Dipesh | Applied Mathematics | Research Excellence Award

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Research Excellence Award

Dipesh

SR University, India

Dipesh
Affiliation SR University
Country India
Scopus ID 57564071300
Documents 36
Citations 147
h-index 8
Subject Area Applied Mathematics
Event Global Network Awards
ORCID 0000-0003-4883-9369

Dipesh of SR University. The assessment presented here is based on bibliometric indicators, publication activity, and documented research engagement within the field of Applied Mathematics.[1]

Abstract

This article documents the academic profile of Dipesh from SR University in relation to the Research Excellence Award presented within the framework of the Global Network Awards. Available bibliometric indicators indicate sustained research activity in Applied Mathematics, supported by indexed publications, citation performance, and scholarly visibility. The profile demonstrates engagement with mathematical methodologies and interdisciplinary research applications that contribute to the advancement of knowledge and academic discourse.[1][2]

Keywords

Research Excellence Award, Applied Mathematics, Academic Recognition, Scopus Author Profile, Citation Analysis, Research Impact, Scholarly Publications, Bibliometrics, Global Network Awards, Scientific Contributions.

Introduction

Academic awards serve as mechanisms for recognizing research quality, scholarly productivity, and influence within scientific communities. Evaluation frameworks frequently consider publication output, citation metrics, collaboration networks, and disciplinary relevance when assessing candidates. Within this context, the Research Excellence Award highlights achievements that demonstrate sustained contributions to research and knowledge dissemination.[3]

Research Profile

Dipesh is affiliated with SR University and is associated with research activities in Applied Mathematics. Bibliographic records indicate a portfolio of 36 indexed documents supported by 147 citations and an h-index of 8. These indicators suggest active participation in scholarly communication and a measurable level of influence within the research community.[1]

  • Primary discipline: Applied Mathematics.
  • Institutional affiliation: SR University.
  • Indexed research documents: 36.
  • Total citations: 147.
  • Reported h-index: 8.

Research Contributions

Research contributions in Applied Mathematics commonly involve analytical modeling, optimization methods, computational techniques, numerical analysis, and interdisciplinary problem solving. The documented publication activity associated with this profile reflects participation in scholarly investigations that support theoretical understanding and practical applications across scientific domains.[2]

  • Development and application of mathematical methodologies.
  • Contribution to peer-reviewed scholarly literature.
  • Support for interdisciplinary research initiatives.
  • Advancement of quantitative and analytical approaches.

Publications

Publication output constitutes an important indicator of research productivity. Indexed works contribute to scholarly visibility and facilitate knowledge exchange across institutions and disciplines. The available record identifies 36 documents associated with the researcher profile, reflecting ongoing engagement with academic publishing and peer-review processes.[1]

  1. Peer-reviewed journal articles.
  2. Conference-related scholarly contributions.
  3. Collaborative research publications.
  4. Mathematics-oriented academic studies.

Research Impact

Research impact is often evaluated through citation activity, scholarly adoption, and influence on subsequent investigations. A citation count of 147 and an h-index of 8 indicate that published work has been referenced by other researchers and has contributed to continuing academic discussions. Such indicators provide quantitative evidence of visibility and engagement within the scientific literature.[1][3]

Award Suitability

Based on the available academic indicators, the profile demonstrates characteristics commonly considered during research award evaluations, including publication productivity, citation performance, and subject-specific contributions. Participation in scholarly dissemination activities and measurable bibliometric outcomes align with criteria frequently used to identify candidates for academic recognition programs.[3]

  • Documented publication record.
  • Established citation footprint.
  • Recognized activity within Applied Mathematics.
  • Alignment with academic excellence indicators.

