バイオグラフィー
Meng Wan currently serving as an assistant professor at the Computer Network Information Center of the Chinese Academy of Sciences, has an academic background with a Bachelor's degree from Beijing University of Posts and Telecommunications (2016), a Master's from the University of Southampton, UK (2018), and a Ph.D. from the University of Science and Technology Beijing (2024).
His research spans across software and systems engineering, time series forecasting, and high-performance computing, focusing on interdisciplinary applications such as artificial intelligence cloud platforms, photovoltaic power generation prediction and ecological carbon cycles. He has published more than 20 publications and 1 section of monograph in respected journals and international conferences like IEEE Transactions on Sustainable Energy and the Journal of System Architecture, etc.
He has also played an active role in research projects, hosting/participating in more than 10 national or fund projects. His won the second prize in the ANAC 2018, one of the competition in IJCAI 2018. He further contributes to his field as a reviewer for various international conferences.
研究の興味
System Architecture(software and cloud platform); Multivariate Time Series; Transformer-based Neural Networks; High-performance computing.
Editor
仕事内容
Assistant Professor
Chinese Academy of Sciences
Department of Computer Science
China
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研究論文
- Wishful Thinking or Valuable Forecasts? The Value of Policy Rate Predictions in Sweden
- Influence of Polycarboxylate Superplasticizer on the Calorimetric and Physicomechanical Properties of Mortar
- Effect of Rainfall on Water Parameters in Recreational Lakes in Heidelberg, Germany
- Utilising Phytoremediation in Green Technologies: Exploring Natural Means of Environmental Clean-up
- Communication Training at Medical School: A Quantitative Analysis
- The Influence of Dynamical Downscaling and Boundary Layer Selection on Egypt’s Potential Evapotranspiration using a Calibrated Version of the Hargreaves-samani Equation: RegCM4 Approach
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