S. Fazli

发表

Bristle-sensors—low-cost flexible passive dry EEG electrodes for neurofeedback and BCI applications

C. Grozea, C. D. Voinescu, S. Fazli, 2011, Journal of neural engineering.

Single Trial Classification of Motor Imagination Using 6 Dry EEG Electrodes

K. Müller, B. Blankertz, S. Fazli, 2007, PloS one.

Using Rest Class and Control Paradigms for Brain Computer Interfacing

Klaus-Robert Müller, Benjamin Blankertz, Siamac Fazli, 2009, IWANN.

Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies.

Klaus-Robert Müller, Siamac Fazli, Grégoire Montavon, 2013, Journal of chemical theory and computation.

Learning From More Than One Data Source: Data Fusion Techniques for Sensorimotor Rhythm-Based Brain–Computer Interfaces

Klaus-Robert Müller, Wojciech Samek, Siamac Fazli, 2015, Proceedings of the IEEE.

Learning Invariant Representations of Molecules for Atomization Energy Prediction

Andreas Ziehe, Klaus-Robert Müller, Siamac Fazli, 2012, NIPS.

On the feasibility of using motor imagery EEG-based brain–computer interface in chronic tetraplegics for assistive robotic arm control: a clinical test and long-term post-trial follow-up

C Grozea, C. Grozea, S. Fazli, 2012, Spinal Cord.

A bibliometric review of the water security concept in Central Asia

S. Fazli, Lei Xie, S. Xenarios, 2020, Environmental Research Letters.

EEG-based decoding of declarative memory formation

S. Fazli, Taeho Kang, Yiyu Chen, 2016, 2016 4th International Winter Conference on Brain-Computer Interface (BCI).

EEG-based neural decoding of Intelligence Questions

S. Fazli, F. Biessmann, Yiyu Chen, 2015, The 3rd International Winter Conference on Brain-Computer Interface.

A Review of Modern Approaches for Coronary Angiography Imaging Analysis

S. Fazli, Eldar Ismailov, Maxim Y Popov, 2022, ArXiv.

Spatio-Spectral Feature Representation for Motor Imagery Classification Using Convolutional Neural Networks

Seong-Whan Lee, S. Fazli, Cuntai Guan, 2021, IEEE Transactions on Neural Networks and Learning Systems.

Tutorial on multimodal neuroimaging for brain-computer interfacing

K. Müller, Seong-Whan Lee, B. Blankertz, 2013, Balkan Conference in Informatics.

A biologically-inspired multi-modal evaluation of molecular generative machine learning

Vsevolod A. Peshkov, S. Fazli, K. Pats, 2022, 2208.09658.

A biologically-inspired evaluation of molecular generative machine learning

Vsevolod A. Peshkov, S. Fazli, K. Pats, 2022, ArXiv.

Decoding cognitive brain states

Stefan Haufe, Gabriel Curio, Benjamin Blankertz, 2013, 2013 International Winter Workshop on Brain-Computer Interface (BCI).

NIRS signal predict SMR-based BCI performance in EEG

Gabriel Curio, Benjamin Blankertz, Siamac Fazli, 2010 .

Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data

Stefan Haufe, Klaus-Robert Müller, Wojciech Samek, 2015, Proceedings of the IEEE.

How visual attention affects choice outcomes: An eyetracking study

Siamac Fazli, Riccardo Scarpa, Vincenzina Caputo, 2015, The 3rd International Winter Conference on Brain-Computer Interface.

A High-Security EEG-Based Login System with RSVP Stimuli and Dry Electrodes

Hyoung Joong Kim, Benjamin Blankertz, Siamac Fazli, 2016, IEEE Transactions on Information Forensics and Security.

EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy

John Williamson, Siamac Fazli, Seong-Whan Lee, 2019, GigaScience.

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

Stefan Haufe, Klaus-Robert Müller, Gabriel Curio, 2010, Front. Neurosci..

Detecting Mental States by Machine Learning Techniques: The Berlin Brain-Computer Interface

Klaus-Robert Müller, Gabriel Curio, Benjamin Blankertz, 2009 .

The Berlin Brain-Computer Interface

Klaus-Robert Müller, Gabriel Curio, Benjamin Blankertz, 2008, WCCI.

An Efficient ERP-Based Brain-Computer Interface Using Random Set Presentation and Face Familiarity

Klaus-Robert Müller, Siamac Fazli, Seong-Whan Lee, 2014, PloS one.

