What is he best known for?
The fields of study he is best known for:
- Computer network
- Statistics
- The Internet
Nick Duffield spends much of his time researching Computer network, Network packet, Sampling, Real-time computing and Distributed computing.
His Computer network study integrates concerns from other disciplines, such as The Internet and Denial-of-service attack.
The Network packet study combines topics in areas such as Flow and Traffic generation model.
His Sampling research integrates issues from Estimator, Data mining, Selection and Entropy.
His Real-time computing research includes themes of Estimation theory, Range, Simulation, Packet loss and Measure.
His work carried out in the field of Distributed computing brings together such families of science as Routing and Internet traffic.
His most cited work include:
- A flexible model for resource management in virtual private networks (531 citations)
- Fast accurate computation of large-scale IP traffic matrices from link loads (499 citations)
- On the constancy of internet path properties (445 citations)
What are the main themes of his work throughout his whole career to date?
Nick Duffield focuses on Computer network, Network packet, Sampling, Real-time computing and Data mining.
His Computer network research is multidisciplinary, incorporating elements of The Internet and Distributed computing.
Nick Duffield has included themes like NetFlow, Network monitoring, Flow and Router in his Network packet study.
His work on Reservoir sampling is typically connected to Context as part of general Sampling study, connecting several disciplines of science.
His biological study spans a wide range of topics, including Service provider and Packet loss.
His work is dedicated to discovering how Data mining, Theoretical computer science are connected with Inference and other disciplines.
He most often published in these fields:
- Computer network (24.51%)
- Network packet (24.11%)
- Sampling (22.53%)
What were the highlights of his more recent work (between 2015-2021)?
- Sampling (22.53%)
- Artificial intelligence (6.72%)
- Graph (5.53%)
In recent papers he was focusing on the following fields of study:
Nick Duffield mostly deals with Sampling, Artificial intelligence, Graph, Graph and Algorithm.
The various areas that he examines in his Sampling study include Estimator and Pairwise comparison.
The concepts of his Estimator study are interwoven with issues in Martingale, Data mining and Reservoir sampling.
His studies deal with areas such as Theoretical computer science and Inference as well as Graph.
His Algorithm study incorporates themes from Sample, Biological network and Scalability.
Provisioning is a subfield of Computer network that Nick Duffield explores.
Between 2015 and 2021, his most popular works were:
- Graphlet decomposition: framework, algorithms, and applications (53 citations)
- On sampling from massive graph streams (51 citations)
- Variational Graph Recurrent Neural Networks (33 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Statistics
- The Internet
His primary scientific interests are in Theoretical computer science, Graph, Sampling, Algorithm and Inference.
His Theoretical computer science study combines topics from a wide range of disciplines, such as Recommender system, Representation, Graph embedding and Cluster analysis.
His research integrates issues of Projection, Connection, Graph neural networks, Similarity and Bayesian probability in his study of Sampling.
His work deals with themes such as Scalability and Biological network, which intersect with Algorithm.
His Inference research incorporates themes from Recurrent neural network, Random variable, Feature learning and Generative grammar, Generative model.
Estimator is closely attributed to STREAMS in his study.
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