Qiang He | Computer Science | Computer Scientists Awards

Published on by Computer Scientists Awards

Young Scientist Award

Qiang He
Affiliation Northeastern University
Country China
Scopus ID 57193014262
Documents 191
Citations 2,807
h-index 30
Subject Area Computer Science
Event Computer Scientists Awards
ORCID 0000-0002-3695-723X

Qiang He

Northeastern University, China

Qiang He is a tenured professor and doctoral supervisor at Northeastern University whose academic activities focus on cloud computing, computing power networks, distributed systems, and machine learning. His scholarly profile includes extensive editorial responsibilities, peer-review service for internationally recognized journals, and sustained contributions to high-impact research venues. With 191 indexed publications, 2,807 citations, and an h-index of 30, his research demonstrates continuous influence across service computing, edge computing, optimization, and intelligent networking. These accomplishments provide a substantial foundation for consideration within the Young Scientist Award category.[1]

Abstract

This article summarizes the academic profile of Qiang He, highlighting research achievements in cloud computing, service computing, machine learning, mobile edge computing, and distributed intelligent systems. His publication record demonstrates consistent participation in internationally recognized journals and conferences while addressing quality of service prediction, decentralized edge computing, optimization algorithms, and microservice management. These contributions have strengthened modern computing infrastructures and provide evidence of sustained scholarly productivity suitable for academic recognition.[2]

Keywords

Cloud Computing, Service Computing, Machine Learning, Edge Computing, QoS Prediction, Computing Power Networks, Evolutionary Algorithms, Microservices, Distributed Systems, Artificial Intelligence.

Introduction

Qiang He has established an interdisciplinary research program integrating theoretical computer science with practical cloud-based services. His work combines intelligent optimization, network resource allocation, and scalable service architectures to improve the reliability and efficiency of distributed computing platforms. Beyond research, he contributes to the academic community through editorial service for numerous journals and peer review for leading IEEE and ACM publications, reflecting professional recognition within the international research community.[3]

Research Profile

  • Tenured Professor and Doctoral Supervisor at Northeastern University.
  • Research focuses on cloud computing, machine learning, service computing and computing power networks.
  • Editorial board member for sixteen academic journals.
  • Recipient of the Liaoning Provincial Youth Science Fund.
  • Author of numerous journal papers, conference publications and invention patents.

Research Contributions

His recent investigations emphasize adaptive feature learning for quality-of-service prediction, communication-efficient decentralized edge data deduplication, influence maximization through evolutionary computation, and game-theoretic request dispatching for mobile edge computing. These studies combine advanced artificial intelligence with distributed infrastructure optimization to improve scalability, reliability, and computational efficiency across modern cloud environments.[4]

Publications

  • An Adaptive Feature Interaction Learning Model for QoS Prediction With Multi-Source Context. IEEE Transactions on Services Computing (2026).
  • Popularity-Aware Communication-Efficient Decentralized Edge Data Deduplication. IEEE Transactions on Parallel and Distributed Systems (2026).
  • Enhancing Evolutionary Algorithms with Solution Prediction for Influence Maximization. Applied Soft Computing (2026).
  • A Game-Theoretic Approach for Microservice Request Dispatching in Mobile Edge Computing Systems. IEEE Transactions on Services Computing (2025).

Research Impact

Bibliometric indicators demonstrate a productive and influential academic career. His publications have accumulated more than 2,800 citations while maintaining an h-index of 30. Multiple highly cited papers, active participation in premier conferences, and more than thirty national invention patents collectively illustrate measurable research influence and sustained innovation within computer science.[5]

Award Suitability

The Young Scientist Award recognizes emerging researchers demonstrating significant scholarly achievement, innovation, and professional service. Qiang He’s publication record, editorial engagement, interdisciplinary research, and sustained impact in cloud and service computing align well with these objectives. His combination of scientific productivity and practical technological contributions represents a strong academic profile for international recognition.[6]

Conclusion

Qiang He has developed a distinguished research portfolio spanning cloud services, distributed intelligence, optimization, and machine learning. His combination of impactful publications, editorial leadership, patent activity, and international scholarly engagement demonstrates a sustained commitment to advancing computer science research and supports his recognition within the Computer Scientists Awards.

