Minhazur Rahman | Computer Science | Best Researcher Award

Published on by Young Scientists Awards

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

Yerassyl Saparbekov | Machine Learning | Research Excellence Award

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Mr. Yerassyl Saparbekov | Machine Learning | Research Excellence Award

Nazarbayev University | Kazakhstan

Mr. Yerassyl Saparbekov is a researcher in computer science specializing in deep learning, natural language processing, and computer vision. His work focuses on embedding models, clustering techniques, and retrieval-augmented generation systems for evidence-based analysis. He has contributed to developing advanced AI solutions for student feedback interpretation and decision-support systems. His research also spans medical visual question answering, scene text super-resolution, and multimodal learning approaches. He is actively engaged in advancing applied artificial intelligence for real-world problem solving and intelligent data-driven insights.


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Featured Publications

Vikas Verma | Computer Science | Young Scientist Award

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Mr. Vikas Verma | Computer Science
| Young Scientist Award

The ICFAI University, Jaipur | India

Dr. Vikas Verma’s research contributions focus extensively on Software Defined Networking (SDN), Machine Learning, and Network Optimization, emphasizing energy efficiency, intelligent routing, and data-driven automation. His doctoral research, “Flow Classification and Energy Efficient Routing in Software Defined Networks Using Machine Learning Techniques,” explores the integration of adaptive algorithms for sustainable network management. His projects, including “Routing Optimization for Software-Defined Networking Using Machine Learning Techniques and Multi-Domain Controller” and “Industry-Academia Collaboration of SME with Academics,” demonstrate practical applications of AI in networking and innovation ecosystems. Dr. Verma’s publications in high-impact journals and conferences, such as the Philippine Journal of Science, Suranaree Journal of Science and Technology, IEEE Xplore, and Springer CCIS, address key advancements in SDN, IoT-based smart farming, and quantum communication security. His work “Energy-Efficient Techniques in SDN: Software, Hardware, and Hybrid Approaches” and “Comparative Analysis of Quantum Key Distribution Protocols” highlight optimization in computing systems and secure data transmission. Additionally, he holds two UK design patents—one for an AI-driven finance management device and another for a medical diagnostic system using saliva-based biomarkers. His current research extends to privacy preservation, intelligent traffic classification, and predictive analytics, establishing his expertise in sustainable and secure intelligent network systems.

Featured Publications

Verma, V., & Jain, M. (2024). Energy-efficient techniques in SDN: Software, hardware, and hybrid approaches. Philippine Journal of Science, 153(1).

Agarwal, N., & Verma, V. (2023). Comparative analysis of quantum key distribution protocols: Security, efficiency, and practicality. In Proceedings of the International Conference on Artificial Intelligence of Things (pp. 151–163).

Verma, V., Ramakant, Mathur, H., & Agarwal, N. (2022). IoT assisted smart farming using data science techniques. In 2022 IEEE World Conference on Applied Intelligence and Computing (AIC). IEEE.

Verma, V. (2017). Automatic mood classification of Indian popular music. International Journal for Research in Applied Science and Engineering.

Verma, V., & Jain, M. (2023). Optimization of routing using traffic classification in software defined networking. Suranaree Journal of Science and Technology, 30(1), 010198(1–8).*

Vaibhav Tummalapalli | Machine learning | Excellence in Innovation Award

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Mr. Vaibhav Tummalapalli l Machine learning
| Excellence in Innovation Award

Epsilon Data Management, LLC | United States

Mr. Vaibhav Tummalapalli’s research focuses on the advancement of applied machine learning methodologies, predictive modeling, and data-driven optimization across large-scale industrial domains, particularly automotive and telecommunications. His work emphasizes the integration of artificial intelligence in lifecycle analytics, customer engagement, and personalization strategies to enhance business intelligence and operational efficiency. His studies explore innovative modeling frameworks such as EV Conquest modeling, VIN-level mileage prediction, and vehicle recommendation systems, which apply behavioral, telematics, and demographic data to drive precision marketing and service optimization. Additionally, his contributions to outlier detection, cohort-based stratified sampling, and KNN imputation distance metrics extend theoretical and applied understanding in data preprocessing and imbalanced learning. His research also addresses model monitoring and drift management using SAS Viya and PySpark-based architectures, ensuring robust model performance in production environments. Through the development of scalable ML pipelines, channel propensity models, and retention-focused predictive systems, his work demonstrates the transformative potential of AI in driving measurable business outcomes, customer retention, and ethical personalization. His scholarly and technical pursuits collectively aim to advance the design of intelligent, explainable, and sustainable machine learning systems for real-world, high-impact applications

Featured Publications

Tummalapalli, V. (2025). Understanding distance metrics in KNN imputation: Theoretical insights and applications. Journal of Mathematical & Computer Applications, 4(4), 1–4. https://doi.org/10.47363/JMCA

Tummalapalli, V. (2025). Machine learning pipeline for automotive propensity models. International Journal of Core Engineering & Management, 8(3), [Issue-03].