Conclusion

The academic profile presented in this article reflects a record of scholarly productivity and research engagement within Applied Mathematics. Publication output, citation performance, and institutional affiliation collectively support recognition through academic award initiatives such as the Research Excellence Award. Continued research activity and scholarly dissemination remain important factors in sustaining long-term academic impact and professional recognition.[1][2]

References

  1. Scopus author details: Dipesh, Author ID 57564071300. Scopus. https://www.scopus.com/authid/detail.uri?authorId=57564071300
  2. Fractal-AIMAS synergy for multiscale consciousness modeling in neuro-cybernetic systems: A multifractal, Kuramoto oscillator, and hybrid neuroprosthetic approach.
    https://www.sciencedirect.com/science/article/abs/pii/S0960077925014067?via%3Dihub
  3. Quantifying Musculoskeletal Strain in Laptop Users with Laplace Transformation and Delay Differential Equations. https://www.lhscientificpublishing.com/Journals/articles/DOI-10.5890-JEAM.2025.12.002.aspx

Yasir Nawaz | Machine Learning | Research Excellence Award

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Dr. Yasir Nawaz | Machine Learning | Research Excellence Award

Dr. Ankit Agrawal is a cardiology fellow at the University of Arkansas for Medical Sciences with 943 citations, h-index 18, and 33 i10-index. His research spans structural cardiology, transcatheter valve therapies, pericardial diseases, cardiovascular imaging, meta-analyses, and outcomes research, emphasizing evidence-based strategies to improve cardiovascular care and patient safety.

Citation Metrics (Google Scholar)

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Citations 1391

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Featured Publications

Supattana Sukrat | Digital Transformation | Best Researcher Award

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Assist. Prof. Dr. Supattana Sukrat | Digital Transformation | Best Researcher Award

Assist. Prof. Dr. Supattana Sukrat | Prince of Songkla University | Thailand 

Assist. Prof. Dr. Supattana Sukratis a distinguished academic at the Faculty of Commerce and Management, Prince of Songkla University, Trang Campus. With a Ph.D. in Information Technology from King Mongkut’s University of Technology Thonburi, her expertise spans Digital Business, Digital Transformation, Social Commerce, and Management Information Technology. She has actively contributed to various research projects, including studies on digital transformation maturity models, sustainability performance, and agri-digital innovation in Thailand and Southeast Asia. Assist. Prof. Dr. Supattana Sukrat has authored influential works such as A Digital Business Transformation Maturity Model for Micro Enterprises in Developing Countries and numerous papers in the Journal of Education and Innovative Learning. Her earlier research includes frameworks for recommendation systems in social commerce and analyses of e-commerce strategies for local enterprises. With 89 citations by 87 documents, 6 publications, and an h-index of 5, she has demonstrated consistent research impact in the field of information systems and digital innovation.Assist. Prof. Dr. Supattana Sukrat dedication to integrating digital transformation into education and business development continues to shape sustainable growth and technology adoption in emerging markets.

Profiles : Scopus | Google Scholar

Sukrat, S., and Leeraphong, A. (2023). A digital business transformation maturity model for micro enterprises in developing countries. Global Business and Organizational Excellence, 00, 1–28.

Sukrat, S., and Leerapong, A. (2022). An effect of teaching and learning based on work-integrated learning and multidisciplinary instruction in digital marketing and emerging technologies subject. Journal of Education and Innovative Learning, 2(3), 205–222.

Leerapong, A., and Sukrat, S. (2022). Developing learners’ competency through project-based learning: Case study of digital marketing and management course, Faculty of Commerce and Management, Prince of Songkla University, Trang Campus. Journal of Education and Innovative Learning, 2(1), 35–49.

Sukrat, S., and Papasratorn, B. (2018). An architectural framework for developing a recommendation system to enhance vendors’ capability in C2C social commerce. Social Network Analysis and Mining, 8(1), 1–13.

Sukrat, S. (2015). Guidelines for business directions of e-commerce for OTOP. University of the Thai Chamber of Commerce Journal (Humanities and Social Sciences), 35(1), 50–64.

Prof. Keon Baek | Data analysis | Best Researcher Award

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Keon Baek | Data analysis | Best Researcher Award

Keon Baek | Chosun University | South Korea

Keon Baek is a dedicated Data Scientist and Electrical Engineer based in Gwangju, South Korea 1 🇰🇷. With a strong academic background and practical experience, he focuses on power market analysis, policy design, and technology development through insightful data analysis 📊. His research interests include consumer behavior 💡, demand flexibility 🔄, market and policy implications 🏛️, and the growing field of vehicle electrification 🚗⚡. Keon’s passion lies in leveraging data to shape the future of sustainable energy.

