What is he best known for?
The fields of study he is best known for:
- Computer network
- Operating system
- The Internet
Lionel M. Ni mainly focuses on Computer network, Distributed computing, Real-time computing, Mobile computing and Network topology.
His studies deal with areas such as Scalability and The Internet as well as Computer network.
The concepts of his Distributed computing study are interwoven with issues in Static routing, Multipath routing, Destination-Sequenced Distance Vector routing and Dynamic Source Routing.
His Real-time computing research includes themes of Software deployment, Wireless sensor network, Diversity scheme, Embedded system and Channel state information.
His Mobile computing research includes elements of Radio-frequency identification, Wireless ad hoc network, Vehicular ad hoc network, Mobile radio and Mobile device.
His Network topology research is multidisciplinary, incorporating perspectives in Distributed algorithm, Overlay network, Node and Topology.
His most cited work include:
- LANDMARC: indoor location sensing using active RFID (1736 citations)
- A survey of wormhole routing techniques in direct networks (1289 citations)
- The turn model for adaptive routing (866 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Computer network, Distributed computing, Wireless sensor network, Real-time computing and Scalability.
The various areas that he examines in his Computer network study include Wireless, Wireless network and Communication channel.
His research in Distributed computing intersects with topics in Network topology, Static routing, Overlay network and Dynamic Source Routing.
His work carried out in the field of Network topology brings together such families of science as Routing and Topology.
His Wireless sensor network study incorporates themes from Sensor node, Key distribution in wireless sensor networks, Topology control, Energy consumption and Efficient energy use.
His biological study spans a wide range of topics, including Transmitter, Multipath propagation and Embedded system.
He most often published in these fields:
- Computer network (33.14%)
- Distributed computing (26.23%)
- Wireless sensor network (16.37%)
What were the highlights of his more recent work (between 2013-2021)?
- Artificial intelligence (6.11%)
- Real-time computing (13.41%)
- Computer network (33.14%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Real-time computing, Computer network, Machine learning and Wireless.
His Real-time computing research incorporates themes from Wireless sensor network, Simulation, Embedded system, Transmitter and Mobile computing.
His Wireless sensor network research is multidisciplinary, relying on both Sensor node, Efficient energy use and Distributed computing.
His Distributed algorithm study, which is part of a larger body of work in Distributed computing, is frequently linked to Rationality, bridging the gap between disciplines.
His Computer network research integrates issues from Multi-user MIMO, Transmission, Constant false alarm rate, Wireless network and Vehicular ad hoc network.
He has included themes like Node and Multipath propagation, Communication channel in his Wireless study.
Between 2013 and 2021, his most popular works were:
- WiFall: Device-Free Fall Detection by Wireless Networks (327 citations)
- TRAC: Truthful Auction for Location-Aware Collaborative Sensing in Mobile Crowdsourcing (280 citations)
- Generalizing from a Few Examples: A Survey on Few-shot Learning (197 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Operating system
- The Internet
Lionel M. Ni mainly investigates Wireless, Real-time computing, Computer network, Artificial intelligence and Machine learning.
His Wireless research incorporates elements of Transmitter, Multipath propagation and Simulation.
His Real-time computing research is multidisciplinary, incorporating elements of Process, Wireless sensor network, Preprocessor, Wiener filter and Embedded system.
His research on Process also deals with topics like
- Key, which have a strong connection to Human–computer interaction,
- Software and related Distributed computing.
His studies in Computer network integrate themes in fields like Constant false alarm rate, Precoding, Wireless network, Vehicular ad hoc network and Software-defined radio.
In the field of Artificial intelligence, his study on Categorization, Taxonomy and Data set overlaps with subjects such as Point.
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