What is he best known for?
The fields of study he is best known for:
- Computer network
- Operating system
- The Internet
Minglu Li focuses on Computer network, Real-time computing, Wireless sensor network, Vehicular ad hoc network and Simulation.
His work is dedicated to discovering how Computer network, Wireless ad hoc network are connected with Mobile ad hoc network and other disciplines.
His Real-time computing research includes themes of Key, Global Positioning System and Floating car data.
His research in Wireless sensor network intersects with topics in Sensor node, Wireless network, Scheduling and Distributed computing.
In Vehicular ad hoc network, Minglu Li works on issues like Mobile radio, which are connected to Probability distribution, End-to-end delay and Exponential distribution.
Minglu Li has researched Simulation in several fields, including Object, Sample and Accelerometer.
His most cited work include:
- Recognizing Exponential Inter-Contact Time in VANETs (214 citations)
- Target-Oriented Scheduling in Directional Sensor Networks (197 citations)
- Performance Evaluation of Vehicle-Based Mobile Sensor Networks for Traffic Monitoring (143 citations)
What are the main themes of his work throughout his whole career to date?
Minglu Li spends much of his time researching Distributed computing, Computer network, Grid, Grid computing and Wireless sensor network.
His study looks at the relationship between Distributed computing and topics such as Cloud computing, which overlap with Virtual machine.
His Computer network study incorporates themes from Wireless, Wireless ad hoc network, Vehicular ad hoc network and Wireless network.
His work deals with themes such as Mobile ad hoc network and Mobility model, which intersect with Wireless ad hoc network.
He combines subjects such as Semantic grid and Workflow technology, Workflow engine, Workflow, Workflow management system with his study of Grid computing.
The Wireless sensor network study combines topics in areas such as Data mining, Sensor node, Key distribution in wireless sensor networks, Real-time computing and Sensor array.
He most often published in these fields:
- Distributed computing (30.00%)
- Computer network (27.95%)
- Grid (20.23%)
What were the highlights of his more recent work (between 2017-2021)?
- Computer network (27.95%)
- Artificial intelligence (7.27%)
- Real-time computing (10.68%)
In recent papers he was focusing on the following fields of study:
His main research concerns Computer network, Artificial intelligence, Real-time computing, Wireless and Mobile device.
His study in Computer network is interdisciplinary in nature, drawing from both Scheme and Analytics.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Construct, Machine learning and Computer vision.
In his research, Minglu Li performs multidisciplinary study on Real-time computing and Bandwidth.
Minglu Li studied Wireless and Antenna that intersect with Wireless power transfer, Topology and Wireless sensor network.
In his research on the topic of Stability, Distributed computing is strongly related with Publication.
Between 2017 and 2021, his most popular works were:
- Characterizing Urban Vehicle-to-Vehicle Communications for Reliable Safety Applications (57 citations)
- A Double Auction Mechanism to Bridge Users’ Task Requirements and Providers’ Resources in Two-Sided Cloud Markets (30 citations)
- Lip Reading-Based User Authentication Through Acoustic Sensing on Smartphones (27 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- The Internet
Mobile device, Computer network, Software deployment, Speech recognition and Human–computer interaction are his primary areas of study.
His biological study spans a wide range of topics, including Virtual machine, Biometrics, Workload, Live migration and Cloud computing.
His work carried out in the field of Computer network brings together such families of science as Analytics and Duration.
Minglu Li has included themes like CPU cache, Cache, Statistics, Key and Scheme in his Software deployment study.
The Speech recognition study which covers Replay attack that intersects with Deep learning, Artificial intelligence, Identifier and Feature extraction.
By researching both Bandwidth and Real-time computing, he produces research that crosses academic boundaries.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
