What is she best known for?
The fields of study she is best known for:
- Algorithm
- Computer network
- Programming language
Her primary scientific interests are in Competitive analysis, Online algorithm, Algorithm, Mathematical optimization and Parallel computing.
Her studies deal with areas such as Algorithm complexity, Binary search tree, Binary tree, Data structure and Data compression as well as Competitive analysis.
The various areas that Susanne Albers examines in her Online algorithm study include Self-organizing list, List update problem, Data science and Operations research.
Her work is dedicated to discovering how Algorithm, Paging are connected with Pairwise comparison, Theory of computation and Locality of reference and other disciplines.
Susanne Albers has researched Mathematical optimization in several fields, including Time complexity, Computational complexity theory, Randomized algorithm, Scheduling and Packet loss.
Her Parallel computing research includes elements of Multiprocessor scheduling and Approximation algorithm.
Her most cited work include:
- Energy-efficient algorithms (355 citations)
- Exploring Unknown Environments (235 citations)
- Online algorithms: a survey (203 citations)
What are the main themes of her work throughout her whole career to date?
Her primary areas of study are Competitive analysis, Online algorithm, Algorithm, Mathematical optimization and Scheduling.
Her Competitive analysis study combines topics in areas such as Theoretical computer science, Deterministic algorithm, Paging, List update problem and Randomized algorithm.
Her Online algorithm research incorporates elements of Discrete mathematics, Network packet and Cache.
Her work in the fields of Algorithm, such as Time complexity and Theory of computation, overlaps with other areas such as Sequence, Line and Clock rate.
Her Time complexity study combines topics from a wide range of disciplines, such as Linear programming and Parallel computing.
As a member of one scientific family, Susanne Albers mostly works in the field of Scheduling, focusing on Approximation algorithm and, on occasion, Optimization problem, Packing algorithm and Bin.
She most often published in these fields:
- Competitive analysis (49.68%)
- Online algorithm (43.31%)
- Algorithm (26.11%)
What were the highlights of her more recent work (between 2017-2021)?
- Competitive analysis (49.68%)
- Online algorithm (43.31%)
- Mathematical optimization (24.84%)
In recent papers she was focusing on the following fields of study:
Her scientific interests lie mostly in Competitive analysis, Online algorithm, Mathematical optimization, Job shop scheduling and Scheduling.
As part of her studies on Competitive analysis, Susanne Albers often connects relevant areas like Deterministic algorithm.
Susanne Albers combines subjects such as Matching, Theoretical computer science, Theory of computation and Combinatorics with her study of Online algorithm.
Her study in Matching is interdisciplinary in nature, drawing from both Time complexity, Optimization problem and Server.
As part of one scientific family, Susanne Albers deals mainly with the area of Mathematical optimization, narrowing it down to issues related to the Randomized algorithm, and often Knapsack problem, Generalized assignment problem and Combinatorial optimization.
Her study looks at the relationship between Job shop scheduling and fields such as Minification, as well as how they intersect with chemical problems.
Between 2017 and 2021, her most popular works were:
- Improved Online Algorithms for Knapsack and GAP in the Random Order Model (12 citations)
- Optimal Algorithms for Right-Sizing Data Centers (8 citations)
- New Results for the k-Secretary Problem (7 citations)
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