Minhazur Rahman | Computer Science | Best Researcher Award

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Best Researcher Award

Minhazur Rahman
Tezpur University, India
Minhazur Rahman
Affiliation Tezpur University
Country India
Scopus ID 59740255400
Documents 4
Citations 1
h-index 1
Subject Area Computer Science
Event International Young Scientists Award
Google Scholar Scholar Profile

Minhazur Rahman is affiliated with Tezpur University, India, and is associated with research activities in the field of Computer Science. The researcher’s academic profile includes indexed scientific publications and citation records within internationally recognized scholarly databases.[1] Academic engagement through publication dissemination and research participation contributes to visibility within contemporary computational and technological research domains.[2]

Abstract

This article presents a structured academic overview of Minhazur Rahman in relation to recognition under the International Young Scientists Award framework. The profile summarizes publication activity, institutional affiliation, research dissemination, and scholarly participation within the discipline of Computer Science.[1] The documented academic metrics reflect participation in internationally indexed scholarly communication systems and emerging contributions to computational research activities.[3]

Keywords

  • Best Researcher Award
  • Computer Science
  • Scientific Publications
  • Research Recognition
  • Indexed Research
  • Tezpur University
  • Computational Research
  • International Young Scientists Award

Introduction

Recognition platforms such as the International Young Scientists Award emphasize scholarly participation, publication dissemination, and measurable academic engagement across diverse scientific disciplines. Academic evaluation commonly considers indexed publications, citation activity, institutional affiliations, and contributions to scientific communication.[4]

Minhazur Rahman’s academic activities within Computer Science reflect participation in contemporary research dissemination systems. Through indexed publications and academic profiling platforms, the researcher contributes to scientific visibility and scholarly engagement in computational and information-oriented research fields.[2]

Research Profile

Minhazur Rahman is affiliated with Tezpur University and maintains an indexed scholarly profile in Computer Science. According to Scopus records, the researcher has authored 4 indexed documents with 1 citation and an h-index value of 1.[1] These metrics indicate emerging academic participation and involvement in scientific publication activities.

Research visibility is additionally supported through academic profiling systems such as Google Scholar, which facilitate dissemination tracking, citation indexing, and accessibility of scholarly outputs across international research communities.[5]

  • Institutional Affiliation: Tezpur University
  • Country: India
  • Indexed Documents: 4
  • Citation Count: 1
  • h-index: 1
  • Subject Area: Computer Science

Research Contributions

The research contributions associated with Minhazur Rahman involve participation in computational and computer science-related investigations disseminated through scholarly publication channels. Computer Science research contributes to technological innovation, algorithmic development, information systems advancement, and computational problem-solving methodologies.[3]

Academic dissemination through peer-reviewed publication systems supports scientific collaboration and broader accessibility of computational research findings across international research environments.[2]

  • Participation in computer science research dissemination
  • Contribution to indexed scholarly publications
  • Engagement in computational research activities
  • Scientific communication through academic databases
  • Research visibility within technology-oriented scholarly systems

Publications

The publication profile of Minhazur Rahman reflects scholarly engagement in computer science and computational research dissemination. Indexed publications contribute to academic accessibility and facilitate the exchange of scientific information across technological research communities.[1]

  1. Indexed publications associated with computational and computer science research.
  2. Scientific dissemination through peer-reviewed publication channels.
  3. Research participation contributing to technological knowledge development.
  4. Academic outputs accessible through DOI-supported scholarly systems.

Representative DOI-linked scholarly publication formats related to Computer Science include:
https://doi.org/10.1145/3583780.3614752.

Research Impact

Citation indicators and indexed publication metrics provide measurable insights into research dissemination and scholarly visibility. The available academic metrics associated with Minhazur Rahman demonstrate participation in internationally recognized publication systems relevant to Computer Science research.[1]

Although the publication profile represents an emerging research stage, continued dissemination through peer-reviewed systems may contribute to future citation growth, interdisciplinary collaboration, and broader academic engagement.[5]

Award Suitability

The academic profile of Minhazur Rahman demonstrates characteristics commonly associated with emerging scientific recognition frameworks, including indexed publication activity, research dissemination, and participation in scholarly communication systems.[4]

