Mrs. Ionela Chereja | Privacy of data | Best Researcher Award

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Mrs. Ionela Chereja | Privacy of data | Best Researcher Award

Data Engineer and Doctoral student, Technical University of Cluj-Napoca, Romania

Ionela Chereja is a dedicated Data Engineer and doctoral student at the Technical University of Cluj-Napoca, Romania. With over 12 years of experience in data engineering and research, she has contributed significantly to data warehousing, database administration, performance optimization, and data privacy. Her expertise extends to developing frameworks that enhance data security in complex ecosystems.

Publication Profile

Scopus

🎓 Academic Background:

Ionela holds a Bachelor’s degree in Computer Science and a Master’s degree in Databases (Data Science). She is currently pursuing her Ph.D., focusing on privacy assessment frameworks for multilayered data ecosystems. Her academic journey has been marked by a deep commitment to advancing data security and architecture.

💼 Professional Experience:

With extensive industry experience, Ionela has worked on numerous data ecosystem projects in education, media, retail, finance, private hosting, and advertising. She has been instrumental in developing data storage solutions that balance performance and privacy while ensuring compliance with industry regulations.

🏆 Awards and Honors:

Ionela has been recognized for her research contributions in data privacy and security. Her work on privacy assessment frameworks has been widely appreciated in academic and professional circles, earning her citations and collaborations in high-impact research projects.

🔬 Research Focus:

Her primary research interests include data privacy, data storage systems, and data architecture. She is actively engaged in developing innovative assessment frameworks that address security challenges in complex data ecosystems, aiming to improve vulnerability detection and risk mitigation strategies.

🔎 Conclusion:

Ionela Chereja is a passionate researcher and industry expert committed to enhancing data privacy and security in modern ecosystems. Through her academic and professional journey, she continues to bridge the gap between research and real-world applications, making valuable contributions to the field of data engineering.

🔗 Publications Top Notes:

Muhammad Bilal Mahmood | Security | Best Researcher Award

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Mr. Muhammad Bilal Mahmood | Security | Best Researcher Award

PhD Scholar, Dalian University of Technology, China

Muhammad Bilal Mahmood is a dedicated researcher and educator in Software Engineering, currently pursuing his Ph.D. at Dalian University of Technology, China 🎓. With a strong foundation in Computer Engineering and extensive expertise in machine learning, natural language processing, and cybersecurity, he has contributed significantly to academia and research. As a lecturer at The University of Lahore, Pakpattan Campus, since 2017, he has been instrumental in shaping young minds and fostering innovation 💡. His research interests include deep learning, facial expression recognition, and AI-driven cybersecurity solutions.

Publication Profile

ORCID

📚 Education

Muhammad Bilal Mahmood’s academic journey reflects his passion for cutting-edge technology and innovation 🚀. He is currently a Ph.D. candidate in Software Engineering (2021–2025) at Dalian University of Technology, China. Prior to this, he earned his MS in Computer Engineering from NUST College of Electrical & Mechanical Engineering, Rawalpindi, Pakistan (2015) 🎓. His undergraduate studies in Computer System Engineering were completed at NFC Institute of Engineering & Technological Training, Multan, Pakistan (2011), laying the groundwork for his expertise in programming and research.

💼 Experience

With over six years of academic and research experience, Muhammad Bilal Mahmood has been serving as a Lecturer at The University of Lahore, Pakpattan Campus, since 2017 🏫. His responsibilities include developing system requirement specifications, designing databases, programming under strict coding guidelines, and ensuring seamless project management 📊. His ability to mentor students and collaborate with fellow researchers has made him a valuable asset in the field of software engineering.

🏆 Awards and Honors

Throughout his career, Muhammad Bilal Mahmood has been recognized for his contributions to research and academia 🏅. His innovative work in deep learning, NLP, and cybersecurity has earned him appreciation within the research community. His expertise in artificial intelligence-driven security solutions has led to impactful publications, making significant contributions to advancing technological frontiers.

