Mojtaba Rafiee | Cryptography | Innovative Research Award

Published on by Global CSE Awards

Innovative Research Award

Mojtaba Rafiee
University of Isfahan, Iran

Mojtaba Rafiee
Affiliation University of Isfahan
Country Iran
Scopus ID 56689591300
Documents 5
Citations 53
h-index 4
Subject Area Cryptography
Event Global CSE Awards
ORCID 0000-0001-9365-1803

Mojtaba Rafiee is a researcher affiliated with the University of Isfahan whose scholarly work focuses on cryptography, privacy-preserving systems, and secure cloud computation. His research contributions emphasize functional encryption, encrypted set operations, and adaptive security models applicable to modern distributed systems and secure communication infrastructures.[1] His published studies demonstrate ongoing engagement with advanced cybersecurity challenges involving encrypted cloud datasets and secure multi-client cryptographic protocols.[2]

Abstract

Mojtaba Rafiee has contributed to research in cryptography and secure cloud computing through studies centered on functional encryption, private set operations, and adaptive security frameworks. His work addresses challenges related to data privacy, encrypted cloud datasets, and secure information sharing across distributed systems. By examining multi-adjustable join schemes and multi-client encryption models, his publications support the advancement of efficient privacy-preserving computation methodologies applicable to modern cybersecurity environments.[1][2] The scholarly impact of these studies reflects continued interest in practical cryptographic applications designed for scalable and secure computational infrastructures.[3]

Keywords

Cryptography, Functional Encryption, Secure Cloud Computing, Data Privacy, Encrypted Datasets, Multi-Client Encryption, Adaptive Security, Private Set Operations, Cybersecurity, Secure Computation.

Introduction

The increasing demand for secure digital communication has expanded research interest in cryptographic systems capable of preserving privacy within distributed computing environments. Mojtaba Rafiee’s work contributes to this field through studies focused on functional encryption and privacy-preserving cloud operations designed for modern computational infrastructures.[1]

Research Profile

Mojtaba Rafiee is affiliated with the University of Isfahan and specializes in cryptography and secure computation research. His publications investigate adaptive security mechanisms, encrypted cloud data processing, and functional encryption frameworks that support secure information exchange across distributed digital platforms.[2]

Research Contributions

His research contributions include the development of multi-adjustable join schemes and secure set intersection mechanisms applicable to encrypted cloud environments. These studies address data confidentiality challenges while maintaining computational efficiency and adaptable security structures for multi-client cryptographic applications.[1][4]

Publications

The publication record of Mojtaba Rafiee includes articles published in recognized journals such as IEEE Transactions on Dependable and Secure Computing, The Journal of Supercomputing, and The Computer Journal. These studies collectively examine encryption methodologies, secure cloud datasets, and adaptive privacy-preserving systems.[1][2]

  • Multi-Adjustable Join Schemes with Adaptive Indistinguishably Security
  • Flexible Multi-Client Functional Encryption for Set Intersection
  • Security of Multi-Adjustable Join Schemes: Separations and Implications
  • Private Set Operations over Encrypted Cloud Dataset and Applications

Research Impact

The documented citation record and publication activity indicate scholarly engagement within the field of cryptography. His studies contribute to advancing privacy-preserving computational methods and support ongoing academic discussion regarding secure cloud infrastructures and encrypted communication technologies.[3]

Award Suitability

Mojtaba Rafiee’s research profile aligns with the objectives of the Global CSE Awards due to his contributions to cryptography and secure computing methodologies. His publications address contemporary cybersecurity challenges while presenting practical frameworks for secure data sharing and encrypted cloud computation.[1]

Conclusion

The academic contributions of Mojtaba Rafiee reflect continued research activity in cryptography and secure cloud technologies. His studies provide relevant insights into adaptive encryption systems and privacy-preserving computation, supporting the broader advancement of dependable and secure digital communication infrastructures.[2]