Tummalapalli, V. (2025). Outlier detection & treatment for machine learning models. International Journal of Innovative Research and Creative Technology, 11(3).

Tummalapalli, V. (2025). Stratified sampling in cohort-based data for machine learning model development. International Scientific Journal of Engineering and Management, 4.

Sharmila More | Machine Learning | Women Researcher Award

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Dr. Sharmila More | Machine Learning | Women Researcher Award

MIT Arts, Commerce & Science College| India

Dr. Sharmila More is an accomplished academician and researcher, currently serving as Assistant Professor in the Department of Science and Computer Science at MIT ACSC, Alandi (D), Pune. With over nine years of teaching and administrative experience, along with eight years of dedicated research expertise, she has significantly contributed to the fields of computer science, data science, cyber security, and artificial intelligence. She holds a Ph.D. in Computer Science from MATS University, Raipur, an MCA from Pune University, and a Postgraduate Diploma in Core Competency from Shivaji University. Dr. More has published 18 research papers in reputed journals, presented 20 papers at national and international conferences, and authored a book titled Solving Security Issues in Personal Identification using Fuzzy Approach and Multimodal Images. She has also guided several students in research and academic projects. Her innovations are reflected in multiple patents, including an Indian patent at the FER stage, one design patent, and granted patents in Australia, Germany, and the UK. She is actively engaged in academic committees, curriculum development under the NEP framework, and serves as an editorial board member for journals. Her professional memberships include the Computer Society of India, Indian Science Congress Association, and Soft Computing Research Society. Recognized for her excellence, she has received prestigious honors such as the International Research Excellence Awards for Outstanding Researcher and Distinguished Researcher, Best Teacher Award, and multiple prizes at research competitions. A sought-after resource person and reviewer, she has delivered expert lectures and contributed as co-supervisor and examiner for Ph.D. programs. Her citation index stands at 67, reflecting her impactful scholarship. Dr. More continues to advance interdisciplinary research in computer science, focusing on biometric systems, machine learning, cryptography, and emerging technologies, while inspiring future scholars through teaching, mentorship, and innovation.

Profile: Google Scholar

Featured Publications

More, S. S. (2025). Revolutionizing military operations: The role of deep learning with YOLO v7 in the evolution of drones. Advancements in Intelligent Systems, 33–43. Computing & Intelligent Systems.

More, S. S. (2024). Pythonic learning: Advancements and innovations in machine intelligence. International Journal of Advanced Research in Science, Communication and Technology.

More, S. S. (2023). Statistical and fuzzy inference system analysis of multimodal. Solovyov Studies ISPU.

More, S. S. (2023). Statistical and fuzzy inference system analysis of multimodal images using NMRSA. Solovyov Studies ISPU, 71(11), 122–127.

More, S., Narain, B., & Jadhav, B. T. (2023). Privacy conserving using fuzzy approach and blowfish algorithm for malicious personal identification. In Institute of Engineering (pp. xx–xx). Springer.

 

PRAVEENA VASUDEVAN | Machine Learning |Best Researcher Award

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Mrs. PRAVEENA VASUDEVAN | Machine Learning | Best Researcher Award

Mrs  at SRM INSTITUTE OF SCIENCE & TECHNOLOGY, RAMAPURAM CAMPUS, CHENNAI India

V. Praveena is a dedicated Assistant Professor with over 14 years of teaching experience in VLSI Design, Electronics, and Computer Science. She holds an M.Tech in VLSI Design from BIHER, Chennai, and has consistently achieved outstanding academic results, including a 100% pass rate in various subjects. She has a strong background in mentoring students, organizing workshops, and coordinating placements, contributing to a 100% placement record in her department. With a passion for research, she has published papers in SCOPUS-indexed journals and guided innovative student projects, demonstrating her commitment to excellence in education and academic development.

Profile

Orcid

 

Objective:

Dedicated and ambitious professional seeking to leverage skills in electronics and VLSI design in a challenging academic or corporate environment.

Academic Background:

M.Tech in VLSI Design Barath Institute of Higher Education and Research (BIHER), Chennai (2006) CGPA: 7.7. B.E. in Electronics & Instrumentation Engineering Madras University, Easwari Engineering College, Chennai (2002) Percentage: 70%

Professional Experience:

Assistant Professor (Selection Grade), SRM University, Ramapuram Campus June 2010 – December 2017 | June 2019 – Present Over 9 years of teaching experience, mentoring, and coordinating academic activities.. Senior Lecturer, Sri Muthukumaran Institute of Technology
July 2006 – April 2010. Lecturer, Sree Sastha Institute of Technology & Easwari Engineering College Various positions held in 2006, gaining early teaching experience. New Product Design & Development Engineer, M/S Ram Says Corporation 1.5 years of industrial experience in product design and development.

