Welcome
Welcome to the MaD Lab!
The researchers in the Machine Learning and Data Analytics (MaD) lab conduct theoretical and applied research for wearable computing systems and machine learning algorithms for engineering applications at the intersection of sports and health care. Our motivation is generating a positive impact on human wellbeing, be it through increasing performance, maintaining health, improving rehabilitation, or monitoring disease.
The MaD Lab is the home of the Innovation Lab for Wearable and Ubiquitous Computing, where students develop innovative prototypes with industry partners.
At the 54th Edition of the Hawaii International Conference on Systems Sciences (HICSS-54), January 4-8, 2021, Hawaii, USA, Imrana Abdullahi Yari's paper was awarded the Best Paper Award in the IT in Health Care track out of 1448 papers submitted to HICSS-54 (https://hicss.hawaii.edu/best-papers/). H... Continue
Falk joined the MAD Team in October 2020. He studied Mathematics at the RWTH Aachen University. During his ERASMUS exchange in Birmingham, UK, he discovered his interest in Machine Learning and Neural Networks. This inspired his master thesis "Training of ReLU-Networks with Gradient Descent". Before... Continue
Dario joined the MaD lab in November as a Postdoc. Previously, he spent one year as a Postdoc at the NeuroSense joint lab in Siena (Italy), developing machine learning techniques for the analysis of eye-tracking data. He received his Ph.D. in Smart Computing from the University of Florence (Italy), ... Continue
With great pleasure, we can announce that Prof. Dr. Björn Eskofier has been awarded the Curious-Mind-Forscherpreis in the category Life Science. The excellent cutting-edge research was expressly honored and congratulated by Angela Merkel.
The Curious-Mind-Forscherpreis, presented by manager magazin... Continue
At the WeRob2020/WearRAcon Europe 2020 conference, Prof. Anne Koelewijn was awarded the best paper award, sponsored by Sensors journal. At the conference, she presented the paper “Predictive Gait Simulations of Human Energy Optimization”, collaborative work with Prof. Jessica Selinger, who leads the... Continue
