Akashdeep Bhardwaj | Cybersecurity | Editorial Board Member

Published on by NESIN Awards

Dr.  Akashdeep Bhardwaj | Cybersecurity | Editorial Board Member

University of Petroleum and Energy Studies | India

Akashdeep Bhardwaj is a distinguished researcher affiliated with the University of Petroleum and Energy Studies, Dehradun, India, with expertise spanning cybersecurity, intrusion detection, cyber-physical systems security, IoT protection frameworks, and machine-learning-based threat analysis. His research contributions include the development of robust intrusion detection models using statistical feature-selection techniques, elasticsearch-based threat-hunting mechanisms, and advanced security architectures for cyber-physical robotic systems. He has published extensively in high-impact international journals such as Scientific Reports, Eurasip Journal on Information Security, Computers & Security, Egyptian Informatics Journal,Measurement Sensors, and the Journal of Database Management. His interdisciplinary work also includes deep learning applications in medical imaging, particularly diabetic-retinopathy detection using residual networks. In addition to journal publications, he has authored key academic books, including Mastering Cybersecurity: A Practical Guide to Cyber Tools and Techniques (Volume 2) and A Practical Approach to Open Source Intelligence (OSINT) – Volume 1, highlighting his commitment to knowledge dissemination and professional capacity building. With collaborations involving over 100 co-authors worldwide, his work significantly contributes to enhancing digital security, strengthening smart-infrastructure resilience, and advancing next-generation threat-mitigation strategies. His academic influence and research productivity are reflected in his metrics 1,208 citations by 1,097 documents, 110 documents, and an h-index of 21.

Profiles: Google Scholar | Scopus | ORCID | LinkedIn

Featured Publications

1. Security Algorithms for Cloud Computing Bhardwaj, A., Subrahmanyam, G. V. B., Avasthi, V., & Sastry, H. (2016). Security algorithms for cloud computing. Procedia Computer Science, 85, 535–542. Citations: 162

2. Smart IoT and Machine Learning-Based Framework for Water Quality Assessment and Device Component Monitoring Bhardwaj, A., Dagar, V., Khan, M. O., Aggarwal, A., Alvarado, R., Kumar, M., … (2022). Smart IoT and machine learning-based framework for water quality assessment and device component monitoring. Environmental Science and Pollution Research, 29(30), 46018–46036. Citations: 121

3. Penetration Testing Framework for Smart Contract Blockchain Bhardwaj, A., Shah, S. B. H., Shankar, A., Alazab, M., Kumar, M., & Gadekallu, T. R. (2021). Penetration testing framework for smart contract blockchain. Peer-to-Peer Networking and Applications, 14(5), 2635–2650. Citations: 121

4. Machine Learning-Based Regression Framework to Predict Health Insurance Premiums Kaushik, K., Bhardwaj, A., Dwivedi, A. D., & Singh, R. (2022). Machine learning-based regression framework to predict health insurance premiums. International Journal of Environmental Research and Public Health. Citations: 118

5. Ransomware Digital Extortion: A Rising New Age Threat Bhardwaj, A., Avasthi, V., Sastry, H., & Subrahmanyam, G. V. B. (2016). Ransomware digital extortion: A rising new age threat. Indian Journal of Science and Technology, 9(14), 1–5. Citations: 92

Abdul Razaque | Cybersecurity | Best Researcher Award

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Prof. Dr. Abdul Razaque | Cybersecurity | Best Researcher Award

Professor | Satbayev University | Kazakhstan

Prof. Dr.Abdul Razaque is an accomplished cybersecurity and computer science scholar with more than twenty years of academic, research, and industry experience spanning the United States, Kazakhstan, China, South Korea, France, Morocco, and Pakistan. Currently a Professor of Cybersecurity at Satbayev University and a Postdoctoral Researcher at Gachon University, he has previously served in multiple tenure-track positions, directed international IT projects for UNESCO, and contributed to national ICT initiatives. His research expertise covers cybersecurity, IoT, cloud and edge computing, artificial intelligence, blockchain systems, wireless sensor networks, and smart-city technologies. He has authored more than 200 peer-reviewed publications, including high-impact Q1 journals such as Computer Science Review, IEEE Access, Sensors, Internet of Things, and Future Generation Computer Systems, alongside several books and book chapters. His work has accrued thousands of citations globally, reflecting sustained scholarly influence across interdisciplinary domains. As Principal Investigator or Co-Investigator, he has secured over US$6 million in competitive national and international research funding, leading large-scale projects in intelligent systems, cybersecurity frameworks, image-based monitoring, smart city infrastructures, and privacy-preserving architectures. His collaborative network spans leading institutions across the United States, Korea, Kazakhstan, Saudi Arabia, Europe, and South Asia, with repeated partnerships involving multidisciplinary teams of engineers, computer scientists, medical researchers, and industry stakeholders. Throughout his career, he has demonstrated a commitment to societal impact by developing scalable technologies for public safety, healthcare, digital governance, secure urban infrastructure, and advanced educational systems. His contributions extend to mentoring students, advising theses, shaping curricula, and promoting global research exchange. Recognized with awards including the Best Engineering Student Researcher Award, and supported by extensive professional certifications in cybersecurity, data science, AI, and enterprise technologies, he represents a globally engaged researcher dedicated to advancing secure, intelligent, and equitable digital ecosystems.

Profiles: Google Scholar | Scopus | ORCID

Featured Publications

Almiani, M., AbuGhazleh, A., Al-Rahayfeh, A., Atiewi, S., & Razaque, A. (2020). Deep recurrent neural network for IoT intrusion detection system. Simulation Modelling Practice and Theory, 101, 102031.

Razaque, A., Bleakley, C., & Dobson, S. (2013). Compression in wireless sensor networks: A survey and comparative evaluation. ACM Transactions on Sensor Networks (TOSN), 10(1), Article 5.

Adnan, M., Razaque, A., Ahmed, I., & Isnin, I. F. (2014). Bio-mimic optimization strategies in wireless sensor networks: A survey. Sensors, 14(1), 299–345.

Al-lQubaydhi, N., Alenezi, A., Alanazi, T., Senyor, A., Alanezi, N., Alotaibi, B., … Razaque, A. (2024). Deep learning for unmanned aerial vehicles detection: A review. Computer Science Review, 51, 100614.

Razaque, A., & Sallah, M. (2013). The use of mobile phone among farmers for agriculture development. International Journal of Scientific Research, 2, 95–98.

Abdul Razaque’s work advances secure, intelligent, and scalable digital systems that strengthen cybersecurity, smart-city infrastructure, and data-driven decision-making across governments, industry, and academia. By integrating AI, blockchain, and IoT technologies into real-world solutions, he enhances public safety, operational efficiency, and technological resilience. His vision is to build globally accessible, trustworthy, and innovative digital ecosystems that drive sustainable societal and economic progress.