References

  1. Elsevier. (n.d.). Scopus Author Details: Qiang He, Author ID 57193014262.
    https://www.scopus.com/authid/detail.uri?authorId=57193014262
  2. He, Q. (2026). An Adaptive Feature Interaction Learning Model for QoS Prediction With Multi-Source Context. IEEE Transactions on Services Computing.
    https://doi.org/10.1109/TSC.2026.3655980
  3. He, Q. (2026). Popularity-Aware Communication-Efficient Decentralized Edge Data Deduplication. IEEE TPDS.
    https://doi.org/10.1109/TPDS.2025.3638945
  4. He, Q. (2026). Enhancing Evolutionary Algorithms with Solution Prediction for Influence Maximization. Applied Soft Computing.
    https://doi.org/10.1016/J.ASOC.2025.114399
  5. He, Q. (2025). A Game-Theoretic Approach for Microservice Request Dispatching in Mobile Edge Computing Systems. IEEE Transactions on Services Computing.
    https://doi.org/10.1109/TSC.2025.3602905
  6. Computer Scientists Awards. Young Scientist Award Recognition Program.
    https://computerscientists.net/

Serigne Modou Sarr | Computer Science | Best Researcher Award

Published on by Computer Scientists Awards

Best Researcher Award

Serigne Modou Sarr
University of Alioune Diop, Senegal

Serigne Modou Sarr
Affiliation University of Alioune Diop
Country Senegal
Scopus ID 58618515700
Documents 3
Citations 3
h-index 1
Subject Area Computer Science
Event Computer Scientists Awards
ORCID 0000-0001-6313-2164

Serigne Modou Sarr is a researcher affiliated with the University of Alioune Diop, Senegal. His scholarly activities focus primarily on ecosystem management, environmental sustainability, biodiversity conservation, and socio-economic resilience in protected landscapes. His research combines field investigations with applied environmental assessment to support evidence-based decision making for natural resource management. Although his indexed publication portfolio remains selective, his studies demonstrate interdisciplinary approaches that integrate ecological observations with community-based perspectives. This profile highlights his academic contributions and evaluates his suitability for recognition through the Best Researcher Award.[1]

Abstract

The research portfolio of Serigne Modou Sarr emphasizes sustainable environmental governance through investigations of protected areas, mangrove ecosystems, ecosystem services, fisheries, and climate resilience. His publications contribute practical knowledge concerning conservation strategies, valuation of ecosystem resources, and community perceptions that support long-term environmental planning in Senegal. Recent studies extend this work by examining nature-based solutions and coastal resilience, providing useful scientific evidence for policymakers and environmental managers.[2]

Keywords

Protected areas; Ecosystem services; Mangrove ecosystems; Fisheries; Climate resilience; Environmental management; Senegal; Nature-based solutions.

Introduction

Environmental sustainability requires multidisciplinary approaches that combine ecological science with socio-economic understanding. Serigne Modou Sarr’s research addresses these challenges through analyses of coastal ecosystems, biodiversity conservation, and community engagement. His publications examine how protected ecosystems provide valuable environmental and economic services while supporting resilient livelihoods. These studies contribute to regional environmental policy and strengthen understanding of conservation practices in West Africa.[3]

Research Profile

According to indexed academic records, the researcher has authored publications focusing on environmental assessment and ecosystem conservation. His work spans ecosystem valuation, fisheries diversity, mangrove ecology, protected area management, and socio-economic resilience. The research demonstrates consistent interest in linking scientific evidence with sustainable resource governance and practical conservation outcomes.[1]

Research Contributions

  • Investigated ecosystem services provided by protected forests and mangrove ecosystems.
  • Evaluated biodiversity and fisheries resources within Senegalese mangrove environments.
  • Studied community perceptions regarding conservation and ecosystem management.
  • Examined nature-based solutions supporting socio-economic resilience in coastal environments.

Publications

  • Contribution of Nature-Based Solutions to the Socio-Economic Resilience of Market Gardening in a Coastal Environment (2026).
  • Diversity of Fishery Resources in Mangrove Ecosystems (2026).
  • Local Perceptions of Ecosystem Services Provided by Forest and Mangrove Ecosystems (2025).

Research Impact

The available bibliometric indicators record three indexed documents, three citations, and an h-index of one. While these metrics indicate an emerging publication profile, the research demonstrates practical regional relevance by addressing conservation priorities, ecosystem services, biodiversity management, and sustainable development. The interdisciplinary nature of these studies provides useful evidence for environmental planning and community-based conservation initiatives.[4]

Award Suitability

The Best Researcher Award recognizes scholarly achievement, research integrity, and meaningful academic contribution. Serigne Modou Sarr’s investigations into ecosystem services, fisheries, mangrove conservation, and climate resilience demonstrate scientific rigor and relevance to sustainable development objectives. His research supports evidence-informed environmental policy and illustrates continued commitment to applied environmental scholarship deserving professional recognition.[5]

Conclusion

Serigne Modou Sarr has established a focused academic profile centered on environmental conservation and sustainable ecosystem management. His published work contributes to scientific understanding of protected areas and community resilience while providing practical insights for environmental governance. Continued research and collaboration are expected to further strengthen the scholarly impact of his contributions.

