What is he best known for?
The fields of study he is best known for:
- Computer network
- Statistics
- Artificial intelligence
Qing Zhao mainly focuses on Computer network, Communication channel, Cognitive radio, Markov process and Throughput.
His Computer network research incorporates elements of Wireless, Wireless ad hoc network, Physical layer and Wireless network.
The study incorporates disciplines such as Estimation theory and Robustness in addition to Communication channel.
His studies deal with areas such as Spectrum, Data science and Taxonomy as well as Cognitive radio.
His research integrates issues of Upper and lower bounds, Decision theory and Mathematical optimization in his study of Markov process.
He has researched Throughput in several fields, including False alarm, Distributed computing, Markov chain and Access control.
His most cited work include:
- A Survey of Dynamic Spectrum Access (2424 citations)
- Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework (1544 citations)
- On the lifetime of wireless sensor networks (429 citations)
What are the main themes of his work throughout his whole career to date?
Qing Zhao focuses on Mathematical optimization, Computer network, Communication channel, Cognitive radio and Regret.
His Mathematical optimization research includes elements of Stochastic process, Anomaly detection, Markov process and Upper and lower bounds.
His work deals with themes such as Wireless ad hoc network, Transmission, Distributed computing and Physical layer, which intersect with Computer network.
His research investigates the link between Communication channel and topics such as Wireless that cross with problems in Frequency allocation.
His work in Cognitive radio covers topics such as Throughput which are related to areas like Queueing theory.
His work in the fields of Multi-armed bandit overlaps with other areas such as Order.
He most often published in these fields:
- Mathematical optimization (38.08%)
- Computer network (26.92%)
- Communication channel (25.38%)
What were the highlights of his more recent work (between 2016-2021)?
- Mathematical optimization (38.08%)
- Regret (19.62%)
- Anomaly detection (8.85%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Mathematical optimization, Regret, Anomaly detection, Asymptotically optimal algorithm and Random walk.
His research in Mathematical optimization intersects with topics in Adversarial system, Partially observable Markov decision process, Cognitive radio and Reduction.
His research investigates the connection between Cognitive radio and topics such as Test that intersect with issues in Minimax.
His Regret research is multidisciplinary, incorporating perspectives in Mathematical economics, Upper and lower bounds, Sublinear function and Time horizon.
His biological study spans a wide range of topics, including Sequential analysis, Inference and Search algorithm.
He combines subjects such as Stochastic process, Tree structure and Data stream mining with his study of Random walk.
Between 2016 and 2021, his most popular works were:
- Active Anomaly Detection in Heterogeneous Processes (32 citations)
- Algorithmic Bidding for Virtual Trading in Electricity Markets (14 citations)
- Multi-armed Bandits: Theory and Applications to Online Learning in Networks (12 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Statistics
- Artificial intelligence
Anomaly detection, Mathematical optimization, Asymptotically optimal algorithm, Algorithm and Linear search are his primary areas of study.
The concepts of his Anomaly detection study are interwoven with issues in Regret and Search algorithm.
His research integrates issues of Cognitive radio, Sequential analysis, Partially observable Markov decision process and Markov process in his study of Mathematical optimization.
The various areas that Qing Zhao examines in his Cognitive radio study include Test, Test plan, Minimax, Sampling and Group testing.
His Partially observable Markov decision process study combines topics from a wide range of disciplines, such as Resource allocation, State, Selection and Expected utility hypothesis.
Within one scientific family, Qing Zhao focuses on topics pertaining to Random walk under Algorithm, and may sometimes address concerns connected to Expected value and Combinatorics.
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