World's Best Scientists 2026 revealed!
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Computer Science
Germany
2025

D-Index & Metrics

Computer Science

D-Index
75
Citations
31042
World Ranking
1383
National Ranking
55

Research.com Recognitions

  • 2025 - Research.com Computer Science in Germany Leader Award
  • 2023 - Research.com Computer Science in Germany Leader Award
  • 2022 - Research.com Computer Science in Germany Leader Award

Overview

Benjamin Blankertz is affiliated with the Technical University of Berlin in Germany. Their research spans multiple areas within neuroscience and medicine, focusing extensively on brain-computer interfaces and neural engineering.

Their notable recent publications include the following:

  • Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson's disease, 2022, eLife
  • Machine-learning model predicting postoperative delirium in older patients using intraoperative frontal electroencephalographic signatures, 2022, Frontiers in Aging Neuroscience
  • Desflurane is risk factor for postoperative delirium in older patients' independent from intraoperative burst suppression duration, 2023, Frontiers in Aging Neuroscience
  • Roadmap, 2020, Data Archiving and Networked Services (DANS)
  • Motor Imagery Under Distraction- An Open Access BCI Dataset, 2020, Frontiers in Neuroscience

The frequent co-authors who have collaborated with Benjamin Blankertz include:

  • Wolf-Julian Neumann
  • Timon Merk
  • Victoria Peterson
  • Witold Lipski
  • Ningfei Li

Their work has appeared in several publication venues, with multiple contributions to:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Frontiers in Aging Neuroscience
  • Imaging Neuroscience
  • eLife
  • Frontiers in Neuroscience

Benjamin Blankertz's main fields of study are:

  • Neuroscience
  • Medicine

Within these fields, their subfields of study specialize in:

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience
  • Neurology
  • Electrical and Electronic Engineering
  • Critical Care and Intensive Care Medicine

The primary topics of their research activities cover:

  • EEG and Brain-Computer Interfaces
  • Neuroscience and Neural Engineering
  • Neurological disorders and treatments
  • Advanced Memory and Neural Computing
  • Intensive Care Unit Cognitive Disorders
  • Anesthesia and Sedative Agents
  • Neural and Behavioral Psychology Studies

Best Publications

  • Optimizing Spatial filters for Robust EEG Single-Trial Analysis

    B. Blankertz;R. Tomioka;S. Lemm;M. Kawanabe

  • On the interpretation of weight vectors of linear models in multivariate neuroimaging.

    Stefan Haufe;Frank C. Meinecke;Kai Görgen;Sven Dähne

  • Single-Trial Analysis and Classification of ERP Components - a Tutorial

    Benjamin Blankertz;Steven Lemm;Matthias Sebastian Treder;Stefan Haufe

  • Review of the BCI Competition IV

    Michael Tangermann;Klaus Robert Müller;Ad Aertsen;Niels Birbaumer

  • The non-invasive Berlin Brain-Computer Interface: fast acquisition of effective performance in untrained subjects.

    Benjamin Blankertz;Guido Dornhege;Matthias Krauledat;Klaus Robert Müller

  • The BCI competition III: validating alternative approaches to actual BCI problems

    B. Blankertz;K.-R. Muller;D.J. Krusienski;G. Schalk

  • The BCI competition 2003: progress and perspectives in detection and discrimination of EEG single trials

    B. Blankertz;K.-R. Muller;G. Curio;T.M. Vaughan

  • Neurophysiological Predictor of SMR-based BCI Performance

    Benjamin Blankertz;Claudia Sannelli;Sebastian Halder;Eva M. Hammer

  • Introduction to machine learning for brain imaging.

    Steven Lemm;Benjamin Blankertz;Thorsten Dickhaus;Klaus Robert Müller

  • Spatio-spectral filters for improving the classification of single trial EEG

    S. Lemm;B. Blankertz;G. Curio;K.-R. Muller

  • Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms

    G. Dornhege;B. Blankertz;G. Curio;K.-R. Muller;K.-R. Muller

  • Enhanced performance by a hybrid NIRS–EEG brain computer interface

    Siamac Fazli;Jan Mehnert;Jan Mehnert;Jens Steinbrink;Gabriel Curio

  • Classifying Single Trial EEG: Towards Brain Computer Interfacing

    Benjamin Blankertz;Gabriel Curio;Klaus-Robert Müller

  • Towards adaptive classification for BCI.

    Pradeep Shenoy;Matthias Krauledat;Benjamin Blankertz;Rajesh P.N. Rao

  • Machine learning for real-time single-trial EEG-analysis: from brain-computer interfacing to mental state monitoring.

    Klaus Robert Müller;Michael Tangermann;Guido Dornhege;Matthias Krauledat

  • Towards a Cure for BCI Illiteracy

    Carmen Vidaurre;Benjamin Blankertz

  • Combined Optimization of Spatial and Temporal Filters for Improving Brain-Computer Interfacing

    G. Dornhege;B. Blankertz;M. Krauledat;M. Krauledat;F. Losch

  • The Berlin brain-computer interface: EEG-based communication without subject training

    B. Blankertz;G. Dornhege;M. Krauledat;K.-R. Muller

  • The Berlin Brain–Computer Interface: Non-Medical Uses of BCI Technology

    Benjamin Blankertz;Benjamin Blankertz;Michael Tangermann;Carmen Vidaurre;Siamac Fazli

  • (C)overt attention and visual speller design in an ERP-based brain-computer interface.

    Matthias S Treder;Benjamin Blankertz

Frequent Co-Authors

Klaus-Robert Müller
Klaus-Robert Müller Technical University of Berlin
Gabriel Curio
Gabriel Curio Charité - University Medicine Berlin
Carmen Vidaurre
Carmen Vidaurre Technical University of Berlin
Andrea Kübler
Andrea Kübler University of Würzburg
Niels Birbaumer
Niels Birbaumer University of Tübingen
Klaus Obermayer
Klaus Obermayer Technical University of Berlin
Clemens Brunner
Clemens Brunner University of Graz
Giulio Jacucci
Giulio Jacucci University of Helsinki
Gerwin Schalk
Gerwin Schalk Sichuan University
John-Dylan Haynes
John-Dylan Haynes Charité - University Medicine Berlin

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