Dr. Michael Knierim

Do you also hate meetings? Or perhaps, too many, too long, or unproductive meetings? There is probably a lot to improve about meetings. Sure, sometimes they are great, but it feels like that is rather the exception and not the rule. Thanks to the recent advances in wearable sensing technology and artificial intelligence (AI) we are finally approaching innovative, adaptive systems that could turn lame meetings into great ones. How you might ask?

First of all, did you know that during the peak of the first Covid-19 lockdowns, Microsoft conducted an EEG study on how people become fatigued from prolonged participation in virtual meetings? (https://www.microsoft.com/en-us/worklab/work-trend-index/brain-research) Specifically, they learned that their EEG recordings showed increasing levels of fatigue, especially when there were too few or too short breaks between meetings. When these breaks were taken, the EEG levels showed a clear recovery effect. So what if we use ExG headphones (https://doi.org/10.1145/3544549.3585875 & https://github.com/MKnierim/openbci-headphones) to detect those fatigue levels and recommend appropriate meeting breaks automatically?

Second, did you know that a lot of research from MIT and others has looked at what makes a good team meeting? (https://hbr.org/2012/04/the-new-science-of-building-great-teams) Interestingly, a very strong predictor is how evenly the speaking time is distributed in the team. If everyone gets to speak, it's usually a good team meeting; if only one person speaks, it's often a one-man show. Now, if you don't need to know exactly what is being said, then we could use muscle activity recordings (again, from headphone sensors) to classify when a person is speaking (in fact, we have already done research that shows such classification is possible - https://doi.org/10.1007/978-3-030-88900-5_6) and provide feedback on the distribution of speech in a particular meeting. Pretty neat, right?

I am quite interested in integrating your ideas in this topic, so please consider submitting them together with your CV & transcript of records when applying for the project.

Also, if you have any questions about the topic beforehand, please contact Michael Knierim (michael.knierim@kit.edu).