Professional profile : 

orcid

Google scholar

Summary of Suitability : 

Keon Baek, a dedicated Data Scientist and Electrical Engineer from Gwangju, South Korea, is an excellent candidate for the Best Researcher Award. With a robust academic foundation and a wealth of hands-on experience, Keon has demonstrated significant contributions to the fields of power market analysis, policy design, and technology development. His expertise lies in using data to inform decisions around sustainable energy, which aligns perfectly with the award’s criteria for groundbreaking research that drives innovation and societal impact.

Education :

  • Ph.D. (Power System & Economics) – Gwangju Institute of Science and Technology (2020.03 – 2023.02) ⚡💰
  • M.S. (Power System & Economics) – Gwangju Institute of Science and Technology (2018.03 – 2020.02) 💡📈
  • B.S. (Electrical Engineering) – Korea Advanced Institute of Science and Technology (2004.03 – 2011.02) ⚙️🔌

Experience :

  • Assistant Professor, Dept. of Electrical Engineering – Chosun University (2023. 09 – 2023. 08) 👨‍🏫💡
  • Post-doc., Research Institute for Solar and Sustainable Energies (RISE) – Gwangju Institute of Science and Technology (2023. 02 – 2023.08) ☀️🌱
  • Electric Engineer, Distribution Transformer Division – Hyundai (2017. 04 – 2018. 07) 🏭⚡
  • Engineer, Offshore Plant Engineering Center – Korea Shipbuilding & Offshore Engineering (2015. 02 – 2017. 03) 🚢🌊
  • Associate Researcher, Wind Power System Research Center – Korea Shipbuilding & Offshore Engineering (2011. 02 – 2015. 01)
  • Publication Top NOTES :
    Resident Behavior Detection Model for Environment Responsive Demand Response :

    • Authors: K. Baek, E. Lee, J. Kim

    • Published in: IEEE Transactions on Smart Grid, 2021, Vol. 12, Issue 5, Pages 3980-3989

    • Citations: 35

    • Summary: This paper proposes a model for detecting resident behavior in smart grid environments, aiming to optimize demand response (DR) mechanisms. The approach focuses on adjusting electricity usage patterns by predicting and responding to residents’ behavior, enhancing both energy efficiency and grid reliability. This model is crucial for increasing the responsiveness and flexibility of demand response programs in residential areas.

    Evaluation of Demand Response Potential Flexibility in the Industry Based on a Data-Driven Approach :

    • Authors: E. Lee, K. Baek, J. Kim

    • Published in: Energies, 2020, Vol. 13, Issue 23, Article 6355

    • Citations: 28

    • Summary: This study assesses the potential flexibility of demand response programs in industrial settings using a data-driven approach. It evaluates how various industrial processes can be adjusted to provide flexibility in energy consumption without negatively impacting production efficiency. The research also explores the use of real-time data to enhance decision-making in demand response strategies, enabling more effective integration of renewable energy sources.

    Multi-Objective Optimization of Home Appliances and Electric Vehicles Considering Customer’s Benefits and Offsite Shared Photovoltaic Curtailment :

    • Authors: Y. Kwon, T. Kim, K. Baek, J. Kim

    • Published in: Energies, 2020, Vol. 13, Issue 11, Article 2852

    • Citations: 22

    • Summary: This paper discusses a multi-objective optimization approach for managing home appliances and electric vehicles (EVs) while considering customer benefits and photovoltaic (PV) energy curtailment. It focuses on maximizing the benefits to consumers by coordinating the use of home appliances and EVs with the availability of solar energy while reducing the waste of excess PV power. The study is significant for improving the efficiency of residential energy management systems.

    Stochastic Optimization-Based Hosting Capacity Estimation with Volatile Net Load Deviation in Distribution Grids : 

    • Authors: Y. Cho, E. Lee, K. Baek, J. Kim

    • Published in: Applied Energy, 2023, Vol. 341, Article 121075

    • Citations: 13

    • Summary: The research proposes a stochastic optimization method to estimate hosting capacity in distribution grids, accounting for the volatile nature of net load deviation. The study addresses challenges related to integrating renewable energy sources, such as solar and wind, into existing power grids. It develops a model that quantifies the grid’s capacity to absorb additional renewable energy without compromising stability, providing valuable insights for grid operators managing increasing renewable penetration.