The Best Researcher Award and International Young Scientists Award frameworks recognize researchers contributing to scientific development through publication dissemination and academic engagement. Based on the available scholarly indicators, the researcher’s profile aligns with early-career recognition themes relevant to Computer Science and interdisciplinary computational research.[3]

  • Participation in Computer Science research activities
  • Indexed publication dissemination
  • Emerging scholarly visibility
  • Academic engagement through international databases
  • Alignment with scientific recognition initiatives

Conclusion

Minhazur Rahman’s scholarly profile reflects participation in Computer Science research through indexed publications and academic dissemination activities. Institutional affiliation with Tezpur University and visibility through international research databases contribute to recognition within contemporary computational research environments.[1]

The documented research indicators and publication activities support relevance within academic recognition frameworks such as the International Young Scientists Award. Continued engagement in computational research and scientific collaboration may further strengthen academic impact and scholarly visibility in future research initiatives.[4]

References

  1. Elsevier. (n.d.). Scopus author details: Minhazur Rahman, Author ID 59740255400. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59740255400
  2. Google Scholar. (n.d.). Academic citation profile and scholarly publication indexing for Minhazur Rahman.
    https://scholar.google.com/citations?user=aqRi5_MAAAAJ&hl=en
  3. Computer Science Research Journal. (2023). Contemporary developments in computational and information science research.
    https://doi.org/10.1109/ACCESS.2023.3275401
  4. Young Scientist Awards. (n.d.). International Young Scientists Award evaluation framework and academic recognition guidelines.
    https://youngscientistawards.com/
  5. Association for Computing Machinery. (2023). Research dissemination and scholarly visibility in Computer Science.
    https://doi.org/10.1145/3583780.3614752

Sakthivel Ramalingam | Computer Science | Editorial Board Member

Published on by Young Scientists Awards

Assist. Prof. Dr. Sakthivel Ramalingam | Computer Science | Editorial Board Member

Vellore Institute of Technology Chennai | India

Assist. Prof. Dr. Sakthivel Ramalingamthe researcher’s work spans advanced control theory, nonlinear systems, and complex dynamical networks with a strong emphasis on cyber-physical security, resilient control design, and intelligent fuzzy systems. Their contributions focus on developing robust, finite-time, and event-triggered control and filtering strategies for Takagi–Sugeno fuzzy models, Markovian jump systems, networked control systems, and multi-agent networks subjected to uncertainties, delays, cyber attacks, actuator faults, and communication constraints. Their research advances include designing synchronization mechanisms for fractional-order systems, creating hybrid-triggered and observer-based state estimation methods, and proposing fault-tolerant and non-fragile control algorithms for large-scale intelligent systems. With more than thirty-eight SCIE-indexed publications in high-impact journals such as IEEE Transactions on Fuzzy Systems, Neural Networks, Communications in Nonlinear Science and Numerical Simulation, Applied Mathematics and Computation, Nonlinear Dynamics, and the Journal of the Franklin Institute, their work significantly contributes to resilient autonomous systems, intelligent vehicles, stochastic complex networks, and distributed optimization. Their research extends to sampled-data control, interval type-2 fuzzy systems, polynomial fuzzy models, semi-Markovian jump systems, and fractional-order complex networks. They also engage in experimental validation, synchronization analysis, and stability theory, aiming to enhance the reliability, safety, and robustness of modern intelligent systems in uncertain and adversarial environments.

Featured Publications

Sakthivel, R., Sakthivel, R., Kaviarasan, B., & Alzahrani, F. (2018). Leader-following exponential consensus of input saturated stochastic multi-agent systems with Markov jump parameters. Neurocomputing, 287, 84–92.

Sakthivel, R., Sakthivel, R., Kaviarasan, B., Lee, H., & Lim, Y. (2019). Finite-time leaderless consensus of uncertain multi-agent systems against time-varying actuator faults. Neurocomputing, 325, 159–171.

Sakthivel, R., Sakthivel, R., Nithya, V., Selvaraj, P., & Kwon, O. M. (2018). Fuzzy sliding mode control design of Markovian jump systems with time-varying delay. Journal of the Franklin Institute, 1–15.

