What is he best known for?
The fields of study he is best known for:
- Operating system
- Programming language
- Algorithm
Christian Bischof mostly deals with Algorithm, Automatic differentiation, QR decomposition, Parallel computing and Factorization.
His Algorithm study also includes fields such as
- Matrix which connect with Discrete mathematics, Subspace topology and Linear subspace,
- RRQR factorization together with Sparse matrix and Block.
The various areas that Christian Bischof examines in his Automatic differentiation study include Computer Aided Design and Fortran.
His work focuses on many connections between QR decomposition and other disciplines, such as Rank, that overlap with his field of interest in Applied mathematics and Mathematical optimization.
The Parallel computing study combines topics in areas such as Basic Linear Algebra Subprograms, Visualization, Feature extraction, Eigenvalues and eigenvectors and Virtual reality.
Christian Bischof interconnects Representation, Matrix multiplication, Householder's method, Householder transformation and Multiplication in the investigation of issues within Factorization.
His most cited work include:
- LAPACK Users' Guide, 3rd ed. (413 citations)
- LAPACK: a portable linear algebra library for high-performance computers (399 citations)
- ADIFOR-Generating Derivative Codes from Fortran Programs (379 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Automatic differentiation, Parallel computing, Algorithm, Fortran and Computation.
His Automatic differentiation study is associated with Programming language.
His Parallel computing study incorporates themes from Lattice problem and Scalability.
His work deals with themes such as Function, Matrix, QR decomposition and Chain rule, which intersect with Algorithm.
His study looks at the relationship between Chain rule and fields such as Differential calculus, as well as how they intersect with chemical problems.
His Fortran research includes themes of Numerical differentiation and Numerical analysis.
He most often published in these fields:
- Automatic differentiation (33.33%)
- Parallel computing (22.44%)
- Algorithm (20.46%)
What were the highlights of his more recent work (between 2013-2020)?
- Parallel computing (22.44%)
- Lattice problem (4.29%)
- Cryptography (3.63%)
In recent papers he was focusing on the following fields of study:
Christian Bischof mainly investigates Parallel computing, Lattice problem, Cryptography, Automatic differentiation and Solver.
His Parallel computing study integrates concerns from other disciplines, such as Scalability, Compiler, Computer architecture, Code and Data structure.
His Lattice problem study also includes
- Theoretical computer science and Prime most often made with reference to Cryptosystem,
- Non-blocking algorithm which connect with Linked list.
His Cryptography research is multidisciplinary, relying on both Computational complexity theory and Simulated annealing.
His Operator overloading study in the realm of Automatic differentiation interacts with subjects such as Source transformation.
His Solver research includes elements of Core and Speedup.
Between 2013 and 2020, his most popular works were:
- Lock-Free GaussSieve for Linear Speedups in Parallel High Performance SVP Calculation (25 citations)
- Tuning GaussSieve for Speed (25 citations)
- Parallel (Probable) Lock-Free Hash Sieve: A Practical Sieving Algorithm for the SVP (23 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Programming language
- Algorithm
His primary areas of investigation include Parallel computing, Lattice problem, Cryptography, Theoretical computer science and Cryptosystem.
His Parallel computing research incorporates elements of Scalability, Compiler and Implementation.
His biological study deals with issues like Solver, which deal with fields such as Performance engineering, Task, Automation, Supercomputer and Learning with errors.
His study in Theoretical computer science is interdisciplinary in nature, drawing from both Programming language, Source code, Operator overloading, Unreachable code and Code bloat.
He usually deals with Code bloat and limits it to topics linked to Source lines of code and Automatic differentiation.
His Algorithm study combines topics in areas such as Heuristics and Prime.
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