References

  1. Rafiee, M. (2023). Multi-Adjustable Join Schemes with Adaptive Indistinguishably Security. IEEE Transactions on Dependable and Secure Computing.
    https://ieeexplore.ieee.org/document/10363626
  2. Rafiee, M. (2023). Flexible multi-client functional encryption for set intersection. The Journal of Supercomputing.
    https://link.springer.com/article/10.1007/s11227-023-05129-y
  3. Rafiee, M., & Khazaei, S. (2021). Security of Multi-Adjustable Join Schemes: Separations and Implications. IEEE Transactions on Dependable and Secure Computing.
    https://ieeexplore.ieee.org/document/9366363
  4. Rafiee, M., & Khazaei, S. (2020). Private Set Operations over Encrypted Cloud Dataset and Applications.
    https://ieeexplore.ieee.org/document/9579286
  5. Elsevier. (n.d.). Scopus author details: Mojtaba Rafiee, Author ID 56689591300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=56689591300

Ramchandra Mangrulkar | Cryptography | Best Researcher Award

Published on by Global CSE Awards

Dr. Ramchandra Mangrulkar | Cryptography | Best Researcher Award

Professor at SVKM’s Dwarkadas J. Sanghvi College of Engineering | India

Dr. Ramchandra Sharad Mangrulkar is a prolific researcher and academic leader whose contributions bridge advanced artificial intelligence research with practical, industry-ready solutions. leading international publishers, his scholarly output reflects both depth and breadth. He holds patents in deep learning-based applications and has provided consultancy in blockchain, high-performance computing, fraud detection, and cybersecurity, showcasing his commitment to solving real-world problems. As an IEEE Senior Member and editorial board member of reputed journals, Dr. Mangrulkar actively contributes to the global research community while mentoring doctoral scholars and fostering interdisciplinary collaborations. His research spans GPU-accelerated computing, secure AI, ethical applications of technology, and blockchain-based systems, all at the forefront of computer science. Through his innovative work, leadership, and dedication, Dr. Mangrulkar continues to advance secure, scalable, and ethical computing systems, making him an ideal candidate for prestigious recognition.

Professional Profiles

  Google scholar | Scopus | ORCID

Education

Dr. Ramchandra Sharad Mangrulkar has pursued an extensive academic journey that has provided him with a strong foundation in computer science and engineering. He completed his postgraduate degree from the prestigious National Institute of Technology, Rourkela, where he gained expertise in advanced computing methodologies and problem-solving strategies. His academic pursuit continued with a doctorate in Computer Science and Engineering from Sant Gadge Baba Amravati University, where his research was focused on innovative computational models and data-driven techniques. This combination of advanced qualifications has helped him specialize in areas such as predictive analytics, GPU-accelerated computing, and cybersecurity. His educational achievements reflect not only academic excellence but also a deep commitment to research-driven learning, providing him with the intellectual capacity to mentor future researchers. Through his education, Dr. Mangrulkar has developed a solid framework of technical and theoretical knowledge that has continuously guided his teaching, research, and consulting contributions.

Experience

Dr. Mangrulkar serves as a Professor in the Department of Information Technology at SVKM’s Dwarkadas J. Sanghvi College of Engineering, Mumbai, where he plays a pivotal role in teaching, mentoring, and guiding students in advanced domains of computing. With extensive academic and professional experience, he has contributed significantly to the growth of computer science research through his publications, consultancy, and supervisory roles. He has authored and co-authored numerous books with globally recognized publishers and has published more than a hundred research papers across reputed journals and conferences. His expertise extends into consultancy, where he has guided industries in adopting advanced frameworks for blockchain, data analytics, and high-performance computing. As an IEEE Senior Member and approved Ph.D. supervisor, he has mentored several doctoral scholars and graduate students. His leadership in academics, coupled with his strong research background, establishes him as a distinguished figure in the computer science engineering community.

Skills 

Dr. Mangrulkar possesses an extensive range of technical skills and domain expertise that span predictive analytics, artificial intelligence, cybersecurity, blockchain technology, and GPU-accelerated computing. His proficiency in developing high-performance computing solutions has made him a trusted consultant for organizations seeking innovation in research and industrial domains. He is highly skilled in ethical AI development, advanced cryptanalysis, data visualization, and network security frameworks. His capabilities include designing and implementing solutions for fraud detection, autonomous systems, and medical diagnostics, providing practical and impactful applications of his research. He has conducted cybersecurity audits, offered risk mitigation strategies, and guided enterprises in enhancing their IT infrastructure. His expertise extends to industry collaborations, where he has helped organizations implement blockchain frameworks, data-driven decision-making tools, and cloud-based GPU solutions. These multifaceted skills reflect his ability to bridge academic research with industrial innovation, demonstrating leadership in both technological development and applied problem-solving.