    Datasets on South Korean Manufacturing Factories’ Electricity Consumption and Demand Response Participation :

    • Authors: E. Lee, K. Baek, J. Kim

    • Summary: This dataset publication presents detailed information on electricity consumption patterns and the participation of South Korean manufacturing factories in demand response programs. It provides real-world data that can be used to evaluate the effectiveness of demand response strategies and analyze consumption behaviors in industrial sectors. Researchers and energy managers can leverage this dataset to optimize industrial demand response programs and improve grid reliability.

Dr. Abdulrahman Alnaim | Technology | Excellence in Research Award

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Dr. Abdulrahman Alnaim | Technology | Excellence in Research Award

Dr. Abdulrahman Alnaim | Technology – Associate Professor at King Faisal University, Saudi Arabia

Dr. Abdulrahman Khalid Alnaim is an accomplished academic and researcher specializing in computer science and information security. With a strong foundation in computer information systems and management information systems, he has dedicated his career to advancing research in emerging technologies such as cybersecurity, cloud computing, and network architecture. His work is characterized by innovative approaches to securing next-generation networks and optimizing system performance, reflecting a commitment to both academic excellence and practical applications in the tech industry.

Profile:

Google Scholar

Education:

Dr. Alnaim earned his Ph.D. in Computer Science from Florida Atlantic University, USA, where he focused on developing secure and efficient computing models. He also holds a Master’s in Management Information Systems from Nova Southeastern University, USA, which enriched his understanding of integrating technology with business strategies. His academic journey began at King Faisal University, Saudi Arabia, where he completed his Bachelor’s degree in Computer Information Systems, laying the groundwork for his passion for research and technology. This diverse educational background has enabled him to approach complex problems with a multidisciplinary perspective.

Experience:

Dr. Alnaim has served at King Faisal University, Saudi Arabia, in various academic roles. Starting as a Teacher Assistant in 2012, he quickly advanced to become a Lecturer and later an Assistant Professor in the Management Information Systems Department within the School of Business. Throughout his tenure, he has contributed significantly to curriculum development, academic research, and student mentorship. His professional journey reflects a consistent commitment to fostering an environment of academic growth, research innovation, and knowledge dissemination.

Research Interests:

Dr. Alnaim’s research interests lie in the domains of cloud technologies, cybersecurity, and network architecture, with a particular focus on emerging trends like 5G/6G networks, network function virtualization (NFV), and edge computing. His work explores the development of robust security frameworks, optimized resource management strategies, and innovative architectures for next-generation networks. His research not only addresses theoretical challenges but also provides practical solutions for enhancing cybersecurity, system efficiency, and data integrity in complex digital environments.

Awards:

While Dr. Alnaim’s distinguished academic career is marked by numerous achievements, his contributions to research have earned him recognition within the academic community. His work has been cited extensively, reflecting its influence on contemporary studies in cybersecurity and network technologies. His dedication to research excellence is evident through his continuous pursuit of knowledge, innovative problem-solving, and commitment to advancing the field of computer science.

Publications 📚:

  1. “Zero Trust Strategies for Cyber-Physical Systems in 6G Networks” (2025) – Mathematics
    This paper discusses advanced security models tailored for cyber-physical systems in 6G environments. 🚀

  2. “Securing 5G Virtual Networks: A Critical Analysis of SDN, NFV, and Network Slicing Security” (2024) – International Journal of Information Security
    The article provides an in-depth analysis of security vulnerabilities and countermeasures in 5G networks. 🔐

  3. “Trust Management and Resource Optimization in Edge and Fog Computing Using the CyberGuard Framework” (2024) – Sensors
    This research introduces the CyberGuard framework for enhancing trust management in edge and fog computing environments. 🌐

  4. “Network Slicing in 6G: A Strategic Framework for IoT in Smart Cities” (2024) – Sensors
    A strategic approach to optimizing network slicing for IoT applications in smart cities. 🏙️

  5. “Classification of Alzheimer’s Disease Using MRI Data Based on Deep Learning Techniques” (2024) – Journal of King Saud University – Computer and Information Sciences
    This study leverages deep learning models to improve the early detection of Alzheimer’s disease using MRI data. 🧠

