Ricardo Chavarriaga Lozano



Phone+41 21 69 36968
H4 2 129.096 (Campus Biotech Batiment H4)
Ch. des Mines 9
CH-1202 Genève
OfficeH4 2 129.096
In unit
Defitech Foundation Chair in Brain-machine Interface


* Our paper on Quantifying electrode reliability during Brain-Computer Interface operation has just been accepted in IEEE Trans on Biomedical Engineering
* You can join the Free Live webinar we set up as part of the BMI workshop at the IEEE SMC conference
* A paper with A. Tzovara and M. de Lucia has been accepted on the Journal of Neuroscience methods: Quantifying the time for accurate EEG decoding of single value-based decisions
* We are organizing a Workshop on Brain-Machine Interfaces Systems at the upcoming IEEE SMC conference, October 5-7, 2014 in San Diego, USA.
* New papers: Errare machinale est: The use of error-related potentials in brain-machine interfaces and Single trial prediction of self-paced reaching directions from EEG signals
* Our paper Single trial analysis of slow cortical potentials: A study on anticipation related potentials was selected as one of Journal of Neural Engineering's highlight for 2014
* New paper: Latency Correction of Event-Related Potentials Between Different Experimental Protocols, Journal of Neural Engineering, 2014
* Marija Uscumlic successfully passed their PhD exam, and is now post-doctoral researcher at TU Berlin. Congratulations!
* New paper in PLoS ONE — An Iterative Framework for EEG-based Image Search: Robust Retrieval with Weak Classifiers
* Our lab will provide lectures and experimental projects during FENS-IBRO Imaging Training Center 2013 - Switzerland August 25 - September 13, 2013
* Hesam Sagha and Mohit Goel successfully passed their PhD exam. Congratulations!
* Our work on cognitive signals for BCI, in collaboration with the University of Zaragoza, has been nominated for the gTEC Annual BCI research award 2013.

Ricardo Chavarriaga Lozano

Research Scientist

Nationality : Colombian

Fields of Expertise

  • Brain-computer interfaces / Bio-inspired robotics / Human-robot interaction / Statistical machine learning / Computational Neuroscience