D-Index & Metrics Best Publications
Neuroscience
Italy
2023
Computer Science
Italy
2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 70 Citations 14,565 359 World Ranking 1197 National Ranking 16
Neuroscience D-index 80 Citations 18,386 455 World Ranking 940 National Ranking 29

Research.com Recognitions

Awards & Achievements

2023 - Research.com Computer Science in Italy Leader Award

2023 - Research.com Neuroscience in Italy Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Electroencephalography
  • Neuroscience

His scientific interests lie mostly in Electroencephalography, Artificial intelligence, Neuroscience, Pattern recognition and Brain–computer interface. His study of Brain activity and meditation is a part of Electroencephalography. His Artificial intelligence research is multidisciplinary, incorporating elements of Inverse problem, High resolution eeg, Estimator, Computer vision and Machine learning.

His work deals with themes such as Coherence, Multivariate statistics and Autoregressive model, which intersect with Pattern recognition. His Brain–computer interface research integrates issues from BitTorrent tracker, Emulation and Human–computer interaction. His work is dedicated to discovering how Neurophysiology, Workload are connected with Air traffic management and Air traffic control and other disciplines.

His most cited work include:

  • Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness. (537 citations)
  • Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function. (339 citations)
  • Human Movement-Related Potentials vs Desynchronization of EEG Alpha Rhythm: A High-Resolution EEG Study (300 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of investigation include Electroencephalography, Artificial intelligence, Neuroscience, Pattern recognition and Cognition. Fabio Babiloni studied Electroencephalography and Audiology that intersect with Perception. His Artificial intelligence research includes themes of Machine learning, High resolution eeg, Computer vision and Autoregressive model.

His Pattern recognition course of study focuses on Coherence and Estimator. His studies in Cognition integrate themes in fields like Workload, Cognitive psychology, Neuroimaging and Neuromarketing. He combines subjects such as Speech recognition and Human–computer interaction with his study of Brain–computer interface.

He most often published in these fields:

  • Electroencephalography (62.45%)
  • Artificial intelligence (32.45%)
  • Neuroscience (23.06%)

What were the highlights of his more recent work (between 2015-2021)?

  • Electroencephalography (62.45%)
  • Artificial intelligence (32.45%)
  • Cognition (16.73%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Electroencephalography, Artificial intelligence, Cognition, Workload and Air traffic control. When carried out as part of a general Electroencephalography research project, his work on Brain activity and meditation is frequently linked to work in Correlation, therefore connecting diverse disciplines of study. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Field, Machine learning, Computer vision and Pattern recognition.

His Cognition research integrates issues from Speech recognition, Stimulation and Neurometrics. His biological study spans a wide range of topics, including Simulation and Vigilance. His research in Air traffic management intersects with topics in Brain–computer interface and Human–computer interaction.

Between 2015 and 2021, his most popular works were:

  • Investigating Cooperative Behavior in Ecological Settings: An EEG Hyperscanning Study (86 citations)
  • Adaptive Automation Triggered by EEG-Based Mental Workload Index: A Passive Brain-Computer Interface Application in Realistic Air Traffic Control Environment. (80 citations)
  • Passive BCI beyond the lab: current trends and future directions (72 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Neuroscience
  • Cognition

His primary scientific interests are in Electroencephalography, Cognition, Brain–computer interface, Artificial intelligence and Air traffic control. His research integrates issues of Cognitive psychology, Perception, Parietal lobe, Neuroimaging and Brain mapping in his study of Electroencephalography. His Neuroimaging research includes themes of Quality, Frequency domain, Usability and Pattern recognition.

His Brain mapping study improves the overall literature in Neuroscience. His Brain–computer interface research is multidisciplinary, relying on both Simulation, Vigilance and Human–computer interaction. His study looks at the intersection of Artificial intelligence and topics like Machine learning with Classifier.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness.

Gianluca Borghini;Laura Astolfi;Giovanni Vecchiato;Donatella Mattia.
Neuroscience & Biobehavioral Reviews (2014)

1044 Citations

Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function.

Fabio Babiloni;Febo Cincotti;Claudio Babiloni;Filippo Carducci.
NeuroImage (2005)

476 Citations

Social neuroscience and hyperscanning techniques: past, present and future.

Fabio Babiloni;Laura Astolfi.
Neuroscience & Biobehavioral Reviews (2014)

424 Citations

Human Movement-Related Potentials vs Desynchronization of EEG Alpha Rhythm: A High-Resolution EEG Study

Claudio Babiloni;Filippo Carducci;Febo Cincotti;Paolo M. Rossini.
NeuroImage (1999)

418 Citations

Comparison of different cortical connectivity estimators for high-resolution EEG recordings.

Laura Astolfi;Febo Cincotti;Donatella Mattia;M. Grazia Marciani.
Human Brain Mapping (2007)

388 Citations

Non-invasive brain-computer interface system: towards its application as assistive technology

Febo Cincotti;Donatella Mattia;Fabio Aloise;Simona Bufalari.
Brain Research Bulletin (2008)

377 Citations

Prefontal cortex in long-term memory: an "interference" approach using magnetic stimulation

Simone Rossi;Stefano F. Cappa;Claudio Babiloni;Patrizio Pasqualetti.
Nature Neuroscience (2001)

318 Citations

Computerized processing of EEG-EOG-EMG artifacts for multi-centric studies in EEG oscillations and event-related potentials.

D V Moretti;F Babiloni;F Carducci;F Cincotti.
International Journal of Psychophysiology (2003)

277 Citations

Spline Laplacian estimate of EEG potentials over a realistic magnetic resonance-constructed scalp surface model

F. Babiloni;C. Babiloni;F. Carducci;L. Fattorini.
Electroencephalography and Clinical Neurophysiology (1996)

274 Citations

Human cortical electroencephalography (EEG) rhythms during the observation of simple aimless movements: a high-resolution EEG study.

Claudio Babiloni;Fabio Babiloni;Filippo Carducci;Febo Cincotti.
NeuroImage (2002)

269 Citations

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