(Feb 2020): PHinishieD!! After working on brain-computer interfaces for the last four years, I felt very prepared to present my work. Unfortunately, the oral presentation only lasts 20 minutes, so I could only provide a short overview of my research projects. The subsequent questions took much longer—over one hour—and were more challenging, but at the same time, it was a great pleasure discussing various aspects with the examineers.
(Jan 2020): I have visited the applied machine learning days for a third time and it was again, a great pleasure. After five days of continuous input, my brain was slightly overloaded, but still the conference never ceases to amaze me with the various input not only from technical projects, but also from topics related to ethical, privacy and socioeconomical questions.
(Oct 2019): And another good news. I will be working for Averbis starting from January 2020. Averbis uses text mining and natural language processing for extracting and processing information from medical documents to assist medical practitioners with their everyday job.
(Oct 2019): Together with Torsten Koller and Jörg Franke, we have founded freiburg.ai, a non-profit meeting platform where our main activity is to host a series of talks in the AI field in Freiburg. We are very happy that our first event with Prof. Frank Hutter on 24.10.2019 had more than 80 attendees .
(Apr 2019): I submitted my PhD thesis "From supervised to unsupervised machine learning for brain-computer interfaces and their application in language rehabilitation". A big shout-out to the numerous collaborators and other people that have supported me in that process.
(Jan 2019): We gave a talk about our aphasia project at the applied machine learning days (AMLD 2019) - a highly inspiring event.
(Nov 2018): Here is a video how unsupervised machine learning can be used to rapidly allow a user to spell some letters only by using his brain signals and without prior calibration. Thanks to my cousin Daniel Knobloch for participating in this video.
(Sep 2018): A new article appeared in Frontiers in Human Neuroscience where we have compared the usage of auditory BCIs with open- and with closed-eyes.
Interestingly, the majority of subjects preferred to close their eyes while controlling the BCI – something which is not yet being used in practical applications.
This work is the result of our annual practical course where the students Albrecht Schall and Natalie Prange showed great effort. Link (open access)
(Apr 2018): We have been nominated for the BCI Award again: This time with our work on BCI-supported language training. Check out our video below. The winner will be crowned at the 7th International BCI Meeting May 21 – 25, 2018 at the Asilomar Conference Center in Pacific Grove, California, USA. There, we will also have a workshop on unsupervised learning.
Update: We won the 2nd price in the BCI award! Yay! News
(Apr 2018): Our new paper on unsupervised learning appeared in the IEEE computational intelligence magazine.
In this paper, we review different unsupervised learning approaches for ERP-based BCIs and compare three of them in an online study.
(Jan 2018): We presented a workshop about unsupervised learning for BCIs at the applied machine learning days in Lausanne – a great event where I would love to return next year Link
(Sep 2017): I won the best talk award for an oral presentation at the
7th Graz Brain-Computer Interface Conference 2017. I presented our joint work on unsupervised learning by mixing model estimators. Thanks again to the great collaborators.
(Aug 2017): Our work on unsupervised learning has been nominated for the BCI Award 2017,
an international award with more than 50 competing groups. A great collaboration with Pieter-Jan Kindermans, Thibault Verhoeven,
Klaus-Robert Müller and Michael Tangermann. Poster
(Jul 2017): I won the best talk award at the first Neuroadaptive Technology (NAT 17) conference in Berlin.
I presented work about unsupervised learning with learning from label proportions (LLP).
(Apr 2017): A new idea for BCIs: Learning from label proportions has been used in other areas as a simple and powerful concept to allow unsupervised learning. Together with Pieter-Jan Kindermans,
Thibault Verhoeven, Konstantin Schmid, Klaus-Robert Müller and Michael Tangermann, we demonstrate how this can be applied in ERP-based BCIs to obtain the first unsupervised classifier with guaranteed convergence.
If you are interested, then check out the project page or have a look at the article in PLOS ONE. Link (open access)