What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Computer network
Zheng Yang mainly focuses on Real-time computing, Wireless, Wireless sensor network, Computer network and Telecommunications.
Zheng Yang has included themes like Scalability, Physical layer, Channel state information, Communication channel and Embedded system in his Real-time computing study.
The study incorporates disciplines such as Leverage and Mobile computing in addition to Wireless.
His Wireless sensor network study combines topics from a wide range of disciplines, such as Key distribution in wireless sensor networks, Ranging and Mobile radio.
His Computer network study integrates concerns from other disciplines, such as Throughput and Distributed computing.
In his research on the topic of Telecommunications, Mobility model, Accelerometer, Inertial measurement unit and Radio frequency is strongly related with Software deployment.
His most cited work include:
- From RSSI to CSI: Indoor localization via channel response (624 citations)
- Locating in fingerprint space: wireless indoor localization with little human intervention (592 citations)
- WILL: Wireless Indoor Localization without Site Survey (321 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Real-time computing, Wireless, Wireless sensor network, Computer network and Artificial intelligence.
Zheng Yang combines subjects such as Multilateration, Fingerprint, Embedded system, Key and Mobile device with his study of Real-time computing.
His Wireless research is multidisciplinary, relying on both Software deployment, Mobile computing and Leverage.
The various areas that Zheng Yang examines in his Wireless sensor network study include Distributed computing, Wireless ad hoc network, Key distribution in wireless sensor networks, Ranging and Efficient energy use.
His Computer network study incorporates themes from Multipath propagation and Physical layer.
His research integrates issues of Machine learning and Computer vision in his study of Artificial intelligence.
He most often published in these fields:
- Real-time computing (34.86%)
- Wireless (29.71%)
- Wireless sensor network (25.14%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (16.57%)
- Wireless (29.71%)
- Real-time computing (34.86%)
In recent papers he was focusing on the following fields of study:
Zheng Yang mainly focuses on Artificial intelligence, Wireless, Real-time computing, Key and Crowdsourcing.
The Artificial intelligence study combines topics in areas such as Machine learning and Computer vision.
His Wireless research is mostly focused on the topic Channel state information.
His study in Real-time computing is interdisciplinary in nature, drawing from both Wireless sensor network and Microphone.
His Key study also includes
- Interoperability which intersects with area such as Computer network,
- Leverage, which have a strong connection to Tracking, Range and Joint,
- Motion, Mobility model, Base station and Mobile phone most often made with reference to The Internet.
His Crowdsourcing research includes elements of Distributed computing and Human–computer interaction.
Between 2017 and 2021, his most popular works were:
- Widar2.0: Passive Human Tracking with a Single Wi-Fi Link (92 citations)
- Automatic Radio Map Adaptation for Indoor Localization Using Smartphones (75 citations)
- Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi (56 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Computer network
His primary scientific interests are in Real-time computing, Wireless, Artificial intelligence, Key and Mobile device.
His Real-time computing research is multidisciplinary, incorporating elements of Wearable computer and Microphone.
His studies in Wireless integrate themes in fields like Antenna array, Rotation, Inertial measurement unit, Mobile computing and Sensor fusion.
His work on Recurrent neural network, Deep learning and Gesture as part of general Artificial intelligence research is often related to Domain, thus linking different fields of science.
His biological study spans a wide range of topics, including Computer network, Joint and Interoperability.
His Mobile device research incorporates elements of Crowdsourcing and Optimization problem.
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