Journal of Artificial Intelligence and Digital Health

Dr. Junaid Nasir Qureshi is an impact-driven technologist and academic leader whose career spans over 17 years, sharply divided between significant contributions to the software industry and advanced academic research. Holding a Ph.D. in Computer Science from the University of Management and Technology, Lahore, Pakistan, he possesses a rare and powerful combination of 10 years of intensive industry experience and over 7 years of dedicated service in academia. Currently, Dr. Qureshi is a dynamic Assistant Professor in the Department of Computer Science at Bahria University, Lahore Campus (BULC). In this role, he is not only shaping the next generation of computing professionals through rigorous teaching and mentorship but is also aggressively pursuing cutting-edge research to advance the field. His career is defined by his proven ability to seamlessly translate theoretical knowledge into real-world applications, effectively closing the gap between the classroom and the computing frontier. His diverse and high-impact research portfolio is focused on the most critical emerging technologies, including: Blockchain Technology: Pioneering the exploration of decentralized applications, cryptographic security, and trust mechanisms within distributed ledgers. Artificial Intelligence and Machine Learning (AI/ML): Driving intelligent system design and data-driven solutions, specializing in developing advanced algorithms for predictive modeling, automation, and enhanced decision-making across various applications. Distributed Systems: Driving innovations in scalability, reliability, and high-performance computing to solve complex networking challenges. Internet of Things (IoT): Designing and architecting smart, connected ecosystems for next-generation automation and operational efficiency. Software Engineering & Agile Project Development: Championing best practices in adaptive development methodologies and optimizing the entire software lifecycle. Human-Computer Interaction (HCI): Focused on optimizing user experience through advanced, user-centric design principles. Educational Technologies: Leading the digital transformation of learning experiences through innovative EdTech and AI-driven pedagogical approaches. Driven by a profound passion for technological advancement, Dr. Qureshi is a key contributor to the evolving landscape of computer science, continually enriching academia through influential publications, strategic collaborative research, and robust industry partnerships. His deep expertise in modern computing paradigms makes him a formidable authority in the field

• Blockchain Systems Requirements Engineering
• Data Modeling & Transformation
• Human–Computer Interaction
• IoT and Distributed Computing
• Software Testing & QA
• Software Engineering & Automation
• Agile & Distributed Software Development
• AI & Federated Learning
• Intelligent Systems

1. Assistant Professor at Bahria University
2. Member, BU Strategic Plans Committee
3. Member, Cluster Head IT & CS Committee
4. Class Advisor (Undergraduate CS)
5. Supervisor – Final Year Projects
6. Numerous workshops on research methodology, IEEE webinars, OBE training, leadership development, and Python workshops
7. Conference participation (Springer, IEEE, ICIC, INTAP)

1. A Comparison of Transfer Learning Performance versus Health Experts in Disease Diagnosis
2. A Blockchain-based Framework for Distributed Agile Software Development
3. Blockchain Applications for the Internet of Things: Systematic Review and Challenges
4. Consortium Framework Using Blockchain for Asthma Healthcare in Pandemics
5. FFM: Flood Forecasting Model using Federated Learning
6. Integration of Blockchain & Distributed DevOps for Secure Software Development
7. ChainAgilePlus Framework for Enhancing Distributed Scrum
8. ChainAgile: A Blockchain-based Agile Software Development Framework
9. Machine Learning–based Privacy-Preserving Technique for Federated Learning
10. Blockchain-Empowered Framework for Agile Software Testing Lifecycle
11. Cybersecurity Risks in DBMS: A Systematic Review