Research Focus

Dr. Mangrulkar’s research work demonstrates a strong focus on GPU-accelerated computing, blockchain frameworks, ethical artificial intelligence, and advanced cybersecurity solutions. He has completed diverse projects on predictive healthcare models, electronic health record security, and intelligent decision systems for medical diagnostics, all of which have had significant societal relevance. His ongoing research includes high-performance vector search applications, cryptanalysis attacks using deep neural networks, and customized generative adversarial networks for image synthesis. His scholarly contributions are evident from his wide publication record, multiple book authorships, and ongoing guidance of research scholars. His work reflects a balance between theoretical exploration and applied innovation, with clear emphasis on responsible computing practices. He actively collaborates with students and researchers, fostering an environment of knowledge exchange and innovation. His research continues to evolve with global technological trends, maintaining a strong impact within academic circles and extending into industry-driven problem-solving applications.

Awards 

Dr. Mangrulkar has been recognized across academia and industry for his outstanding contributions to computer science and engineering. He has authored and edited books with renowned publishers, published high-impact research, and contributed as a reviewer to international journals. His achievements include collaborative patents, such as an innovation on deep learning-based language translation, demonstrating his ability to transform research into applied technological solutions. He holds the distinction of being a Senior Member of IEEE, which reflects his global standing in the professional community. He has received appreciation for his consultancy work in cybersecurity, blockchain adoption, and high-performance computing solutions for enterprises. His leadership roles in academia, coupled with his guidance to research scholars and students, underline his contribution to nurturing future innovators. Recognition through citations, industry projects, and academic visibility highlights his influence, making him a highly respected professional dedicated to advancing computer science research and practice.

Publication Top Notes

Title: Design and implementation of smart HealthCare system using IoT
Journal/Conference: International Conference on Innovations in Information, Embedded and Systems
Citations: 106

Title: Intrusion detection system using random forest on the NSL-KDD dataset
Journal/Conference: Emerging Research in Computing, Information, Communication and Applications
Citations: 96

Title: Routing protocol for delay tolerant network: A survey and comparison
Journal/Conference: International Conference on Communication Control and Computing Technologies
Citations: 84

Title: Few shot learning for medical imaging
Journal/Conference: Machine Learning Algorithms for Industrial Applications (Book Chapter)
Citations: 58

Title: Comparison of tabular synthetic data generation techniques using propensity and cluster log metric
Journal/Conference: International Journal of Information Management Data Insights, 3 (2), 100177
Citations: 45

Title: TaxoDaCML: Taxonomy based Divide and Conquer using machine learning approach for DDoS attack classification
Journal/Conference: International Journal of Information Management Data Insights, 1 (2), 100048
Citations: 43

Title: Trust based secured adhoc On demand Distance Vector Routing protocol for mobile adhoc network
Journal/Conference: Sixth International Conference on Wireless Communication and Sensor Networks
Citations: 36

Title: Cyber security and digital forensics: challenges and future trends
Journal/Conference: John Wiley & Sons (Book Publication)
Citations: 23

Title: Improving Route Selection Mechanism using Trust Factor in AODV Routing Protocol for MaNeT
Journal/Conference: International Journal of Computer Applications, 7 (10), 36–39
Citations: 22

Title: Future Trends in 5G and 6G: Challenges, Architecture, and Applications
Journal/Conference: CRC Press (Book Publication)
Citations: 19

Conclusion

Dr. Ramchandra Sharad Mangrulkar is a distinguished researcher and academic leader whose career reflects a rare combination of scholarly excellence, technological innovation, and industry collaboration.  his contributions have significantly advanced the fields of artificial intelligence, high-performance computing, blockchain technologies, and cybersecurity. He has also demonstrated innovation through patents and consultancy projects that apply advanced research to real-world challenges. As an IEEE Senior Member, editorial board member, and mentor to doctoral scholars, Dr. Mangrulkar has shown strong leadership in shaping the global research community. His work bridges theoretical research with practical applications, ensuring secure, scalable, and ethical computing systems. Based on his research productivity, technological innovations, leadership roles, and industry collaborations, Dr. Mangrulkar is an ideal candidate for the Best Researcher Award in Computer Science & Engineering, with contributions of both academic significance and practical impact.