Millán, José del R. - Other - CNS Directory




: Jose del R Millan
Professor, Professor of Neurology
Chandra Department of Electrical and Computer Engineering, Department of Neurology

Carol Cockrell Curran Chair in Engineering (Holder)

Website
jose.millan@austin.utexas.edu

Phone: 512-471-3434

Office Location
HDB

Postal Address
2501 SPEEDWAY
AUSTIN, TX 78712

: Dr. José del R. Millán is a professor and holds the Carol Cockrell Curran Chair in the Department of Electrical and Computer Engineering at The University of Texas at Austin. He is also a professor in the Department of Neurology of the Dell Medical School.

He received a PhD in computer science from the Technical University of Catalonia, Barcelona, in 1992. Prior to joining UT Austin, he was a research scientist at the Joint Research Centre of the European Commission in Ispra, Italy, and a senior researcher at the Idiap Research Institute in Martigny, Switzerland. He has also been a visiting scholar at the University of California, Berkeley, and Stanford University as well as the International Computer Science Institute in Berkeley. Most recently, he held the Defitech Foundation Chair in Brain-Machine Interface at the École Polytechnique Fédérale de Lausanne in Switzerland, where he helped establish the Center for Neuroprosthetics.

Dr. Millán has made several seminal contributions to the field of brain-machine interfaces, especially based on electroencephalogram signals. Most of his achievements revolve around the design of brain-controlled robots. He has received several recognitions for these seminal and pioneering achievements, notably the IEEE-SMC Norbert Wiener Award in 2011, elevation to IEEE Fellow in 2017 and elected fellow of the International Academy of Medical and Biological Engineering. In addition to his work on the fundamentals of BMI and design of neuroprosthetics, Millán is prioritizing the translation of BMI to end-users who live with motor and cognitive disabilities. In parallel, he is designing BMI technology to offer new interaction modalities for people without disabilities.

The overarching objective of CNBI’s research is to bring brain-machine interfaces (BMI) out of the laboratory into the daily life of people, in particular those with severe disabilities. To do so, we tackle three major scientific challenges:

deploying BMI systems in the clinical realm to promote neural plasticity and functional recovery of patients;
designing novel BMI paradigms to augment interaction experience in our daily activities;
developing new principles to facilitate user’s acquisition of BMI skills.

We also believe that these three aims can only be probed, advanced and demonstrated by engaging BMI users in long-term use of complex brain-controlled devices. In our quest, we depart from a dominant view in the BMI field, where the usual question researchers ask is “how to improve decoding of user’s intention?”. Although this aspect is certainly central and we don’t neglect it, we rather ask “how to facilitate user’s acquisition of BCI skills?”

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Publications

2020

Journal Articles

S. Perdikis, R. Leeb, R. Chavarriaga, J.d.R. Millán. (2020). Context–aware learning for generative models. IEEE Trans. Neural Networks and Learning Systems, to appear.
Pdf version

M. Pereira, N. Faivre, I. Iturrate, M. Wirthlin, L. Serafini, S. Martin, A. Desvachez, O. Blanke, D. Van De Ville, J.d.R. Millán. (2020). Disentangling the origins of confidence in speeded perceptual judgments through multimodal imaging. Proceedings of the National Academy of Sciences USA, 117(15):8382–8390.
Detailed record – Pdf version

B. Orset, K. Lee, R. Chavarriaga, J.d.R. Millán. (2020). User adaptation to closed-loop decoding of motor imagery termination. IEEE Trans. Biomedical Engineering, to appear.
Pdf version

R. Aydarkhanov, M. Ušćumlić, R. Chavarriaga, L.A. Gheorghe, J.d.R. Millán. (2020). Spatial covariance improves BCI performance for late ERPs components with high temporal variability. Neural Engineering, 17:036030.
Pdf version

L. Tonin, F. Bauer, J.d.R. Millán. (2020). The role of the control framework for continuous tele-operation of a BMI driven mobile robot. IEEE Trans. Robotics, 36(1):78–91.
Pdf version

S. Perdikis, J.d.R. Millán. (2020). Brain-machine interfaces: A tale of two learners. IEEE Systems, Man, and Cybernetics Magazine, 6(3):12–19.
Pdf version

M. Bevilacqua, S. Perdikis, J.d.R. Millán. (2020). On error-related potentials during sensorimotor-based brain-computer interface: Explorations with a pseudo-online brain-controlled speller. IEEE Open Journal of Engineering in Medicine and Biology, 1:17–22.
Pdf version

C. Jeunet, D. Hauw, J.d.R. Millán. (2020). Sport psychology: Technologies ahead. Frontiers in Sports and Active Living, 2:10.
Pdf version

C. Jeunet, L. Tonin, L. Albert, R. Chavarriaga, B. Bideau, F. Argelaguet, J.d.R. Millán, A. Lécuyer , R. Kulpa. (2020). Uncovering EEG correlates of covert attention in soccer goalkeepers: Towards innovative sport training procedures. Scientific Reports, 10:1705.
Pdf version

C. Schneider, M. Pereira, L. Tonin, J.d.R. Millán.(2020). Real-time EEG feedback on alpha power lateralization leads to behavioural improvements in a covert attention task. Brain Topography, 33:48–59.
Detailed record

Institute for Neuroscience