Mahfooz Alam | Cloud Computing | Best Researcher Award

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Assist. Prof. Dr. Mahfooz Alam | Cloud Computing | Best Researcher Award

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

Dr. DURGADEVI P | Network security | Best Researcher Award

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Dr. DURGADEVI P | Network security | Best Researcher Award

Assistant Professor, SRM INSTITUTE OF SCIENCE AND ENGINEERING, India

Dr. P. Durgadevi is a passionate academician and researcher in the field of Computer Science and Engineering with over 16 years of teaching and research experience. She is currently serving as an Assistant Professor (S.G.) at SRM Institute of Science and Technology, Vadapalani, Chennai. Her expertise spans across Cloud Computing, Machine Learning, Artificial Intelligence, and Swarm Optimization Algorithms. She has made significant contributions to academia by mentoring research scholars, publishing high-impact papers, and actively participating in professional organizations. Her commitment to excellence has earned her multiple awards and recognitions, establishing her as a distinguished educator and researcher. 📚✨

Publication Profile

Education 🎓

Dr. Durgadevi holds a Ph.D. in Information and Communication Engineering from Anna University, Chennai (2019). She completed her M.E. in Computer Science and Engineering from Arunai Engineering College, Tiruvannamalai with 84% (2009) and her B.Tech in Information Technology from Kamban Engineering College, Tiruvannamalai with 82% (2005). Her strong academic background has laid the foundation for her impactful research in computing and optimization techniques. 🎯

Experience 👩‍🏫

With a career spanning over 16 years, Dr. Durgadevi has held various prestigious teaching positions. She has been an Assistant Professor (S.G.) at SRM Institute of Science and Technology since October 2023 and previously served as an Assistant Professor (Sr.G.) at the same institution (2020-2023). She has also worked as an Associate Professor at Vel Tech Dr. Rangarajan Dr. Sagunthala R&D Institute of Science and Technology and as an Assistant Professor at RMK College of Engineering and Technology and Arunai Engineering College. Her extensive experience in teaching, research supervision, and academic mentoring has contributed significantly to the growth of students and young researchers. 🏆

Awards and Honors 🏅

Dr. Durgadevi has received numerous accolades for her contributions to academia and research. She was honored with the “Best Teaching Faculty” award by Dr. Abdul Kalam Education Trust (2019) and the “Young Woman in Engineering” award by Venus Foundation (2018). She has been recognized as a Top Performing Mentor by NPTEL, earning multiple Elite and Silver Certifications for excellence in courses like Big Data Computing and The Joy of Computing in Python. She has also received Best Paper Awards at renowned international conferences such as ICCAI 2021 and ICOICI 2022. Her commitment to academic excellence is further demonstrated by her lifetime memberships in prestigious organizations like ISTE, CSI, IAENG, and CSTA. 🏆🌟

Research Focus 🔬

Dr. Durgadevi’s research revolves around Cloud Computing, Machine Learning, Artificial Intelligence, and Swarm Optimization Algorithms. Her Ph.D. work focused on “An Optimal Resource Discovery and Allocation in Cloud Using Hybrid Swarm Optimization Algorithms”, aiming to enhance cloud resource management efficiency. She is an active research supervisor at SRM Institute of Science and Technology, guiding four research scholars and serving as a Doctoral Committee Member for Anna University scholars. Her work emphasizes metaheuristic optimization, network security, and intelligent computing, contributing to the development of robust and scalable computing solutions. 🚀

Conclusion 🌍

Dr. P. Durgadevi is an accomplished researcher, educator, and mentor, making remarkable strides in the field of Computer Science and Engineering. Her dedication to research, excellence in teaching, and active engagement in professional communities have solidified her reputation as a leading academician. With her extensive contributions to Cloud Computing, AI, and Swarm Intelligence, she continues to inspire and shape the next generation of computing professionals. 🚀🎯

Publications 📖

Optimizing network security: Weighted average ensemble of BPNN and RELM in EPRN-WPS intrusion detection

Resource Allocation in Cloud Computing using SFLA and Cuckoo Search Hybridization, International Journal of Parallel Programming, 2020 – Cited by 34

Task Scheduling using Amalgamation of Metaheuristics Swarm Optimization Algorithm and Cuckoo Search in Cloud Computing, Journal for Research, 2015 – Cited by 11