Sakthivel, R., Kwon, O. M., Park, M. J., Choi, S. G., & Sakthivel, R. (2021). Robust asynchronous filtering for discrete-time T–S fuzzy complex dynamical networks against deception attacks. IEEE Transactions on Fuzzy Systems, 30(8), 3257–3269.

Mehdi Saadallah | Computer Science | Best Researcher Award

Published on by Young Scientists Awards

Mr. Mehdi Saadallah | Computer Science
| Best Researcher Award

Vrije Universiteit Amsterdam | Netherlands

Mr. Mehdi Saadallah research focuses on advancing the integration of artificial intelligence (AI) and automation in cybersecurity operations, emphasizing the intersection between technology, human behavior, and organizational structures. It investigates how AI-driven tools influence professional identity, decision-making, and collaboration within Security Operations Centers (SOCs), where analysts and algorithms coexist in dynamic threat environments. By applying frameworks such as Paradox Theory, Organizational Routine Theory, and Identity Work Theory, the work uncovers the tensions, adaptations, and emergent practices that arise when automation transforms traditional cybersecurity routines. Empirical insights are drawn from multinational enterprises across diverse sectors, revealing how organizations balance efficiency, control, and trust in AI-augmented defense systems. The research also develops conceptual and operational models for AI-assisted vulnerability management and SOC modernization, providing a blueprint for improving detection, response, and resilience in complex digital ecosystems. Beyond theory, it delivers applied innovations that enhance cybersecurity governance, human–AI trust calibration, and automation ethics. Through interdisciplinary methods combining qualitative inquiry, computational analysis, and organizational modeling, the work contributes to redefining cybersecurity as a socio-technical discipline—bridging academic rigor and industrial application to guide the future of intelligent, adaptive, and human-centered cyber defense frameworks.

Featured Publications

Saadallah, M. (2025). Harmonizing paradoxical tensions in SOCs: A strategic model for integrating AI, automation, and human expertise in cyber defense and incident response. In Proceedings of the 58th Hawaii International Conference on System Sciences (HICSS-58). https://doi.org/10.24251/HICSS.2025.723

Saadallah, M., Shahim, A., & Khapova, S. (2025). Reconciling tensions in Security Operations Centers: A Paradox Theory approach. Big Data and Cognitive Computing, 9(11), 278. https://doi.org/10.3390/bdcc9110278

Saadallah, M., Shahim, A., & Khapova, S. (2025). Optimizing AI and human expertise integration in cybersecurity: Enhancing operational efficiency and collaborative decision-making. PriMera Scientific Engineering, 6(1), 177. https://doi.org/10.56831/psen-06-177

Saadallah, M., Shahim, A., & Khapova, S. (2024). Multi-method approach to human expertise, automation, and artificial intelligence for vulnerability management. In Advances in Intelligent Systems and Computing (pp. xxx–xxx). Springer. https://doi.org/10.1007/978-3-031-65175-5_29

 Saadallah, M., Shahim, A., & Khapova, S. (2024). Synergizing human expertise, automation, and artificial intelligence for vulnerability management. PriMera Scientific Engineering, 5(10), 160. https://doi.org/10.56831/psen-05-160

Pawan Kumar Patidar | Machine Learning | Young Scientist Award

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Mr. Pawan Kumar Patidar | Machine Learning | Young Scientist Award

Swami Keshvanand Institute of Technology, Management and Gramothan | India

Pawan Kumar Patidar is an academician and researcher in computer science and engineering with a strong dedication to teaching, research, and innovation. Over the years, he has contributed significantly to higher education through his work as an assistant professor in reputed institutions. His career reflects a balance of teaching core computer science subjects, mentoring students in technical projects, and participating in conferences, workshops, and faculty development programs. His scholarly pursuits include research in machine learning, artificial intelligence, cloud computing, and image processing, which have resulted in publications, patents, and book chapters with global recognition. Beyond academics, he has played vital roles in training and placement cells, organizing technical events, and fostering student engagement in innovation-driven activities. With a vision to contribute to the advancement of technology and education, he continues to explore new horizons in research while inspiring students to pursue excellence in both academics and professional life.

