What is she best known for?
The fields of study she is best known for:
- Operating system
- Algorithm
- Computer network
Her main research concerns Mathematical optimization, Integer programming, Algorithm, Pre-play attack and Theoretical computer science.
Her Mathematical optimization study which covers Fair-share scheduling that intersects with Flow shop scheduling.
Cynthia A. Phillips has researched Integer programming in several fields, including Facility location problem and Fraction.
Her Algorithm study frequently draws connections between adjacent fields such as Water supply.
The various areas that Cynthia A. Phillips examines in her Theoretical computer science study include Graph theory, Computer network, Computer virus and Corollary.
Her Graph research is multidisciplinary, incorporating elements of Intrusion detection system, Subset and superset and Systems analysis.
Her most cited work include:
- A graph-based system for network-vulnerability analysis (654 citations)
- The battle of the water sensor networks (BWSN): A design challenge for engineers and algorithms (422 citations)
- Computer-attack graph generation tool (302 citations)
What are the main themes of her work throughout her whole career to date?
Her primary areas of study are Mathematical optimization, Theoretical computer science, Distributed computing, Approximation algorithm and Integer programming.
Cynthia A. Phillips studied Mathematical optimization and Integer that intersect with Set.
The concepts of her Theoretical computer science study are interwoven with issues in Graph theory, Graph and Graph.
Graph is connected with Timing attack and Pre-play attack in her research.
Her Approximation algorithm research incorporates themes from Linear programming, Scheduling and Discrete mathematics, Time complexity.
The Integer programming study combines topics in areas such as Heuristics and Massively parallel.
She most often published in these fields:
- Mathematical optimization (17.86%)
- Theoretical computer science (16.43%)
- Distributed computing (14.29%)
What were the highlights of her more recent work (between 2017-2021)?
- Distributed computing (14.29%)
- Algorithm (9.29%)
- Theoretical computer science (16.43%)
In recent papers she was focusing on the following fields of study:
Her primary scientific interests are in Distributed computing, Algorithm, Theoretical computer science, Graph and Neuromorphic engineering.
Her study looks at the relationship between Distributed computing and fields such as Host, as well as how they intersect with chemical problems.
Her research in Algorithm intersects with topics in Vertex, Graph, Scalability and Auxiliary memory.
Her work in Theoretical computer science tackles topics such as Algorithmics which are related to areas like Data mining.
Graph is closely attributed to Dynamic programming in her research.
Her Neuromorphic engineering study incorporates themes from Computation, Leverage, Models of neural computation and Computer engineering.
Between 2017 and 2021, her most popular works were:
- Path Finding for Maximum Value of Information in Multi-Modal Underwater Wireless Sensor Networks (40 citations)
- Constant-Depth and Subcubic-Size Threshold Circuits for Matrix Multiplication (9 citations)
- Scalable generation of graphs for benchmarking HPC community-detection algorithms (9 citations)
In her most recent research, the most cited papers focused on:
- Operating system
- Algorithm
- Computer network
Her primary areas of investigation include Distributed computing, Neuromorphic engineering, Artificial neural network, Human–computer interaction and Dynamic programming.
Her Distributed computing research is multidisciplinary, incorporating elements of Cache, High Bandwidth Memory, Approximation algorithm, Paging and Scheduling.
Her Neuromorphic engineering research incorporates themes from Logic gate, Matrix multiplication, Arithmetic, Computation and Models of neural computation.
Cynthia A. Phillips incorporates Artificial neural network and Constant in her studies.
Her study in Graph extends to Dynamic programming with its themes.
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