Recognition of Face Grounded on Aging Factors by Exploiting AI Techniques, Annals of the Romanian Society for Cell Biology, 2021 – Cited by

Flood Detection and Management using IoT and Correlation Analysis, Journal of Interdisciplinary Cycle Research, 2021

Comparative Analysis of Color and Texture-Based Skin Recognition Techniques, Psychology and Education Journal, 2021

Public Key Encryption with Keyword Search, International Journal of Advance Research, Ideas, and Innovations, 2021

Prediction and Control of Accident Risks Using Logistic Model Learning Technique, Solid State Technology, 2020

Bank Endorsement Classification: A Novel Content-Based Approach Using Pupil Tracking Technology, Journal of Computational and Theoretical Nanoscience, 2020

 

Jiang Zhou | Data Security | Best Researcher Award

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Mr. Jiang Zhou | Data Security | Best Researcher Award

Associate Professor, Institute of Information Engineering, Chinese Academy of Sciences, China

👨‍🏫 Dr. Jiang Zhou is an Associate Professor at the Institute of Information Engineering, Chinese Academy of Sciences and the University of Chinese Academy of Sciences. He earned his Ph.D. from the same institution in 2014 and was a visiting scholar at Texas Tech University from 2015 to 2018. Dr. Zhou’s research focuses on data storage security, privacy computing, and distributed computing, with over 40 publications and numerous contributions to high-performance computing. He actively contributes to several major research projects and serves as a reviewer for leading journals. Dr. Zhou is a member of the IEEE and CCF.

Publication Profile

Google Scholar

Strengths for the Award:

  1. Prolific Publication Record: Jiang Zhou has published over 40 papers in prestigious journals and conferences, with 10 journal publications, 5 of which are SCI-indexed. This demonstrates a solid research foundation, especially in the field of data storage security and privacy computing.
  2. Strong Research Impact: His h-index of 11, with 193 citations since 2019 and a total of 271 citations, showcases the relevance and influence of his research in the academic community.
  3. Project Leadership: He has led significant projects, including the National Natural Science Foundation of China (NSFC) and the Strategic Priority Research Program of the Chinese Academy of Sciences, highlighting his ability to secure and manage high-profile research initiatives.
  4. Innovative Contributions: His work on developing distributed file systems (CFS), data distribution algorithms (SUORA and PRS), secure cloud storage systems, and insider threat detection methods like Log2Graph and LAAEB has direct practical implications, especially in enhancing data security for large organizations like China Mobile.
  5. International Collaboration: His collaboration with Prof. Yong Chen at Texas Tech University, along with his role as a visiting scholar, indicates his global research engagement and his ability to contribute to international projects on data-intensive scalable computing.
  6. Industry Relevance: His research has applications in industry, particularly through projects such as secure cloud storage systems and insider threat detection used by China Mobile, which further amplifies the real-world impact of his work.
  7. Professional Involvement: As an active member of the IEEE and CCF and a reviewer for high-impact journals such as TPDS, TC, and TOS, Zhou is well-integrated within the academic and professional communities, further supporting his candidacy.

Areas for Improvement:

  1. Broader Impact and Outreach: While Zhou has made notable technical contributions, greater emphasis on community outreach or public dissemination of research might improve his profile for broader recognition. Engaging more in public talks, conferences, or workshops would further solidify his reputation as a leader in his field.
  2. Patents and Consultancy: Although he has 2 patents published or in progress, focusing more on technology transfer, commercialization of his innovations, or further collaboration with industry could enhance the practical applications of his research. He currently has limited consultancy or industry collaborations beyond academia.
  3. Cross-disciplinary Work: Expanding his research into adjacent fields such as AI or machine learning, and exploring interdisciplinary collaborations could position him more strongly as a cutting-edge researcher.

 

Education

🎓 Jiang Zhou received his Ph.D. in Computer Science from the University of Chinese Academy of Sciences in 2014. His academic journey includes a visiting scholar stint at Texas Tech University, where he contributed to large-scale projects on high-performance computing and data storage. His strong educational foundation has been pivotal in driving forward his research in data security and distributed systems.

Experience

💼 Dr. Zhou holds the position of Associate Professor at the Institute of Information Engineering, Chinese Academy of Sciences. His academic career is marked by extensive involvement in cutting-edge research, particularly in data security and storage. From 2015 to 2018, he served as a visiting scholar at Texas Tech University, where he collaborated on several key projects related to scalable computing instruments for high-performance computing. He has led significant national research initiatives, including the National Natural Science Foundation of China.

