What is he best known for?
The fields of study he is best known for:
- Computer network
- Statistics
- Algorithm
Demosthenis Teneketzis mostly deals with Mathematical optimization, Distributed computing, Algorithm, Markov process and Identification.
His work in the fields of Mathematical optimization, such as Optimization problem, intersects with other areas such as Property.
His Distributed computing study also includes
- Correctness that connect with fields like State, Protocol and Decision rule,
- Automaton which connect with Data mining.
His Algorithm research incorporates themes from Sufficient statistic, Conditional probability distribution and Nonlinear system.
The various areas that Demosthenis Teneketzis examines in his Markov process study include Dynamic programming, Stochastic control, Markov chain, Communications system and Coding.
His research on Identification also deals with topics like
- Reliability engineering which intersects with area such as Complex system,
- Unobservable which connect with Discrete system and Discrete event dynamic system.
His most cited work include:
- Diagnosability of discrete-event systems (1333 citations)
- Failure diagnosis using discrete-event models (656 citations)
- Coordinated Decentralized Protocols for Failure Diagnosisof Discrete Event Systems (400 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Mathematical optimization, Computer network, Markov process, Markov chain and Nash equilibrium.
His Mathematical optimization study integrates concerns from other disciplines, such as Queue, Scheduling and Queueing theory.
Demosthenis Teneketzis works mostly in the field of Computer network, limiting it down to topics relating to Wireless ad hoc network and, in certain cases, Wireless network.
His studies deal with areas such as Algorithm, Decoding methods, Distortion and Communications system as well as Markov chain.
His study focuses on the intersection of Decoding methods and fields such as Encoding with connections in the field of Theoretical computer science.
Optimal control is a subfield of Control theory that he explores.
He most often published in these fields:
- Mathematical optimization (40.69%)
- Computer network (12.99%)
- Markov process (12.12%)
What were the highlights of his more recent work (between 2011-2021)?
- Mathematical optimization (40.69%)
- Mechanism design (6.49%)
- Nash equilibrium (9.09%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Mathematical optimization, Mechanism design, Nash equilibrium, Microeconomics and Computer network.
His Mathematical optimization research includes elements of Partially observable Markov decision process, Scheduling, Markov process and Markov chain.
His Markov process study also includes fields such as
- Sequential game which intersects with area such as Bayesian probability and Best response,
- Information asymmetry that intertwine with fields like Solution concept, State, Theoretical computer science and Management science.
His work in Nash equilibrium covers topics such as Public good which are related to areas like Resource allocation, Provisioning, Telecommunications service and Telecommunications network.
Demosthenis Teneketzis works mostly in the field of Computer network, limiting it down to topics relating to Game theory and, in certain cases, Key, as a part of the same area of interest.
His biological study deals with issues like Stochastic control, which deal with fields such as Observability.
Between 2011 and 2021, his most popular works were:
- Decentralized Stochastic Control with Partial History Sharing: A Common Information Approach (194 citations)
- Optimal Strategies for Communication and Remote Estimation With an Energy Harvesting Sensor (144 citations)
- Optimal Defense Policies for Partially Observable Spreading Processes on Bayesian Attack Graphs (47 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Statistics
- Artificial intelligence
Demosthenis Teneketzis mainly focuses on Mathematical optimization, Markov process, Mechanism design, Partially observable Markov decision process and Nash equilibrium.
He studies Dynamic programming which is a part of Mathematical optimization.
Demosthenis Teneketzis has included themes like Control theory, Observability and Supervisory control in his Dynamic programming study.
His Markov process research is multidisciplinary, incorporating perspectives in Backward induction, Gittins index, Information asymmetry, Markov chain and Sequential game.
His research in Partially observable Markov decision process intersects with topics in Computer security, Exploit, Stochastic control, Cognitive radio and Scheduling.
The study incorporates disciplines such as Game theory, Telecommunications service and Public good in addition to Nash equilibrium.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