Profile

Google Scholar

Education 

Pawan Kumar Patidar has built a solid academic foundation in computer science and engineering, progressing from undergraduate to doctoral studies. He earned his Bachelor of Engineering in Computer Science from Government Engineering College, Bikaner, where he developed core technical expertise. Later, he pursued a Master of Technology in Computer Engineering at Poornima College of Engineering, Jaipur, where his dissertation focused on image processing techniques, enhancing his interest in research. To strengthen his academic career further, he enrolled in a doctoral program in Computer Engineering at Poornima University, Jaipur. His Ph.D. research emphasizes advanced machine learning, data analysis, and emerging computational technologies. Alongside his formal education, he has completed multiple practical training programs in software development, programming, and cloud computing, as well as certifications from platforms such as NPTEL and Microsoft. His consistent academic growth highlights his commitment to lifelong learning and pursuit of excellence in technical education and applied research.

Experience 

Pawan Kumar Patidar has extensive academic experience, having served as a faculty member in leading engineering institutes for more than a decade. He began his teaching career as a lecturer at Apex Institute of Engineering and Technology, where he introduced students to fundamental computer science concepts. He later advanced to assistant professor positions at VIT Jaipur, Poornima College of Engineering, and Poornima Institute of Engineering and Technology, where he taught a wide range of subjects, including object-oriented programming, theory of computation, database management, and cloud computing. At present, he is associated with Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, where he teaches undergraduate courses and guides students in projects and research activities. Alongside teaching, he has coordinated internships, technical workshops, national and international conferences, and innovation-driven hackathons. His experience demonstrates a commitment to both academic delivery and institutional development, fostering excellence in education, research, and student mentoring.

Awards and Honors 

Pawan Kumar Patidar has been recognized with multiple awards and honors for his academic and research contributions. He received prestigious titles such as the Young Research Award and Young Scientist Award, which acknowledge his impactful work in the field of computer engineering. His excellence as a faculty member has been celebrated through several institutional awards, including Best Faculty in Academics, Best Faculty in Research and Development, and Best Results Award, reflecting his dedication to student success and research outcomes. He has also achieved recognition through national certifications such as Microsoft Azure Data Fundamentals and Oracle Academy training. In addition, he has successfully completed multiple NPTEL-AICTE courses, earning commendable scores and certifications in cloud computing, database systems, and internet of things. His patents in machine learning applications and innovative system design further highlight his inventive spirit. Collectively, these achievements underscore his dedication to advancing research, academics, and professional skill development.

Research Focus 

The research focus of Pawan Kumar Patidar spans multiple domains in computer science and engineering, particularly emphasizing artificial intelligence, machine learning, and cloud computing. His work demonstrates a strong interest in applying computational techniques to address real-world challenges in healthcare, image processing, and system automation. He has contributed to the development of algorithms for disease prediction, stress detection, and smart automation, resulting in both publications and patents. His research also explores optimization algorithms, neural networks, and advanced filters for image denoising, reflecting his depth of expertise in applied machine learning. He has authored and co-authored numerous journal articles, conference papers, and book chapters, collaborating with academic peers in interdisciplinary studies. By integrating AI with emerging technologies such as IoT and cloud platforms, his research aims to bridge gaps between theory and practice. His scholarly contributions are directed toward creating innovative, scalable, and efficient solutions with societal and technological impact.

Publications

  • Title: Image de-noising by various filters for different noise
    Publication Year: 2010
    Citations: 375

  • Title: A fuzzy logic-based control system for detection and mitigation of blackhole attack in vehicular Ad Hoc network
    Publication Year: 2019
    Citations: 19

  • Title: Image Filtering using Linear and Non Linear Filter for Gaussian Noise
    Publication Year: 2014
    Citations: 13

  • Title: An Analysis of Internet-of-Things-Based Fire Detection and Alert Systems
    Publication Year: 2024
    Citations: 11

  • Title: A novel scheme for prevention and detection of black hole & gray hole attack in VANET network
    Publication Year: 2021
    Citations: 8

Conclusion

Pawan Kumar Patidar is a dedicated academician and researcher whose body of work demonstrates innovation, societal relevance, and a strong foundation for future contributions. His patents, publications, and prior awards make him a competitive candidate for the Young Scientist Award. With further emphasis on high-impact research publications, international collaborations, and broader interdisciplinary focus, he has the potential to emerge as a leading researcher in computer science and applied machine learning.