Research Focus

🔬 Dr. Zhou’s research interests lie in file and storage systems, data security, parallel computing, and insider threat detection. He has made impactful contributions in optimizing I/O operations, enhancing metadata services, and improving data availability and security in large-scale distributed systems. His work has introduced innovative data distribution algorithms and insider threat detection techniques that are widely recognized in the computing community.

Awards and Honors

🏆 Throughout his academic career, Dr. Zhou has been recognized for his contributions to data storage and security. He has successfully led several national research projects and collaborated on international initiatives. His research output has earned him an esteemed reputation in the field, particularly with regard to his contributions to distributed computing and storage optimization.

Publications Top Notes

📚 Dr. Zhou has published over 40 peer-reviewed papers, including highly cited works in renowned journals such as TPDS, TC, and TSC. His top 5 SCI-indexed publications include groundbreaking research on distributed file systems, insider threat detection, and data security. His work is consistently cited, with over 271 citations to date. Below are some of his notable publications:

“Secure Data Distribution in Heterogeneous Storage Systems” (2023) – IEEE Transactions on Computers (TC), cited by 10 articles. Link

“Insider Threat Detection Using Log2Graph” (2022) – Journal of Computer Security (JCS), cited by 15 articles. Link

“High-Performance Distributed Metadata Services on Hadoop” (2021) – IEEE Transactions on Parallel and Distributed Systems (TPDS), cited by 20 articles. Link

“PRIME: A Scalable Data Management System for Cloud” (2020) – Journal of Parallel and Distributed Computing (JPDC), cited by 12 articles. Link

“Confidential Computing: Challenges and Solutions” (2019) – Computer & Security (COSE), cited by 18 articles. Link

Conclusion:

Jiang Zhou is a highly qualified candidate for the Best Researcher Award, given his strong academic contributions, leadership in impactful projects, and tangible real-world applications of his research. His innovations in data storage security, distributed systems, and insider threat detection make him an exceptional contender. Focusing more on cross-disciplinary work, commercialization, and outreach could enhance his profile even further, but overall, his current achievements are commendable and align well with the expectations of a Best Researcher Award recipient.

 

Meikang Qiu | Cloud Computing | Best Researcher Award

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Prof Dr. Meikang Qiu | Cloud Computing | Best Researcher Award

Professor, Augusta University,United States

📚 Dr. Meikang Qiu is a tenured full professor at the Department of Computer and Cyber Sciences at Augusta University. With a rich research background spanning artificial intelligence, big data, and cybersecurity, he has published over 550 papers, books, and book chapters. His work has garnered more than 25,400 citations, reflecting his significant impact on the field. As an ACM Distinguished Member and IEEE Distinguished Visitor, Dr. Qiu has supervised 12 Ph.D. students and 2 postdoctoral researchers, contributing extensively to both academia and industry.

Profile

Strengths for the Award

  1. Diverse Research Interests: Meikang Qiu’s work spans numerous fields, including AI, Big Data, Cybersecurity, IoT, Data Analytics, and more. This interdisciplinary approach can significantly impact various community sectors.
  2. High Citation Metrics: With over 25,400 citations and an H-index of 106, Qiu’s work has a proven broad impact, demonstrating significant influence in the academic community.
  3. Extensive Publications: He has authored over 550 papers/books/book chapters, showcasing a prolific output that contributes to the knowledge base in his fields of expertise.
  4. Recognition and Awards: His numerous accolades, including the IEEE Systems Journal Best Paper Award and the IEEE Big Data Security STC Founder and Pioneer Award, underline his excellence and contributions to research.
  5. Community and Educational Involvement: Qiu’s involvement in workshops and seminars, such as the GenCyber Cybersecurity Workshop for High School Teachers, highlights his commitment to community education and outreach.
  6. Leadership and Mentorship: Supervision of 12 Ph.D. students and 2 postdocs, along with significant roles in professional services (e.g., General Chair of IEEE conferences), indicates his leadership and mentorship capabilities, contributing to the academic and professional growth of others.
  7. Industrial and Practical Experience: His experience working in high-tech companies and collaborations with industry giants like Google and Amazon ensures that his research has practical applications and relevance to real-world problems.

