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Tapping into nature’s wisdom
Electroencephalography (EEG), electrocardiography (ECG), electromyography (EMG) – all of these non-invasive medical diagnostic methods rely on an electrode to measure and record electrical signals or voltage fluctuations of muscle or nerve cells underneath the skin. Depending on the type of diagnostics, this can then be used to measure electrical brain waves, or the currents in the heart or muscles. Present methods use metal sensors which are attached to the skin using a special gel to ensure continuous contact. Researchers at the University of Korea and Technische Universität Berlin have now developed so-called biosensors made of the plant material cellulose. They not only offer better and more durable conductivity than conventional electrodes. They are also 100 percent natural, reusable, do not cause skin irritation like other gels and are biodegradable. The paper “Leaf inspired homeostatic cellulose biosensors” has now been published in the renowned journal Science Advances.
New workshop series “Trustworthy AI”
The AI for Good global summit is an all year digital event, featuring a weekly program of keynotes, workshops, interviews or Q&As. BIFOLD Fellow Dr. Wojciech Samek, head of department of Artificial Intelligence at Fraunhofer Heinrich Hertz Institute (HHI), is implementing a new online workshop series “Trustworthy AI” for this platform.
„European data sovereignty is a critical success factor“
On March 23, 2021, 09:00-12:00 CET, the European Committee Artificial Intelligence in a Digital Age (AIDA) is organizing a hearing on “AI and Competitiveness”. BIFOLD Co-Director Prof. Dr. Volker Markl is invited to give an initial intervention for the second panel on “How to build a competitive and innovative AI sector? What are EU enterprises challenges in entering AI markets, by developing and adopting competitive AI solutions?”
Making the use of AI systems safe
BIFOLD Fellow Dr. Wojciech Samek and Luis Oala (Fraunhofer Heinrich Hertz Institute) together with Jan Macdonald and Maximilian März (TU Berlin) were honored with the award for “best scientific contribution” at this year’s medical imaging conference BVM. Their paper “Interval Neural Networks as Instability Detectors for Image Reconstructions” demonstrates how uncertainty quantification can be used to detect errors in deep learning models.
KI in der Medizin muss erklärbar sein
Wissenschaftler*innen der TU Berlin und der Charité – Universitätsmedizin Berlin sowie der Universität Oslo haben ein neues Analyse-System für die Brustkrebsdiagnostik anhand von Gewebeschnitten entwickelt, das auf Künstlicher Intelligenz (KI) beruht. Zwei Weiterentwicklungen machen das System einzigartig: Zum einen integriert es erstmals morphologische, molekulare und histologische Daten in einer Auswertung. Zum zweiten liefert es eine Erklärung des KI-Entscheidungsprozesses in Form von sogenannten Heatmaps mit. Diese Heatmaps zeigen Pixel für Pixel welche Bildinformation wie stark zu dem KI-Entscheidungsprozess beigetragen hat. Dadurch können die Mediziner*innen das Ergebnis der KI-Analyse nachvollziehen und auf Plausibilität prüfen. Künstliche Intelligenz wird damit erklärbar – ein entscheidender und unabdingbarer Schritt nach vorn, will man KI-Systeme künftig im Klinik-Alltag zur Unterstützung der Medizin einsetzen. Die Forschungsergebnisse wurden jetzt in Nature Machine Intelligence veröffentlicht.
2020 pattern recognition best paper award
A team of scientists from TU Berlin, Fraunhofer Heinrich Hertz Institute (HHI) and University of Oslo has jointly received the 2020 “Pattern Recognition Best Paper Award” and “Pattern Recognition Medal” of the international scientific journal Pattern Recognition. The award committee honored the publication “Explaining Nonlinear Classification Decisions with Deep Taylor Decomposition” by Dr. Grégoire Montavon and Prof. Dr. Klaus-Robert Müller from TU Berlin, Prof. Dr. Alexander Binder from University of Oslo, as well as Dr. Wojciech Samek and Dr. Sebastian Lapuschkin from HHI.
BIFOLD fellow Dr. Wojciech Samek heads newly established AI research department at Fraunhofer HHI
The Fraunhofer Heinrich Hertz Institute (HHI) has established a new research department dedicated to “Artificial Intelligence”. The AI expert and BIFOLD Fellow Dr. Wojciech Samek, previously leading the research group “Machine Learning” at Fraunhofer HHI, will head the new department. With this move Fraunhofer HHI aims at expanding the transfer of its AI research on topics such as Explainable AI and neural network compression to the industry.
BIFOLD Co-Director Prof. Volker Markl named 2020 ACM fellow
The Association for Computing Machinery (ACM), the largest and oldest international association of computer scientists, has named Prof. Dr. Volker Markl, Co-Director of the Berlin Institute for the Foundations of Learning and Data (BIFOLD), as ACM Fellow 2020. Volker Markl received this distinction for his contributions to query optimization, scalable data processing and data programmability. He is one of 22 German scientists who have been honored by the ACM so far.
BIFOLD research into ML for molecular simulation is among the 2020 most downloaded annual reviews articles
The paper “Machine Learning for Molecular Simulation” by BIFOLD Co-Director Prof. Dr. Klaus-Robert Müller, Principal Investigator Prof. Dr. Frank Noé and colleagues was among the top 10 most downloaded physical science articles of Annual Reviews in 2020.
Resilient data management for the internet of moving things: TU Berlin and DFKI paper was accepted at BTW 2021
The paper “Towards Resilient Data Management for the Internet of Moving Things” by Elena Beatriz Ouro Paz, Eleni Tzirita Zacharatou and Volker Markl was accepted for presentation at the 19. Fachtagung für Datenbanksysteme für Business, Technologie und Web (BTW 2021) on September 20 – 24, 2021. Following the acceptance of a paper on fast CSV loading using GPUS, this is the second paper by researchers from the Database Systems and Information Management (DIMA) group at TU Berlin and the Intelligent Analytics for Massive Data (IAM) group at DFKI that will be presented at BTW 2021.