What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Operating system
Bin Hu spends much of his time researching Artificial intelligence, Pattern recognition, Electroencephalography, Machine learning and Support vector machine.
His work carried out in the field of Artificial intelligence brings together such families of science as Functional networks and Functional brain.
His Pattern recognition study combines topics in areas such as Resting state fMRI and Logistic regression.
Electroencephalography and Intelligent decision support system are commonly linked in his work.
The various areas that Bin Hu examines in his Machine learning study include Tractography, Valence, Arousal and Correlation.
He interconnects Artificial neural network, Hydraulic machinery, Injection moulding, Signal and Least squares in the investigation of issues within Support vector machine.
His most cited work include:
- Optimal parameters selection for BP neural network based on particle swarm optimization: A case study of wind speed forecasting (247 citations)
- Smart Clothing: Connecting Human with Clouds and Big Data for Sustainable Health Monitoring (204 citations)
- Energy-Latency Tradeoff for Energy-Aware Offloading in Mobile Edge Computing Networks (181 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Electroencephalography, Pattern recognition, Depression and Machine learning.
The study of Artificial intelligence is intertwined with the study of Computer vision in a number of ways.
His study in Electroencephalography is interdisciplinary in nature, drawing from both Resting state fMRI, Speech recognition, Cognition and Audiology.
His Cognition study deals with the bigger picture of Neuroscience.
His Pattern recognition and Feature selection and Wavelet investigations all form part of his Pattern recognition research activities.
Bin Hu regularly links together related areas like Artificial neural network in his Support vector machine studies.
He most often published in these fields:
- Artificial intelligence (42.51%)
- Electroencephalography (28.41%)
- Pattern recognition (27.97%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (42.51%)
- Pattern recognition (27.97%)
- Electroencephalography (28.41%)
In recent papers he was focusing on the following fields of study:
Bin Hu mainly investigates Artificial intelligence, Pattern recognition, Electroencephalography, Depression and Feature extraction.
His studies link Machine learning with Artificial intelligence.
His research on Pattern recognition focuses in particular on Support vector machine.
His studies deal with areas such as Classifier, Wearable computer, Functional connectivity, Benchmark and Biomarker as well as Electroencephalography.
His research investigates the connection between Depression and topics such as Audiology that intersect with issues in Resting state fMRI.
Bin Hu has researched Feature extraction in several fields, including Focus and Entropy.
Between 2019 and 2021, his most popular works were:
- Joint Computing and Caching in 5G-Envisioned Internet of Vehicles: A Deep Reinforcement Learning-Based Traffic Control System (41 citations)
- When Deep Reinforcement Learning Meets 5G-Enabled Vehicular Networks: A Distributed Offloading Framework for Traffic Big Data (35 citations)
- Intelligent Edge Computing in Internet of Vehicles: A Joint Computation Offloading and Caching Solution (27 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Operating system
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Electroencephalography, The Internet and Edge computing.
His Artificial intelligence research incorporates elements of Weighting and Graph.
His Pattern recognition study incorporates themes from Eye movement and Mood.
The concepts of his Electroencephalography study are interwoven with issues in Decision tree, Classifier, Deep learning and Convolutional neural network.
His research in The Internet intersects with topics in Network performance, Network delay and Co-occurrence.
Bin Hu combines subjects such as Wireless, Wireless network, Quality of experience and Computer network, Server with his study of Edge computing.
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