What is he best known for?
The fields of study he is best known for:
- Operating system
- Computer network
- The Internet
Gang Zhou mainly focuses on Wireless sensor network, Computer network, Real-time computing, Wireless and Efficient energy use.
His research integrates issues of Key distribution in wireless sensor networks, Topology control, Energy consumption, Transmission and Embedded system in his study of Wireless sensor network.
When carried out as part of a general Computer network research project, his work on Network packet and Packet loss is frequently linked to work in Jamming, therefore connecting diverse disciplines of study.
His Real-time computing study which covers Robustness that intersects with Human–computer interaction and Microphone.
His studies examine the connections between Wireless and genetics, as well as such issues in Testbed, with regards to White spaces, Frame and Routing protocol.
His Efficient energy use study incorporates themes from Wireless ad hoc network, Duty cycle, Wireless Application Protocol, Power management and Communications protocol.
His most cited work include:
- Impact of radio irregularity on wireless sensor networks (746 citations)
- ATPC: adaptive transmission power control for wireless sensor networks (532 citations)
- VigilNet: An integrated sensor network system for energy-efficient surveillance (455 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Wireless sensor network, Real-time computing, Computer network, Embedded system and Wireless.
His work deals with themes such as Distributed computing, Power control, Energy consumption, Key distribution in wireless sensor networks and Event, which intersect with Wireless sensor network.
In his research on the topic of Real-time computing, Packet loss is strongly related with Testbed.
The study incorporates disciplines such as Wireless network, Throughput and Communication channel in addition to Computer network.
Gang Zhou focuses mostly in the field of Embedded system, narrowing it down to topics relating to Accelerometer and, in certain cases, Authentication.
His studies in Wireless integrate themes in fields like Quality of service and Overhead.
He most often published in these fields:
- Wireless sensor network (37.41%)
- Real-time computing (29.93%)
- Computer network (29.25%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (11.56%)
- Accelerometer (9.52%)
- Convolutional neural network (3.40%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Accelerometer, Convolutional neural network, Gesture recognition and Computer vision.
His study focuses on the intersection of Artificial intelligence and fields such as Pattern recognition with connections in the field of Wireless sensor network.
His Accelerometer study combines topics in areas such as Variety and Feature extraction.
His work in Channel state information addresses subjects such as Signal processing, which are connected to disciplines such as Robustness, Activity recognition and Real-time computing.
His Speech recognition research integrates issues from Wireless and Network packet.
His research in Computer network intersects with topics in Wi-Fi, Throughput and Wireless access point.
Between 2017 and 2021, his most popular works were:
- WiFi Sensing with Channel State Information: A Survey (101 citations)
- SignFi: Sign Language Recognition Using WiFi (74 citations)
- Using Data Augmentation in Continuous Authentication on Smartphones (36 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- The Internet
Gang Zhou focuses on Accelerometer, Real-time computing, Authentication, Feature extraction and Convolutional neural network.
His biological study spans a wide range of topics, including Motion sensors and Physical medicine and rehabilitation.
His Real-time computing study integrates concerns from other disciplines, such as Software deployment, Android, Message authentication code, Mobile computing and Sensor fusion.
He usually deals with Authentication and limits it to topics linked to Word error rate and Information leakage, Data mining, Wireless sensor network, Login session and Classifier.
His Convolutional neural network research incorporates elements of Wireless, Speech recognition and Network packet.
The Pattern recognition study combines topics in areas such as Mobile device and Artificial intelligence.
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