  6. “Machine-Learning-Based IoT–Edge Computing Healthcare Solutions” (2023) – Electronics
    Focuses on integrating machine learning with IoT and edge computing to enhance healthcare services. 💡

  7. “A Misuse Pattern for Modifying Non-Control Threats in NFV” (2022) – Future Internet
    Proposes a model to identify and mitigate non-control threats in network function virtualization environments. 🖥️

These publications have collectively garnered significant citations, underscoring their impact on academic research and industry practices. 📈

Conclusion:

Dr. Abdulrahman Khalid Alnaim exemplifies the qualities of an outstanding researcher, with a robust academic background, extensive research contributions, and a commitment to advancing the field of computer science and information security. His work in cybersecurity, cloud technologies, and network architecture has not only enriched academic discourse but also provided practical solutions to real-world challenges.

His innovative approach, combined with a strong publication record and active involvement in academic and research communities, makes him a deserving candidate for the Excellence in Research Award. Dr. Alnaim’s contributions reflect the values of academic rigor, intellectual curiosity, and a relentless pursuit of knowledge that this prestigious award seeks to honor.

Prof. Wan Quan Liu | Big Data Analysis | Best Researcher Award

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Prof. Wan Quan Liu | Big Data Analysis | Best Researcher Award

Prof. Wan Quan Liu, Sun Yat-sen University, China

Prof. Wan Quan Liu is a prominent professor at the School of Intelligent System Engineering at Sun Yat-sen University, where he has been serving since 2021. He earned his Ph.D. in Electrical Engineering from Shanghai Jiaotong University (1991-1993) and holds a Master of Science in Operational Research and Control from the Institute of Systems Science at the Chinese Academy of Science (1985-1988), as well as a Bachelor’s degree in Mathematics from Qufu Normal University (1981-1985). Previously, he was an ARC Fellow and Senior Lecturer at Curtin University of Technology from 2000 to 2021. Prof. Liu’s research focuses on computer vision, deep learning networks, optimization, and intelligent control systems, where he has made significant contributions that advance these fields.

Professional Profile

Scopus
Orcid

Suitability for the Best Researcher Award:

Prof. Wan Quan Liu’s combination of an extensive educational background, significant research contributions, and recognition in the form of awards makes him an excellent candidate for the Best Researcher Award. His work in computer vision, deep learning, and intelligent control systems is highly relevant in today’s technology-driven landscape, with implications for various sectors including robotics, automation, and artificial intelligence.

The recognition he has received, both at the national and provincial levels, further solidifies his status as a leading researcher in his field. His ongoing research and publications contribute to advancements in critical technologies, making a tangible impact on both academia and industry.

Educational Background:

Prof. Wan Quan Liu earned his PhD in Electrical Engineering from Shanghai Jiaotong University (1991-1993). He holds a Master of Science in Operational Research and Control from the Institute of Systems Science at the Chinese Academy of Science (1985-1988) and a Bachelor’s degree in Mathematics from Qufu Normal University (1981-1985).

Academic Experience:

Currently, Prof. Liu is a professor at the School of Intelligent System Engineering at Sun Yat-sen University (2021-present). Prior to this, he held various positions, including ARC Fellow and Senior Lecturer at Curtin University of Technology (2000-2021).

Research Interests:

Prof. Liu specializes in computer vision, deep learning networks, optimization, and intelligent control systems, contributing significantly to advancements in these fields.

Awards and Recognition:

His exceptional work has earned him several accolades, including:

  • 2023: National Talented Researcher from the National Education Committee
  • 2022: Pearl Leading Researcher from Guangdong Province

Publication Top Notes:

  • Title: AFS-FCM with Memory: A Model for Air Quality Multi-dimensional Prediction with Interpretability
    • Publication Year: 2024
  • Title: Efficient and Fast Joint Sparse Constrained Canonical Correlation Analysis for Fault Detection
    • Publication Year: 2024
  • Title: Efficient and Robust Sparse Linear Discriminant Analysis for Data Classification
    • Publication Year: 2024
  • Title: FedREM: Guided Federated Learning in the Presence of Dynamic Device Unpredictability
    • Publication Year: 2024
  • Title: Invertible Residual Blocks in Deep Learning Networks
    • Publication Year: 2024