Assistant professor, G. L. Bajaj College of Technology and Management, Greater Noida, India
Dr. Mahfooz Alam is an esteemed academician and researcher in the field of Computer Science, specializing in Cloud Computing, Internet of Things (IoT), Workflow Scheduling, and Machine Learning 🤖. He is currently serving as an Assistant Professor in the Department of MCA at G. L. Bajaj College of Technology and Management, Greater Noida, India 🇮🇳. With a strong academic background and years of teaching experience, Dr. Alam is dedicated to advancing knowledge in secured workflow allocation and innovative computing methodologies. His research contributions are well-recognized, with publications in reputed journals, including IEEE, Springer, Elsevier, and Wiley 📚.
Publication Profile
Google Scholar
🎓 Education
Dr. Mahfooz Alam holds a Ph.D. in Computer Science from Aligarh Muslim University (AMU), Aligarh, India 🎓. He pursued his M.Tech. in Computer Science and Engineering from Dr. A. P. J. Abdul Kalam Technical University, Lucknow. Additionally, he completed his B.C.A. and M.C.A. from Indira Gandhi National Open University (IGNOU), New Delhi. His academic journey reflects his commitment to excellence in research and innovation in computing technologies 🖥️.
💼 Experience
Dr. Alam has a wealth of teaching and research experience, having served as an Assistant Professor at Al-Barkaat College of Graduate Studies (ABCGS), Aligarh, for six years 🏫. Currently, he holds the position of Assistant Professor at G. L. Bajaj College of Technology and Management, Greater Noida. His dedication to mentoring students and contributing to research has made him a respected figure in academia. His expertise extends to cutting-edge domains such as heuristic and meta-heuristic approaches in secured workflow allocation 🔬.
🏆 Awards and Honors
Dr. Mahfooz Alam has been recognized for his significant contributions to computer science research. His work has been published in high-impact international journals and conferences, gaining citations and recognition from fellow researchers worldwide 🌍. His contributions to machine learning applications and cloud computing security have positioned him as a thought leader in the field.
🔬 Research Focus
Dr. Alam’s research primarily focuses on Cloud Computing, IoT, Workflow Scheduling, and Load Balancing ☁️. He explores innovative approaches to software defect prediction, cybersecurity in IoT, and machine learning-driven optimization techniques. His research integrates heuristic, meta-heuristic, and reinforcement learning methods to address challenges in secure computing environments 🔍.
🔚 Conclusion
Dr. Mahfooz Alam is a dedicated academician and researcher contributing extensively to cloud computing, machine learning, and IoT security. His publications, teaching, and research endeavors continue to impact the field, shaping innovative solutions for complex computational challenges 🚀. With a strong passion for advancing knowledge and technology, Dr. Alam remains a prominent figure in the global research community 🌏.
📜 Publications
Comprehensive Bibliographic Survey and Forward-Looking Recommendations for Software Defect Prediction (IEEE Access, 2025) 📖 DOI: 10.1109/ACCESS.2024.3517419
Software Defects Prediction Using Generative Adversarial Network Based Data Balancing (Book Chapter, 2025) 📖 DOI: 10.1007/978-3-031-83790-6_22
Reinforcing Defect Prediction: A Reinforcement Learning Approach (Iran Journal of Computer Science, 2025) 📖 DOI: 10.1007/s42044-024-00214-8
Ensemble Deep Learning Techniques for Time Series Analysis (Cluster Computing, 2025) 📖 DOI: 10.1007/s10586-024-04684-0
A Levelized Multiple Workflow Heterogeneous Earliest Finish Time Allocation Model (Algorithms, 2025) 📖 DOI: 10.3390/a18020099
Cybersecurity Challenges for Social, Ad-hoc, and Sensor Networks in IoT (Wireless Ad-hoc and Sensor Networks, 2024) 📖 DOI: 10.1201/9781003528982-12
Performance Evaluation on Detection of Phishing Websites Using Machine Learning Techniques (ICEECT, 2024) 📖 DOI: 10.1109/iceect61758.2024.10739275
Empowering IoT Security (Book Chapter, 2024) 📖 DOI: 10.1201/9781003460367-11
A Trustworthy Hybrid Model for Transparent Software Defect Prediction: SPAM-XAI (PLOS ONE, 2024) 📖 DOI: 10.1371/journal.pone.0307112
Security Challenges for Workflow Allocation Model in Cloud Computing Environment: A Comprehensive Survey, Framework,
Taxonomy, Open Issues, and Future Directions (Journal of Supercomputing, 2024) 📖 DOI: 10.1007/s11227-023-05873-1