What is he best known for?
The fields of study he is best known for:
- Computer network
- Artificial intelligence
- Operating system
Erol Gelenbe mainly focuses on Computer network, Artificial intelligence, Artificial neural network, Queueing theory and Distributed computing.
His Computer network and Network packet, Quality of service, Routing, Link-state routing protocol and Adaptive quality of service multi-hop routing investigations all form part of his Computer network research activities.
His Artificial intelligence research integrates issues from Topology, Computer vision and Pattern recognition.
His Artificial neural network research incorporates elements of Feed forward, Algorithm and Random graph.
His Queueing theory research includes elements of Queue and Real-time computing.
His Distributed computing research focuses on Routing protocol and how it relates to Reliability.
His most cited work include:
- A survey of autonomic communications (566 citations)
- Energy-Efficient Cloud Computing (543 citations)
- Random neural networks with negative and positive signals and product form solution (498 citations)
What are the main themes of his work throughout his whole career to date?
Erol Gelenbe focuses on Computer network, Quality of service, Artificial intelligence, Distributed computing and Network packet.
His work in Queueing theory, Node, Wireless sensor network, Routing protocol and Queue is related to Computer network.
His research is interdisciplinary, bridging the disciplines of Mathematical optimization and Queueing theory.
His study looks at the relationship between Quality of service and topics such as Computer security, which overlap with Mobile device.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Computer vision.
He combines subjects such as Energy, Real-time computing and Transmission with his study of Network packet.
He most often published in these fields:
- Computer network (34.26%)
- Quality of service (17.94%)
- Artificial intelligence (16.48%)
What were the highlights of his more recent work (between 2013-2021)?
- Computer network (34.26%)
- Quality of service (17.94%)
- Network packet (15.33%)
In recent papers he was focusing on the following fields of study:
Erol Gelenbe mainly investigates Computer network, Quality of service, Network packet, Random neural network and Artificial intelligence.
His study looks at the relationship between Computer network and fields such as Wireless, as well as how they intersect with chemical problems.
His studies in Quality of service integrate themes in fields like Routing, Distributed computing, The Internet, Cloud computing and Reinforcement learning.
His Network packet research incorporates themes from Energy harvesting, Energy, Real-time computing, Mathematical optimization and Energy storage.
In his study, Relevance is strongly linked to Search engine, which falls under the umbrella field of Random neural network.
His Artificial intelligence study focuses mostly on Deep learning and Artificial neural network.
Between 2013 and 2021, his most popular works were:
- The impact of information technology on energy consumption and carbon emissions (122 citations)
- A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade (81 citations)
- Adaptive Dispatching of Tasks in the Cloud (81 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Operating system
- Artificial intelligence
His primary areas of investigation include Computer network, Quality of service, Network packet, Distributed computing and Energy harvesting.
Erol Gelenbe focuses mostly in the field of Computer network, narrowing it down to topics relating to The Internet and, in certain cases, Computer security, Layered queueing network and Queue.
His Quality of service study incorporates themes from Energy consumption, Routing, Cognitive network and Software-defined networking.
The study incorporates disciplines such as Random neural network, Artificial neural network, Deep learning, Artificial intelligence and Energy in addition to Network packet.
His Energy study integrates concerns from other disciplines, such as Queueing theory, Product-form solution and Energy storage.
His Distributed computing research is multidisciplinary, incorporating elements of Node, Cloud computing, Server, Routing protocol and Reinforcement learning.
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