What is he best known for?
The fields of study he is best known for:
- Computer network
- Telecommunications
- The Internet
Narayan B. Mandayam spends much of his time researching Computer network, Power control, Wireless, Nash equilibrium and Game theory.
His study in Computer network is interdisciplinary in nature, drawing from both Wireless network and The Internet.
His Power control research is multidisciplinary, incorporating elements of Code division multiple access, Throughput, Base station and Radio resource management.
His Wireless research incorporates elements of Key, Communication channel and Spoofing attack.
Narayan B. Mandayam has researched Nash equilibrium in several fields, including Signal-to-interference-plus-noise ratio, Quality of service, Pareto principle and Efficient energy use.
Narayan B. Mandayam combines subjects such as Multiuser detection, Outcome and Prospect theory with his study of Game theory.
His most cited work include:
- Efficient power control via pricing in wireless data networks (1254 citations)
- Power control for wireless data (633 citations)
- Radio-telepathy: extracting a secret key from an unauthenticated wireless channel (568 citations)
What are the main themes of his work throughout his whole career to date?
Narayan B. Mandayam mainly investigates Computer network, Communication channel, Wireless network, Wireless and Nash equilibrium.
The Computer network study combines topics in areas such as Cognitive radio, Relay, Throughput and Power control.
His biological study spans a wide range of topics, including Quality of service, Code division multiple access and Transmitter power output.
His Communication channel research includes elements of Transmitter, Electronic engineering and Interference.
His studies in Wireless integrate themes in fields like Transmission, Real-time computing and Authentication.
His Nash equilibrium research incorporates themes from Computer security, Prospect theory and Game theory.
He most often published in these fields:
- Computer network (41.64%)
- Communication channel (22.87%)
- Wireless network (18.48%)
What were the highlights of his more recent work (between 2015-2021)?
- Computer network (41.64%)
- Nash equilibrium (16.13%)
- Game theory (14.96%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Computer network, Nash equilibrium, Game theory, Prospect theory and Computer security.
The study incorporates disciplines such as Wireless, Transmission and Communication channel, Orthogonal frequency-division multiplexing in addition to Computer network.
His MIMO study, which is part of a larger body of work in Communication channel, is frequently linked to Context, bridging the gap between disciplines.
His Nash equilibrium study combines topics in areas such as Zipf's law, Pricing strategies, Evolutionarily stable strategy and Cache.
His research in Game theory intersects with topics in Replicator equation and Complete information.
His Prospect theory study incorporates themes from Stackelberg competition, Mathematical optimization, Smart grid and Expected utility hypothesis.
Between 2015 and 2021, his most popular works were:
- Joint Caching and Pricing Strategies for Popular Content in Information Centric Networks (73 citations)
- Cloud Storage Defense Against Advanced Persistent Threats: A Prospect Theoretic Study (61 citations)
- Toward a Consumer-Centric Grid: A Behavioral Perspective (61 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Telecommunications
- The Internet
His primary areas of study are Nash equilibrium, Game theory, Smart grid, Prospect theory and Computer security.
His Nash equilibrium study combines topics from a wide range of disciplines, such as Replicator equation, Pricing strategies, Computer network and Evolutionary game theory.
Narayan B. Mandayam has included themes like Channel access method, Throughput and Metric in his Computer network study.
The concepts of his Game theory study are interwoven with issues in The Internet, Stochastic game and Complete information.
His Smart grid research integrates issues from Best response, Microeconomics, Efficient energy use and Mathematical optimization.
His Mathematical optimization research is multidisciplinary, incorporating perspectives in Communication channel and Operations research.
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