References

  1. Elsevier. (n.d.). Scopus author details: Serigne Modou Sarr, Author ID 58618515700.
    https://www.scopus.com/authid/detail.uri?authorId=58618515700
  2. International Journal of Environment and Climate Change. (2026). Contribution of Nature-Based Solutions to the Socio-Economic Resilience of Market Gardening.
    https://doi.org/10.9734/ijecc/2026/v16i25301
  3. Agriculture, Forestry and Fisheries. (2026). Diversity of Fishery Resources in Mangrove Ecosystems.
    https://doi.org/10.11648/j.aff.20261501.13
  4. American Journal of Agriculture and Forestry. (2025). Local Perceptions of Ecosystem Services.
    https://doi.org/10.11648/j.ajaf.20251305.11
  5. European Scientific Journal. (2021). Estimation Of The Value Of Goods And Services Produced By Protected Areas.
    https://doi.org/10.19044/esj.2021.v17n43p282

Dr. Ehsan Adibnia | Computer Science | Editorial Board Member

Published on by Computer Scientists Awards

Dr. Ehsan Adibnia | Computer Science | Editorial Board Member

University of Sistan and Baluchestan | Iran

Dr. Ehsan Adibnia is a dedicated researcher in Electrical Engineering with a strong interdisciplinary focus spanning artificial intelligence, machine learning, deep learning, nanophotonics, optics, plasmonics, and photonic device engineering. His research primarily explores the integration of AI-driven approaches in nanophotonic design, optical switching, and biosensing applications, enabling significant advancements in optical computing and sensing technologies. He has made notable contributions to the fields of photonics and deep learning-based optical system design through innovative studies on inverse design, nonlinear plasmonic structures, and photonic crystal encoders. His expertise extends to advanced simulation tools such as Lumerical, COMSOL, and RSoft, as well as programming in MATLAB and Python for modeling and data analysis. Dr. Adibnia has actively contributed to scientific research through multiple peer-reviewed publications in prestigious international journals. According to Google Scholar, he has accumulated 6,540 citations, an h-index of 45, and an i10-index of 156, reflecting his significant academic influence. His Scopus profile records 70 citations across 53 documents with an h-index of 5, highlighting his growing global research impact.

Profiles

Scopus | ORCID | Google Scholar

Featured Publications

Adibnia, E., Mansouri-Birjandi, M. A., & Ghadrdan, M. (2024). A deep learning method for empirical spectral prediction and inverse design of all-optical nonlinear plasmonic ring resonator switches. Scientific Reports, 14, 5787.

Adibnia, E., Ghadrdan, M., & Mansouri-Birjandi, M. A. (2024). Nanophotonic structure inverse design for switching application using deep learning. Scientific Reports, 14, 21094.

Adibnia, E., Ghadrdan, M., & Mansouri-Birjandi, M. A. (2025). Chirped apodized fiber Bragg gratings inverse design via deep learning. Optics & Laser Technology, 181, 111766.

Jafari, B., Gholizadeh, E., Jafari, B., & Adibnia, E. (2023). Highly sensitive label-free biosensor: graphene/CaF2 multilayer for gas, cancer, virus, and diabetes detection. Scientific Reports, 13, 16184.

Soroosh, M., Al-Shammri, F. K., Maleki, M. J., Balaji, V. R., & Adibnia, E. (2025). A compact and fast resonant cavity-based encoder in photonic crystal platform. Crystals, 15, 24.

Dr. Han Zhang | Computer Science | Best Researcher Award

Published on by Computer Scientists Awards

Han Zhang | Computer Science | Best Researcher Award

Research Institute of Petroleum Exploration and Development, China

Dr. Han Zhang is a young and dedicated researcher at the China National Petroleum Corporation Research Institute of Petroleum Exploration and Production, where he focuses on advancing intelligent reservoir development and optimization for the future of the energy industry. With a strong educational foundation, he earned his bachelor’s degree in Marine Oil and Gas Engineering from a prestigious petroleum university in China, majoring in reservoir and oil production engineering, before continuing his master’s and doctoral studies in Oil and Gas Field Development Engineering at the same institute. His research centers on the development of advanced mathematical and numerical models that address key challenges in petroleum engineering, particularly intelligent reservoir management. Dr. Zhang has contributed to one national-level and one provincial-level research project and has also taken part in an industry consultancy project, demonstrating his ability to bridge academic research with practical applications. He has published peer-reviewed articles, including a notable study on gated recurrent unit-based dynamic characterization methods for horizontal wells in carbonate reservoirs, as well as a paper on closed-loop optimization systems for evaluating development potential with water-alternating gas flooding. With three patents under process and active membership in the Society of Petroleum Engineers, Dr. Zhang has positioned himself as a rising scholar committed to innovation. His contributions include refining the analytic hierarchy process through coupling with entropy weight methods for more objective production evaluation, as well as pioneering predictive models that enhance reservoir characterization. He aspires to continue developing transformative technologies that promote efficiency, sustainability, and innovation in petroleum exploration and production.

Profile: ORCID 

Featured Publications

Zhang, H. (2025). A closed-loop optimization system for evaluating the development effect and potential of producers with water alternating gas flooding. Processes.

Zhang, H. (2025). A dynamic characterization method for horizontal wells based on the gated recurrent unit: A case study of a carbonate reservoir in the Middle East. In Springer Series in Geomechanics and Geoengineering. Springer.