What is he best known for?
The fields of study he is best known for:
- Computer network
- Artificial intelligence
- Statistics
His main research concerns Wireless, Base station, Computer network, Wireless network and Distributed computing.
His Wireless research incorporates elements of Real-time computing, Telecommunications link, Virtual reality and Key.
The Base station study combines topics in areas such as Quality of service, Cellular network and Spectral efficiency.
His study focuses on the intersection of Computer network and fields such as Edge device with connections in the field of Dissemination, CPU cache and Transfer of learning.
His Wireless network study integrates concerns from other disciplines, such as Network planning and design and Network packet.
His Distributed computing research is multidisciplinary, incorporating perspectives in Latency, Resource allocation and Server, Mobile edge computing.
His most cited work include:
- Living on the Edge: The Role of Proactive Caching in 5G Wireless Networks (940 citations)
- Unmanned Aerial Vehicle With Underlaid Device-to-Device Communications: Performance and Tradeoffs (784 citations)
- A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems (626 citations)
What are the main themes of his work throughout his whole career to date?
Mehdi Bennis spends much of his time researching Computer network, Wireless, Base station, Distributed computing and Wireless network.
In most of his Computer network studies, his work intersects topics such as Throughput.
His Wireless study combines topics in areas such as Resource allocation, Communication channel, Real-time computing, Scheduling and Virtual reality.
His study explores the link between Base station and topics such as Cellular network that cross with problems in Spectral efficiency.
Markov decision process is closely connected to Reinforcement learning in his research, which is encompassed under the umbrella topic of Distributed computing.
Many of his studies on Wireless network involve topics that are commonly interrelated, such as Edge device.
He most often published in these fields:
- Computer network (37.17%)
- Wireless (33.27%)
- Base station (31.23%)
What were the highlights of his more recent work (between 2019-2021)?
- Wireless (33.27%)
- Distributed computing (22.86%)
- Reinforcement learning (10.97%)
In recent papers he was focusing on the following fields of study:
Mehdi Bennis mainly investigates Wireless, Distributed computing, Reinforcement learning, Real-time computing and Scheduling.
His work deals with themes such as Cellular network, Computer network, Communication channel and Information privacy, which intersect with Wireless.
Mehdi Bennis undertakes interdisciplinary study in the fields of Computer network and Efficient energy use through his research.
Mehdi Bennis combines subjects such as Artificial neural network, Wireless network, Enhanced Data Rates for GSM Evolution and Server with his study of Distributed computing.
While the research belongs to areas of Wireless network, Mehdi Bennis spends his time largely on the problem of Base station, intersecting his research to questions surrounding Cache.
His biological study spans a wide range of topics, including Resource allocation, Model predictive control, Fading and Stochastic optimization, Mathematical optimization.
Between 2019 and 2021, his most popular works were:
- A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems (544 citations)
- A Speculative Study on 6G (134 citations)
- Blockchained On-Device Federated Learning (114 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Artificial intelligence
- Statistics
Mehdi Bennis mainly focuses on Wireless, Distributed computing, Scheduling, Real-time computing and Artificial neural network.
His Wireless research is multidisciplinary, incorporating elements of Transmission delay, Communication channel, Virtual reality and Base station.
Mehdi Bennis has researched Virtual reality in several fields, including Cellular network and Reliability.
His research integrates issues of Unicast, Multi-user and Telecommunications link in his study of Base station.
His Distributed computing study integrates concerns from other disciplines, such as Network dynamics, Enhanced Data Rates for GSM Evolution, Deep learning, Mobile device and Reinforcement learning.
His Computer network study combines topics from a wide range of disciplines, such as Partition and Slicing.
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