Areas for Improvement

  1. Focus on Direct Community Impact: While Qiu’s research undoubtedly has broad implications, more emphasis on direct, measurable impacts on specific communities could strengthen his case. Detailed examples of how his work has directly benefited particular communities or societal sectors would be beneficial.
  2. Public Engagement: Increasing efforts in public dissemination of his research findings through popular media or public lectures could enhance the visibility and understanding of his work’s impact on the community.
  3. Collaboration with Community Organizations: Strengthening partnerships with community-based organizations to apply his research findings more directly in local settings could further demonstrate the tangible impact of his work.

Education

🎓 Dr. Meikang Qiu earned his Ph.D. in Computer Science from the University of Texas at Dallas in May 2007. Prior to that, he completed his M.S. in Computer Science with a perfect GPA of 4.0 from the same institution in December 2003. He also holds a Master’s degree in Industrial Engineering & Management (March 1998) and a Bachelor’s degree in Naval Architecture & Engineering (July 1992), both from Shanghai Jiao Tong University.

Experience

💼 Before joining academia, Dr. Qiu gained nine years of industry experience working with high-tech companies, where he secured over $2 million in funding and established strong connections with major tech firms like Google, Facebook, and Amazon. In academia, he has attended more than 20 NSF panels and holds significant roles in various professional organizations.

Research Interests

🔍 Dr. Qiu’s research interests are vast and multidisciplinary, encompassing artificial intelligence, reinforcement learning, data analytics, machine learning, cybersecurity, computer security, mobile systems, cloud computing, robotics, cyber-physical systems, real-time embedded systems, sensor networks, ubiquitous and pervasive computing, heterogeneous mobile networks, and smart computing and software systems.

Awards

🏆 Dr. Qiu has received numerous awards, including the 2021 IEEE Computer Society Distinguished Contributor, 2021 Founder and Pioneer Award from IEEE Big Data Security STC, 2021 Senior Leadership Award from IEEE Bio-inspired Computing STC, and has been recognized as a Highly Cited Researcher by Clarivate/Web of Science in 2020. Additionally, he is an ACM Distinguished Member since 2019 and has received multiple best paper awards.

Publications

  1. 🌟 J. Li, M. Qiu, Z. Ming, G. Quan, X. Qin, Z. Gu, “Online Optimization for Scheduling Preemptable Tasks on IaaS Cloud Systems,” Journal of Parallel and Distributed Computing, Vol. 72, No. 5, pp. 666-677, May 2012.
  2. 🌟 K. Gai, M. Qiu, H. Zhao, L. Tao, Z. Zong, “Dynamic Energy-Aware Cloudlet-based Mobile Cloud Computing Model for Green Computing,” Journal of Network and Computer Applications, Vol. 59, No. 1, pp. 46-54, 2016. (Best Research Paper 2018)
  3. 🌟 M. Qiu, Z. Ming, J. Li, K. Gai, Z. Zong, “Phase-Change Memory Optimization for Green Cloud with Genetic Algorithm,” IEEE Transactions on Computers, Vol. 64, No. 12, pp. 3528-3540, Dec. 2015. (Hot Paper 2017, Highly Cited Paper 2017-2021)
  4. 🌟 Y. Li, W. Dai, Z. Ming, M. Qiu, “Privacy Protection for Preventing Data Over-Collection in Smart City,” IEEE Transactions on Computers, Vol. 65, No. 5, pp. 1339-1350, May 2016. (Highly Cited Paper 2017-2018)
  5. 🌟 X. Gao, M. Qiu, “Energy-Based Learning for Preventing Backdoor Attack,” 15th Intl. Conf. on Knowledge Science, Eng., and Management (KSEM, Springer), Vol. 3, pp. 706-721, Aug. 2022. (Best Student Paper Award)
  6. 🌟 Y. Zeng, H. Qiu, G. Memmi, M. Qiu, “Defending Adversarial Examples in Computer Vision based on Data Augmentation Techniques,” 20th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP 2020), Oct. 2020. (Best Paper Award)
  7. 🌟 Y. Zhang, M. Qiu, C.-W. Tsai, M. Hassan, A. Alamri, “Health-CPS: Healthcare Cyber-Physical System Assisted by Cloud and Big Data,” IEEE Systems Journal, Vol. 11, No. 1, pp. 88-95, 2017. (Best Paper Award, Highly Cited Paper 2017-2019)