🔬 Research Focus

Muhammad Bilal Mahmood’s research primarily revolves around artificial intelligence, deep learning, and cybersecurity 🔍. His work includes speech emotion recognition, malicious package detection in PyPI, and facial expression analysis using convolutional neural networks 🤖. He has also contributed to medical image processing, topic discovery in health data, and chatbot development for university applications. His interdisciplinary research bridges the gap between AI and real-world applications, improving human-computer interactions.

📝 Conclusion

Muhammad Bilal Mahmood is a passionate researcher, educator, and software engineer dedicated to advancing AI-driven solutions and cybersecurity methodologies 💡. His commitment to academia, combined with his innovative research projects, makes him a valuable contributor to the field. Through his teaching and research, he continues to inspire the next generation of engineers and scientists, pushing the boundaries of technological advancements. 🚀

📄 Publications

Recognizing Semi-Natural and Spontaneous Speech Emotions Using Deep Neural Networks – This research explores deep learning-based speech emotion recognition to enhance human-computer interaction. [Published in: Journal Name, Year] 📜🔗

PypiGuard: A novel meta-learning approach for enhanced malicious package detection in PyPI through static-dynamic feature fusion – This paper introduces a cutting-edge security framework for detecting malicious packages in Python’s package repository. [Published in: Journal Name, Year] 📜🔗

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

 

Nordine Quadar | Cybersecurity | Best Researcher Award

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Mr. Nordine Quadar | Cybersecurity | Best Researcher Award

Researcher, Royal Military College of Canada, Canada

🎓 Nordine Quadar, P.Eng, is a dedicated technical manager, researcher, and educator based in Montreal, Canada. With a strong foundation in engineering and advanced expertise in cybersecurity and artificial intelligence, he specializes in leveraging cutting-edge technologies to enhance the security of UAV systems. Passionate about teaching, he has guided students through complex subjects and contributed significantly to the fields of smart grids, IoT, and machine learning.

Publication Profile

Google Scholar

Education

📚 Nordine Quadar holds a PhD in Computer Science (in progress, 2022–2025) from the Royal Military College of Canada, supervised by Abdellah Chehri, focusing on UAV cybersecurity using Edge AI. He earned a Master of Applied Science in Electrical & Computer Engineering (2015–2018) from the University of Ottawa under the supervision of Claude D’Amours, with a thesis on spatial modulation for MIMO-CDMA systems. He also completed his Bachelor of Applied Science in Electrical Engineering (2011–2014) at the University of Ottawa.

Experience

💼 Technical Expertise defines Nordine’s career. As a teaching assistant at the University of Ottawa (2015–2017), he facilitated labs, study groups, and lecture preparations for courses like computer networks, applied electromagnetism, and computer architecture. His role demonstrated his commitment to nurturing student success and understanding.

Research Interests

🔍 Nordine’s research interests center on cybersecurity, AI-powered intrusion detection systems, digital twins for smart grids, and IoT testbeds. He explores emerging technologies to solve real-world challenges, combining theoretical innovation with practical applications.

Awards

🏆 Nordine has earned recognition for his impactful contributions to engineering and research, highlighting his commitment to excellence in academia and technical leadership.

Publications

N. Mchirgui, N. Quadar, et al. The Applications and Challenges of Digital Twin Technology in Smart Grids: A Comprehensive Review. Applied Sciences, 2024. DOI:10.3390/app142310933

N. Quadar, A. Chehri, et al. Intrusion Detection Systems in Automotive Ethernet Networks: Challenges, Opportunities and Future Research Trends. IEEE Internet of Things Magazine, 2024, Vol. 7, No. 2, pp. 62–68.

N. Quadar, M. Rahouti, et al. IoT-AI/Machine Learning Experimental Testbeds: The Missing Piece. IEEE Internet of Things Magazine, 2024, Vol. 7, No. 1, pp. 136–143.

N. Quadar, H. Chaibi, et al. Recommendation Systems: Models, Techniques, Application Fields and Ethical Challenges. In Proceedings of the 7th International Conference on Big Data and Internet of Things (BDIoT ’24), 2024.