What is he best known for?
The fields of study he is best known for:
- Algorithm
- Computer network
- Programming language
His primary areas of study are Earliest deadline first scheduling, Combinatorics, Time complexity, Speedup and Scheduling.
His Earliest deadline first scheduling research focuses on subjects like Fixed-priority pre-emptive scheduling, which are linked to Mixed criticality.
As part of one scientific family, Alberto Marchetti-Spaccamela deals mainly with the area of Combinatorics, narrowing it down to issues related to the Discrete mathematics, and often Graph theory and Amortized analysis.
His Time complexity research incorporates themes from Upper and lower bounds, Graph, Approximation algorithm and Applied mathematics.
His work deals with themes such as Linear programming, Computation, Computational complexity theory and Polynomial, which intersect with Approximation algorithm.
His work in the fields of Applied mathematics, such as Minimax approximation algorithm, overlaps with other areas such as Quantum complexity theory.
His most cited work include:
- Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties (1159 citations)
- Complexity and Approximation (806 citations)
- Counting triangles in data streams (222 citations)
What are the main themes of his work throughout his whole career to date?
Alberto Marchetti-Spaccamela spends much of his time researching Mathematical optimization, Algorithm, Approximation algorithm, Scheduling and Combinatorics.
The concepts of his Mathematical optimization study are interwoven with issues in Routing and Network packet.
His study in Algorithm is interdisciplinary in nature, drawing from both Upper and lower bounds, Competitive analysis and Shortest path problem.
His Approximation algorithm study combines topics from a wide range of disciplines, such as Time complexity, Polynomial, Computational complexity theory and Job shop scheduling.
His work in Scheduling addresses subjects such as Multiprocessing, which are connected to disciplines such as Multiprocessor scheduling.
His research in Combinatorics intersects with topics in Discrete mathematics and Bounded function.
He most often published in these fields:
- Mathematical optimization (26.92%)
- Algorithm (24.52%)
- Approximation algorithm (24.52%)
What were the highlights of his more recent work (between 2012-2021)?
- Scheduling (19.23%)
- Parallel computing (10.58%)
- Approximation algorithm (24.52%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Scheduling, Parallel computing, Approximation algorithm, Mathematical optimization and Job shop scheduling.
The Metrical task system research Alberto Marchetti-Spaccamela does as part of his general Scheduling study is frequently linked to other disciplines of science, such as Fork, therefore creating a link between diverse domains of science.
His Parallel computing research is multidisciplinary, incorporating perspectives in Earliest deadline first scheduling, Multiprocessor scheduling and Fixed-priority pre-emptive scheduling.
His Approximation algorithm study results in a more complete grasp of Combinatorics.
Optimization problem is the focus of his Mathematical optimization research.
His Job shop scheduling research includes elements of Time complexity, Algorithm, Job scheduler and Set.
Between 2012 and 2021, his most popular works were:
- Feasibility Analysis in the Sporadic DAG Task Model (102 citations)
- Response-Time Analysis of Conditional DAG Tasks in Multiprocessor Systems (64 citations)
- Preemptive Uniprocessor Scheduling of Mixed-Criticality Sporadic Task Systems (51 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Computer network
- Programming language
Parallel computing, Scheduling, Earliest deadline first scheduling, Speedup and Biotechnology are his primary areas of study.
His Parallel computing research is multidisciplinary, incorporating elements of Software and Multiprocessor scheduling.
His Metrical task system study, which is part of a larger body of work in Scheduling, is frequently linked to Fork, bridging the gap between disciplines.
In Earliest deadline first scheduling, Alberto Marchetti-Spaccamela works on issues like Fixed-priority pre-emptive scheduling, which are connected to Deadline-monotonic scheduling.
His Deadline-monotonic scheduling research incorporates elements of Priority inversion, Mathematical optimization, Least slack time scheduling and Priority inheritance.
His Speedup study incorporates themes from Monotonic function, Online algorithm and Directed graph.
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