Achievements:

Achieved 100% pass rates in several subjects, organized workshops, and received accolades for student project guidance. Published several papers in Scopus-indexed journals and presented at national and international conferences. Successfully coordinated placement activities, achieving a consistent 100% placement record in the CSE department.

Skills:

Programming Languages: C, C++ Programming, HDL, Software Proficiency: Xilinx, SPICE, MS Office

Research Interests:

VLSI Design, Context-aware applications, Secure data sharing, Cloud storage, and Emergency vehicle management systems.

🏆 Strengths for the Award:

Extensive Teaching and Research Experience: With over 14 years of teaching experience and a strong background in VLSI Design, V. Praveena has demonstrated a deep commitment to academic excellence. Her role as an Assistant Professor at SRM University showcases her ability to guide and mentor students effectively. High Success Rate in Teaching: Achieving 100% pass rates in multiple courses across different departments highlights her teaching effectiveness and dedication to student success. Published Research and Conference Participation: Praveena has published several papers in Scopus-indexed journals and presented at international conferences. Her research contributions in the areas of secure computing, cloud storage, and mobile-healthcare emergencies indicate a strong focus on impactful and relevant topics. Leadership and Initiative: She has taken on additional responsibilities, such as being an academic auditor, admission coordinator, and member of the Women’s Grievance Cell. These roles demonstrate her leadership capabilities and commitment to improving the academic environment. Project Guidance and Innovation: Guiding students to develop award-winning projects, including an innovative Android application for student assistance, reflects her ability to inspire and lead innovative research. Industry Collaboration: Her efforts in guiding projects with industry partners, such as M/S. SOLVEDGE, show her ability to bridge the gap between academia and industry, which is crucial for impactful research.

🔧 Areas for Improvement:

Expansion of Research Focus: While her research has been impactful, there could be an opportunity to diversify into more interdisciplinary areas or emerging fields to broaden her research portfolio. Increased Publication in High-Impact Journals: Although she has several publications, aiming for more papers in high-impact journals could further solidify her reputation as a leading researcher. Grant Acquisition: There is no mention of successful grant applications. Securing research funding is essential for sustaining long-term research projects, and focusing on this could enhance her research impact. Public Engagement and Outreach: Increasing her engagement with the broader community, such as through public lectures, workshops, or media appearances, could help disseminate her research findings to a wider audience. International Collaboration: While she has participated in international conferences, forming collaborations with international researchers or institutions could provide new perspectives and enhance the quality and visibility of her work.

 

📚  Publications

  1. Title: Context Aware App Recommendation and Delivery using Decision Support Systems
    • Journal: Indian Journal of Science and Technology
    • Date: June 1, 2016
    • Type: Journal article

 

  1. Title: A Novel And Effective Auditing Approach To Store And Retrieve Reliable Data In Cloud Storage
    • Journal: International Journal of Emerging Technology in Computer Science & Electronics
    • Date: April 2016
    • Type: Journal article

 

  1. Title: Proficient data sharing using Forward Secure ID-based Ring Signature and handling access control using ABE
    • Journal: International Journal of Emerging Technology in Computer Science & Electronics
    • Date: April 1, 2016
    • Type: Journal article

 

  1. Title: Location-Aware and Safer Cards: Enhancing Kerberos Authentication Along With Attribute Based Encryption
    • Journal: International Journal of Applied Engineering Research
    • Date: 2015
    • Type: Journal article

 

  1. Title: EFFICIENT ACCIDENT DETECTION AND RESCUE SYSTEM USING ABEONA ALGORITHM
    • Journal: International Journal of Emerging Trends & Technology in Computer Science
    • Date: October 2014
    • Type: Journal article

 

  1. Title: A SECURE AND CONFIDENTIALITY STRATEGIC COMPUTING ORGANIZATION FOR MOBILE-HEALTHCARE EMERGENCY
    • Journal: International Journal of Computer Science and Mobile Computing
    • Date: March 2014
    • Type: Journal article

 

  1. Title: Framework for Ease Maneuver of on Road Emergency Vehicles: Using Mobile Sink
    • Journal: International Journal of Innovative Research in Computer and Communication Engineering
    • Date: March 2014
    • Type: Journal article

📝 Conclusion:

V. Praveena is a strong candidate for the Best Researcher Award due to her extensive teaching experience, successful student mentorship, leadership in academic roles, and notable research contributions. Her ability to guide students towards innovative projects and her involvement in various academic responsibilities highlight her as a well-rounded academic professional.

However, to further strengthen her candidacy, focusing on expanding her research into interdisciplinary areas, increasing her publication output in high-impact journals, and securing research grants could enhance her research profile even more. Overall, her dedication to academic excellence and her contributions to both teaching and research make her a deserving candidate for the award.