Interdisciplinary Aspects of Cognition

Antonio Cerone, Siamac Fazli, Ahti-Veikko Pietarinen, 2019, SEFM Workshops.

Enhanced Performance by a Hybrid Nirs–eeg Brain Computer Interface

Klaus-Robert Müller, Gabriel Curio, Arno Villringer, 2022 .

Subject-dependent classification for robust idle state detection using multi-modal neuroimaging and data-fusion techniques in BCI

Siamac Fazli, Seong-Whan Lee, Min-Ho Lee, 2015, Pattern Recognit..

Predicting BCI Subject Performance Using Probabilistic Spatio-Temporal Filters

Klaus-Robert Müller, Heung-Il Suk, Siamac Fazli, 2014, PloS one.

A High Performance Spelling System based on EEG-EOG Signals With Visual Feedback

John Williamson, Siamac Fazli, Seong-Whan Lee, 2018, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Advances in Neurotechnology for Brain Computer Interfaces

Siamac Fazli, S. Fazli, 2011 .

cheML.io: an online database of ML-generated molecules

Vsevolod A. Peshkov, S. Fazli, Rustam Zhumagambetov, 2020, RSC advances.

OpenBMI: A real-time data analysis toolbox for Brain-Machine Interfaces

Ji-Hoon Jeong, Siamac Fazli, Seong-Whan Lee, 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

P300 visual speller based on random set presentation

Siamac Fazli, Seong-Whan Lee, Seul-Ki Yeom, 2014, 2014 International Winter Workshop on Brain-Computer Interface (BCI).

Multifrequency Analysis of Brain-Computer Interfaces

Klaus-Robert Müller, Heung-Il Suk, Siamac Fazli, 2015 .

Subject-independent mental state classification in single trials

Klaus-Robert Müller, Benjamin Blankertz, Siamac Fazli, 2009, Neural Networks.

Transmol: repurposing a language model for molecular generation

Siamac Fazli, Ferdinand Molnár, Rustam Zhumagambetov, 2021, RSC advances.

EEG-Based Prediction of Successful Memory Formation During Vocabulary Learning

Christian Wallraven, Siamac Fazli, Taeho Kang, 2020, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Using NIRS as a predictor for EEG-based BCI performance

Benjamin Blankertz, Siamac Fazli, Jens Steinbrink, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

ℓ1-penalized linear mixed-effects models for high dimensional data with application to BCI

Klaus-Robert Müller, Siamac Fazli, Márton Danóczy, 2011, NeuroImage.

Subject independent EEG-based BCI decoding

Klaus-Robert Müller, Benjamin Blankertz, Siamac Fazli, 2009, NIPS.

Brain Computer Interfacing: A Multi-Modal Perspective

Siamac Fazli, Seong-Whan Lee, Seong-Whan Lee, 2013, J. Comput. Sci. Eng..

Hybrid brain-computer interface based on EEG and NIRS modalities

Siamac Fazli, Seong-Whan Lee, Min-Ho Lee, 2014, 2014 International Winter Workshop on Brain-Computer Interface (BCI).

Selective temporal filtering and its application to hand gesture recognition

Seong-Whan Lee, S. Fazli, Myung-Cheol Roh, 2016, Applied Intelligence.

Towards an enhanced ERP speller based on the visual processing of face familiarity

Klaus-Robert Müller, Siamac Fazli, Seong-Whan Lee, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

MLT-LE: predicting drug-target binding affinity with multi-task residual neural networks

S. Fazli, K. Pats, E. Vinogradova, 2022, arXiv.org.

A Low-Cost, IMU-Based Real-Time On Device Gesture Recognition Glove

Oleg Makaussov, Mikhail Krassavin, Maxim Zhabinets, 2020, 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Assessing water security in Central Asia through a Delphi method and a clustering analysis

S. Fazli, S. Xenarios, Aliya Assubayeva, 2022, Frontiers in Environmental Science.

EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy

Seong-Whan Lee, S. Fazli, Min-Ho Lee, 2019, GigaScience.

Integration of Multivariate Data Streams With Bandpower Signals

Klaus-Robert Müller, Siamac Fazli, Felix Bießmann, 2013, IEEE Transactions on Multimedia.

ℓ1-penalized linear mixed-effects models for high dimensional data with application to BCI

K. Müller, S. Fazli, M. Danóczy, 2011, NeuroImage.