What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Gene
- Machine learning
His primary scientific interests are in Memetic algorithm, Bioinformatics, Alzheimer's disease, Disease and Artificial intelligence.
He performs integrative Memetic algorithm and Job shop scheduling research in his work.
When carried out as part of a general Bioinformatics research project, his work on Biological data is frequently linked to work in Scalability, therefore connecting diverse disciplines of study.
His research on Alzheimer's disease also deals with topics like
- Cognition together with Cognitive decline, Hippocampus, Recall and Gene expression profiling,
- Biomarker that intertwine with fields like Metabolite, Metabolomics, Oncology and Area under the curve.
His Disease research includes themes of Longitudinal study and Computational biology.
His research integrates issues of Machine learning, Logistic regression and Fitness landscape in his study of Artificial intelligence.
His most cited work include:
- New Ideas In Optimization (1303 citations)
- On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms (1187 citations)
- Genome-wide association study identifies new multiple sclerosis susceptibility loci on chromosomes 12 and 20 (440 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Memetic algorithm, Artificial intelligence, Bioinformatics, Data mining and Machine learning.
His studies deal with areas such as Theoretical computer science and Metaheuristic as well as Memetic algorithm.
His Artificial intelligence study frequently intersects with other fields, such as Pattern recognition.
His Bioinformatics research incorporates themes from Gene expression profiling, Biomarker, Internal medicine, Disease and Computational biology.
His Disease study combines topics in areas such as Recall and Neuroscience.
His work carried out in the field of Data mining brings together such families of science as Microarray analysis techniques, Quadratic assignment problem, Cluster analysis and Graph.
He most often published in these fields:
- Memetic algorithm (29.52%)
- Artificial intelligence (18.50%)
- Bioinformatics (26.43%)
What were the highlights of his more recent work (between 2018-2021)?
- Memetic algorithm (29.52%)
- Analytics (3.52%)
- Artificial intelligence (18.50%)
In recent papers he was focusing on the following fields of study:
Pablo Moscato spends much of his time researching Memetic algorithm, Analytics, Artificial intelligence, Data science and Cluster analysis.
His study on Memetic algorithm is covered under Local search.
He interconnects Tree and Problem domain in the investigation of issues within Local search.
As a part of the same scientific family, Pablo Moscato mostly works in the field of Analytics, focusing on Data analysis and, on occasion, Metaheuristic and Ensemble learning.
His study in Metaheuristic is interdisciplinary in nature, drawing from both Predictive analytics, Feature selection and Curse of dimensionality.
His Artificial intelligence study incorporates themes from Machine learning, Network alignment and Regression.
Between 2018 and 2021, his most popular works were:
- An Accelerated Introduction to Memetic Algorithms (11 citations)
- Memetic Algorithms for Business Analytics and Data Science: A Brief Survey. (6 citations)
- M-Link: a link clustering memetic algorithm for overlapping community detection (5 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Gene
- Machine learning
His scientific interests lie mostly in Memetic algorithm, Representation, Local search, Theoretical computer science and Data mining.
His Memetic algorithm research is multidisciplinary, relying on both Partition and Cluster analysis.
He combines subjects such as Label propagation, Mutual information, Complex system, Population structure and Community structure with his study of Cluster analysis.
His Representation study is concerned with the field of Artificial intelligence as a whole.
The study incorporates disciplines such as Test, Data collection and Regression in addition to Artificial intelligence.
Within one scientific family, Pablo Moscato focuses on topics pertaining to Problem domain under Local search, and may sometimes address concerns connected to Heuristics.
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