Fanglong Yao Editor at IgMin Research
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Biography
Fanglong Yao received the B.Sc. degree from Inner Mongolia University, Hohhot, China, in 2017, and the Ph.D. degree from the Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China, in 2022. He is currently a Post-Doctoral Researcher and assistant professor with the Aerospace Information Research Institute, Chinese Academy of Sciences. His research interests include cognitive intelligence, embodied intelligence, and swarm intelligence, including aerospace spatiotemporal data analysis; Multimodal fusion and reasoning; Embodied intelligence and multi-agent learning. He is the reviewer of the IEEE Transactions on Neural Networks and Learning Systems (TNNLS) and Artificial Intelligence Review. He has received Best Researcher Award of International Research Awards on Network Science and Graph Analytics (2023), Chinese Academy of Sciences President's Excellence Award (2022), National Scholarship (2021), Graduate Forum Report Excellence Award (2021).
Research Interest
Spatiotemporal data analysis and computer vision; Multimodal fusion and reasoning; Embodied intelligence and multi-agent learning
Editor
Work Details
Assistant Professor
Chinese Academy of Sciences
Aerospace Information Research Institute
China
0000-0003-4187-9755 Contribution by Topic Area
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Which articles are now trending?
Research Articles
- The Antioxidant and Antidepressant Properties of Dietary Proteins Derived from Egg and Bean Extracts and Their Acute Toxicity: A Journey from Nutrition to Pharmacognosy
- 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
- Trend of SO2 Gas Dry Deposition in Vietnam
- Effect of Rainfall on Water Parameters in Recreational Lakes in Heidelberg, Germany
- A New Modification of Classification of Traumatic Patients with Pelvic Fracture
- Exploring Upper Limb Kinematics in Limited Vision Conditions: Preliminary Insights from 3D Motion Analysis and IMU Data
