (2023). Comparison of CNN-based deep learning architectures for rice diseases classification. Artificial Intelligence in Agriculture, 9(1), 22-35.
  10. Basar, M.A., Hosen, M.F., Paul, B.K., …, Bhuiyan, T. (2023). Identification of drug and protein-protein interaction network among stress and depression: A bioinformatics approach. Informatics in Medicine Unlocked, 37, 101174.
  11. Paul, S.G., Saha, A., Arefin, M.S., Bhuiyan, T., …, Moni, M.A. (2023). A Comprehensive Review of Green Computing: Past, Present, and Future Research. IEEE Access, 11, 87445-87494.
  12. Sarker, S., Arefin, M.S., Kowsher, M., Bhuiyan, T., Dhar, P.K., Kwon, O.J. (2022). A Comprehensive Review on Big Data for Industries: Challenges and Opportunities. IEEE Access, 11, 744-769.
  13. Asaduzzaman, S., Rehana, H., Bhuiyan, T., Eid, M.M.A., Rashed, A.N.Z. (2022). Extremely high birefringent slotted core umbrella-shaped photonic crystal fiber in terahertz regime. Applied Physics B, 128(148).
  14. Bhuiyan, T. (2022). Transitioning from education to work during the 4th Industrial Revolution. AIB Review, 7, Adelaide, Australia.
  15. Ali, M.N.B., Saudi, M.M., Bhuiyan, T., Ahmad, A.B., Islam, M.N. (2021). NIPSA Intrusion Classification. Journal of Engineering Science and Technology, 16(4), 3534-3547.

 

 

 

 

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]

 

 

 

 

Negalign Wake Hundera | Cybersecurity | Best Researcher Award

Published on by Innovation Technologist

Assist. Prof. Dr. Negalign Wake Hundera | Cybersecurity | Best Researcher Award

Postdoctoral Researcher of Zhejiang Normal University, China

Dr. Negalign Wake Hundera is a seasoned researcher and educator with a Ph.D. in Software Engineering and extensive experience in network security and IoT technologies. His career reflects a strong commitment to advancing research and teaching in technology-driven fields. With a proven track record in publishing, guiding students, and leading technical teams, he is now seeking opportunities to further his research and contribute to innovative projects in academia or industry. 🌍🔐💻📚

Publication Profile : 

Scopus

🎓 Educational Background :

Negalign Wake Hundera completed his Ph.D. in Software Engineering at the University of Electronic Science and Technology of China (UESTC), Chengdu, in June 2021, under the guidance of Prof. Hu Xiong. Prior to this, he earned an M.Sc. in Computer Science and Technology from UESTC in 2016 and a Bachelor’s degree in Information Technology from Jimma University, Ethiopia, in 2009.

💼 Professional Experience :

Negalign’s professional journey spans roles in academia and industry. He has served as a Postdoctoral Research Fellow at Zhejiang Normal University, Jinhua, China, from August 2022 to August 2024, contributing to high-impact journals and guiding students through their research projects. Before this, he was an Assistant Professor and Lecturer at Wolkite University, Ethiopia, where he not only taught but also led significant projects related to ICT infrastructure and network security. He has also held a leadership position as the Information Communication and Network Infrastructure Team Leader at Wolkite University, overseeing the development and management of the institution’s network infrastructure.

📚 Research Interests : 

Negalign’s research focuses on several cutting-edge areas including network security, public key cryptography, information security, IoT, wireless sensor networks, cloud computing, deep learning, real-time object detection, vehicular networks, and UAV networks. His work aims to apply these technologies in practical fields such as healthcare, intelligent transportation systems, smart agriculture, and cybersecurity.

📝 Publication Top Notes :

  1. Hundera, N. W., Aftab, M. U., Mesfin, D., Xu, H., & Zhu, X. (2024). An efficient heterogeneous online/offline anonymous certificateless signcryption with proxy re-encryption for Internet of Vehicles. Vehicular Communications, 49, 100811. [Open Access]
  2. Hundera, N. W., Shumeng, W., Mesfin, D., Xu, H., & Zhu, X. (2024). An efficient online/offline heterogeneous proxy signcryption for secure communication in UAV networks. Journal of King Saud University – Computer and Information Sciences, 36(5), 102044. [Open Access]
  3. Leka, H. L., Fengli, Z., Kenea, A. T., Tohye, T. G., Tegene, A. T., & Hundera, N. W. (2023). PSO-Based Ensemble Meta-Learning Approach for Cloud Virtual Machine Resource Usage Prediction. Symmetry, 15(3), 613. [Open Access]
  4. Tohye, T. G., Qin, Z., Leka, H. L., & Hundera, N. W. (2023). Glaucoma Detection Using Convolutional Neural Network (CNN). In Proceedings of the 20th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP 2023).
  5. Assefa, A. A., Tian, W., Hundera, N. W., & Aftab, M. U. (2022). Crowd Density Estimation in Spatial and Temporal Distortion Environment Using Parallel Multi-Size Receptive Fields and Stack Ensemble Meta-Learning. Symmetry, 14(10), 2159. [Open Access]
  6. Hundera, N. W., Jin, C., Geressu, D. M., Olanrewaju, O. A., & Xiong, H. (2022). Proxy-based public-key cryptosystem for secure and efficient IoT-based cloud data sharing in the smart city. Multimedia Tools and Applications, 81(21), 29673–29697.
  7. Hundera, N. W., Jin, C., Aftab, M. U., Mesfin, D., & Kumar, S. (2021). Secure outsourced attribute-based signcryption for cloud-based Internet of Vehicles in a smart city. Annales des Telecommunications/Annals of Telecommunications, 76(9-10), 605–616.
  8. Leka, H. L., Fengli, Z., Kenea, A. T., Atandoh, P., & Hundera, N. W. (2021). A Hybrid CNN-LSTM Model for Virtual Machine Workload Forecasting in Cloud Data Center. In Proceedings of the 18th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP 2021), 474–478.
  9. Hundera, N. W., Mei, Q., Xiong, H., & Geressu, D. M. (2020). A secure and efficient identity-based proxy signcryption in cloud data sharing. KSII Transactions on Internet and Information Systems, 14(1), 455–472.
  10. Oluwasanmi, A., Akeem, S., Jehoaida, J., Baagere, E., Qin, Z., & Hundera, N. W. (2019). Sequential multi-kernel convolutional recurrent network for sentiment classification. In Proceedings of the IEEE International Conference on Software Engineering and Service Sciences (ICSESS), 129–133.