What is he best known for?
The fields of study he is best known for:
- Algorithm
- Geometry
- Artificial intelligence
Franco P. Preparata focuses on Combinatorics, Discrete mathematics, Algorithm, Computational geometry and Convex hull.
His Combinatorics study combines topics from a wide range of disciplines, such as Space and Intersection, Line segment intersection.
His Algorithm study frequently draws connections between related disciplines such as Boundary.
His Computational geometry research is multidisciplinary, incorporating perspectives in Real RAM, Plane, Sweep line algorithm and Calculus.
His Calculus research incorporates themes from Bowyer–Watson algorithm and Closest pair of points problem.
Franco P. Preparata interconnects Radon's theorem, Convex polytope and Orthogonal convex hull in the investigation of issues within Convex hull.
His most cited work include:
- Computational Geometry: An Introduction (3147 citations)
- Computational geometry. an introduction (2424 citations)
- On the Connection Assignment Problem of Diagnosable Systems (1206 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Combinatorics, Algorithm, Discrete mathematics, Computation and Very-large-scale integration.
The Combinatorics study combines topics in areas such as Computational geometry, Point location and Convex hull.
His Computational geometry research integrates issues from Plane and Regular polygon.
His work on Theory of computation as part of general Algorithm study is frequently linked to Sequencing by hybridization, therefore connecting diverse disciplines of science.
His study in Discrete mathematics is interdisciplinary in nature, drawing from both Computational complexity theory and Linear code.
His biological study spans a wide range of topics, including Theoretical computer science, Chip, Parallel computing, Sorting and Integrated circuit.
He most often published in these fields:
- Combinatorics (34.96%)
- Algorithm (26.55%)
- Discrete mathematics (22.12%)
What were the highlights of his more recent work (between 2001-2013)?
- Algorithm (26.55%)
- Sequencing by hybridization (6.19%)
- Algorithmics (2.65%)
In recent papers he was focusing on the following fields of study:
Franco P. Preparata mainly focuses on Algorithm, Sequencing by hybridization, Algorithmics, DNA sequencing and Genetics.
His research in Algorithm intersects with topics in Position and Standard deviation.
His Algorithmics research incorporates elements of Theoretical computer science, Industrial engineering, Theory of computation, Library science and Computational geometry.
His Theoretical computer science research is multidisciplinary, relying on both Parameterized complexity, Cluster analysis, Binary search tree, Streaming algorithm and Spanning tree.
His study explores the link between Theory of computation and topics such as Artificial intelligence that cross with problems in Filter, Subsequence and Dynamic programming.
His Data point research includes elements of Time complexity and Roundness, Hyperboloid, Geometry.
Between 2001 and 2013, his most popular works were:
- Sequencing-by-Hybridization Revisited: The Analog-Spectrum Proposal (188 citations)
- Algorithms for Location Estimation Based on RSSI Sampling (66 citations)
- Accurate cylindricity evaluation with axis-estimation preprocessing (30 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Geometry
- Artificial intelligence
Franco P. Preparata mostly deals with Algorithm, Metrology, Mathematical optimization, Genetics and DNA microarray.
His work in the fields of Algorithm, such as Data point, intersects with other areas such as Sensor node.
He has researched Data point in several fields, including Time complexity, Roundness and Linearization.
The concepts of his Metrology study are interwoven with issues in Combinatorics, Geometry, Radius, Algebraic number and Space.
Franco P. Preparata has included themes like Cylinder, Hyperboloid and Markov systems in his Mathematical optimization study.
His DNA sequencing and DNA study, which is part of a larger body of work in Genetics, is frequently linked to Sequencing by hybridization, Important conclusion and De novo sequencing, bridging the gap between disciplines.
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