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Dr. Shuang Wang | Scheduling Optimization Award | Best Researcher Award

Dr. Shuang Wang, Southeast University, China

Dr. Shuang Wang šŸŽ“ is a Lecturer at Southeast University, China šŸ‡ØšŸ‡³ and an Honorary Lecturer at Macquarie University, Australia šŸ‡¦šŸ‡ŗ. She earned her PhD from Southeast University in 2020. Her research focuses on Service Computing, Big Data, and Artificial Intelligence. With a rich publication record in top-tier journals and conferences, including IEEE Transactions and international conferences, she contributes significantly to the field. Dr. Wang’s expertise spans performance analysis, multi-queue scheduling, and workflow optimization in cloud environments. She has also been actively engaged in review activities for prestigious conferences and journals.

 

Publication Profile

Google Scholar

Education Experience

Dr. Shuang Wang’s academic journey began with her undergraduate studies at Nanjing Agricultural University, China šŸ‡ØšŸ‡³, from September 2011 to June 2015, laying the foundation for her future pursuits. She then pursued her PhD at Southeast University, China šŸŽ“, from September 2015 to December 2020, honing her expertise in Service Computing and Artificial Intelligence. Embracing global perspectives, she undertook a Visiting PhD position at Macquarie University, Australia šŸŒ, from November 2019 to November 2020, enriching her academic insights. These educational experiences reflect her dedication to continuous learning and cross-cultural exchange, shaping her into a dynamic scholar with a global perspective.

 

Working Experience

Dr. Shuang Wang embarked on her academic journey as a Research Associate at Macquarie University, Australia šŸ‡¦šŸ‡ŗ, from November 2020 to November 2021, delving into the vibrant research landscape alongside esteemed colleagues. Transitioning seamlessly, she now serves as a Lecturer at Southeast University, China šŸ‡ØšŸ‡³, starting from January 2022. Her dual roles reflect her commitment to academia, bridging continents to impart knowledge and drive innovation. Through her tenure, Dr. Wang continues to enrich the academic community, blending her expertise in Service Computing, Big Data, and Artificial Intelligence with her passion for teaching and research.

 

Research Focus

Dr. Shuang Wang’s research focus primarily revolves around Service Computing šŸ–„ļø, encompassing various facets such as performance analysis, scheduling optimization, and resource allocation in cloud environments. Her work delves into enhancing the efficiency and profitability of cloud services through innovative approaches like queueing theory, multi-queue request scheduling, and adaptive learning methodologies. With a keen interest in addressing real-world challenges, she explores topics like energy minimization, privacy-aware workflow scheduling, and cost-effective resource management, contributing significantly to the advancement of Service Computing paradigms. Dr. Wang’s interdisciplinary research bridges theoretical insights with practical applications, driving progress in cloud computing and beyond.

 

Publication Top Notes

šŸ“ Performance analysis for heterogeneous cloud servers using queueing theory – S Wang, X Li, R Ruiz, IEEE Transactions on Computers, 18 citations, 2019
šŸ“ Assessment2Vec: learning distributed representations of assessments to reduce marking workload – S Wang et al., International Conference on Artificial Intelligence in Education, 11 citations, 2021
šŸ“ Multi-queue request scheduling for profit maximization in IaaS clouds – S Wang et al., IEEE Transactions on Parallel and Distributed Systems, 10 citations, 2021
šŸ“ Performance analysis and optimization on scheduling stochastic cloud service requests: a survey – S Wang et al., IEEE Transactions on Network and Service Management, 7 citations, 2022
šŸ“ Scheduling method with adaptive learning for microservice workflows with hybrid resource provisioning – S Gu, H Li, M Liu, S Wang, International Journal of Machine Learning and Cybernetics, 6 citations, 2021
šŸ“ A survey on location-driven influence maximization – T Cai et al., arXiv preprint arXiv:2204.08005, 5 citations, 2022
šŸ“ An arithmetic differential privacy budget allocation method for the partitioning and publishing of location information – Y Yan et al., 2020 IEEE 19th International Conference on Trust, Security and Privacy, 5 citations, 2020
šŸ“ Accurate and reliable service recommendation based on bilateral perception in multi-access edge computing – Z Liu et al., IEEE Transactions on Services Computing, 4 citations, 2022
šŸ“ Towards predictive analytics in mental health care – A Beheshti et al., 2021 International Joint Conference on Neural Networks (IJCNN), 3 citations

Shuang Wang | Scheduling Optimization Award | Best Researcher Award

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