What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Statistics
- Artificial intelligence
Chaotic, Topology, Statistical physics, Synchronization networks and Dynamical systems theory are his primary areas of study.
His research in Chaotic intersects with topics in Configuration space, Attractor, Symbolic dynamics and Three-body problem.
His Topology research is multidisciplinary, incorporating perspectives in Telecommunications network, Synchronization and Nonlinear system.
His research integrates issues of Nonlinear time series analysis, Contrast, Transfer entropy and Dimension in his study of Statistical physics.
His Synchronization networks study combines topics in areas such as Distributed computing, Parametric statistics, Stability, Master stability function and Eigenvalues and eigenvectors.
By researching both Dynamical systems theory and Synchronization, he produces research that crosses academic boundaries.
His most cited work include:
- Sufficient Conditions for Fast Switching Synchronization in Time-Varying Network Topologies (275 citations)
- Local method for detecting communities. (271 citations)
- Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator (127 citations)
What are the main themes of his work throughout his whole career to date?
Erik M. Bollt spends much of his time researching Dynamical systems theory, Topology, Chaotic, Algorithm and Theoretical computer science.
As a part of the same scientific family, Erik M. Bollt mostly works in the field of Dynamical systems theory, focusing on Applied mathematics and, on occasion, Eigenfunction and Discrete mathematics.
In Topology, Erik M. Bollt works on issues like Synchronization, which are connected to Network topology.
He has included themes like Attractor, Mathematical analysis, Control theory, Nonlinear system and Symbolic dynamics in his Chaotic study.
His Algorithm research includes elements of Probability and statistics, Measure and Dimensionality reduction.
While the research belongs to areas of Theoretical computer science, he spends his time largely on the problem of Entropy, intersecting his research to questions surrounding Time series, Inference and Mutual information.
He most often published in these fields:
- Dynamical systems theory (19.55%)
- Topology (13.16%)
- Chaotic (11.65%)
What were the highlights of his more recent work (between 2015-2021)?
- Algorithm (11.65%)
- Dynamical systems theory (19.55%)
- Entropy (10.15%)
In recent papers he was focusing on the following fields of study:
Erik M. Bollt mainly investigates Algorithm, Dynamical systems theory, Entropy, Applied mathematics and Data-driven.
He interconnects Nonlinear dimensionality reduction, Probability and statistics, Embedding, Robustness and Complex network in the investigation of issues within Algorithm.
In his research on the topic of Dynamical systems theory, Reservoir computing is strongly related with Dynamical system.
In the field of Entropy, his study on Entropy overlaps with subjects such as Causation.
Erik M. Bollt focuses mostly in the field of Applied mathematics, narrowing it down to topics relating to Eigenfunction and, in certain cases, Equivalence class, Rank and Nonlinear system.
His work focuses on many connections between Inference and other disciplines, such as Feature selection, that overlap with his field of interest in Theoretical computer science.
Between 2015 and 2021, his most popular works were:
- Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator (127 citations)
- Inferring causation from time series in Earth system sciences (114 citations)
- Inference of Causal Information Flow in Collective Animal Behavior (25 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Statistics
- Artificial intelligence
His scientific interests lie mostly in Algorithm, Causation, Dynamical systems theory, Entropy and Inference.
His studies deal with areas such as Nonlinear dimensionality reduction, Dimensionality reduction, Manifold, Probability and statistics and Robustness as well as Algorithm.
Data science, Earth system science and Nonlinear system are fields of study that overlap with his Causation research.
While working in this field, Erik M. Bollt studies both Dynamical systems theory and Rectification.
His Entropy research incorporates themes from Estimation theory, Mutual information and Time series.
Erik M. Bollt has researched Inference in several fields, including Information flow and Anatomy.
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