What is he best known for?
The fields of study he is best known for:
- Computer network
- Statistics
- Telecommunications
Mounir Ghogho mostly deals with Algorithm, Communication channel, Estimator, Estimation theory and Fading.
His Algorithm research is multidisciplinary, incorporating perspectives in Antenna array, Speech recognition, Mean squared error, Bit error rate and Signal processing.
The concepts of his Communication channel study are interwoven with issues in Computer network, Artificial noise and Synchronization.
His Computer network study combines topics from a wide range of disciplines, such as Artificial neural network, Artificial intelligence, Channel state information and Rayleigh fading.
His studies in Estimator integrate themes in fields like Electronic engineering and Identifiability.
The study incorporates disciplines such as Throughput and Detector in addition to Fading.
His most cited work include:
- Deep learning approach for Network Intrusion Detection in Software Defined Networking (264 citations)
- Channel estimation and symbol detection for block transmission using data-dependent superimposed training (159 citations)
- Secure Communication via Sending Artificial Noise by the Receiver: Outage Secrecy Capacity/Region Analysis (125 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Algorithm, Communication channel, Computer network, Fading and Electronic engineering.
His study in Algorithm is interdisciplinary in nature, drawing from both Control theory, Signal-to-noise ratio, Statistics and Orthogonal frequency-division multiplexing, Frequency offset.
His Communication channel study incorporates themes from Wireless, Real-time computing and Synchronization.
His Computer network research is multidisciplinary, incorporating elements of MIMO, Efficient energy use and Throughput.
His work carried out in the field of Fading brings together such families of science as Relay and Topology.
He has researched Electronic engineering in several fields, including Transmission and Energy.
He most often published in these fields:
- Algorithm (31.34%)
- Communication channel (27.92%)
- Computer network (21.37%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (8.26%)
- Wireless (13.11%)
- Wireless sensor network (9.97%)
In recent papers he was focusing on the following fields of study:
Mounir Ghogho mainly investigates Artificial intelligence, Wireless, Wireless sensor network, Communication channel and Algorithm.
The various areas that he examines in his Artificial intelligence study include Machine learning and Computer vision.
His work deals with themes such as Path, Real-time computing, Mobile robot and Fading, which intersect with Wireless.
To a larger extent, Mounir Ghogho studies Computer network with the aim of understanding Wireless sensor network.
In general Communication channel study, his work on Spectral efficiency often relates to the realm of Coverage probability, thereby connecting several areas of interest.
As part of his studies on Algorithm, Mounir Ghogho often connects relevant areas like Additive white Gaussian noise.
Between 2017 and 2021, his most popular works were:
- Deep Recurrent Neural Network for Intrusion Detection in SDN-based Networks (65 citations)
- Performance Analysis of UAV Enabled Disaster Recovery Networks: A Stochastic Geometric Framework Based on Cluster Processes (51 citations)
- Who is behind the wheel? Driver identification and fingerprinting (32 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Statistics
- Telecommunications
The scientist’s investigation covers issues in Artificial intelligence, Flexibility, Algorithm, Wireless sensor network and Computer network.
Mounir Ghogho combines subjects such as Distributed computing, Reliability engineering and Electricity with his study of Flexibility.
As a part of the same scientific study, Mounir Ghogho usually deals with the Distributed computing, concentrating on Anomaly detection and frequently concerns with The Internet.
The Algorithm study combines topics in areas such as Wireless, Fading, Relay, Fusion center and Mobile robot.
His research in Wireless sensor network intersects with topics in Key distribution in wireless sensor networks, Transmission, Reliability and Statistical hypothesis testing.
His research integrates issues of Recurrent neural network, Intrusion detection system and Metric in his study of Computer network.
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