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Detecting Visual Elements in Historical Documents
Historians are increasingly in need of digital tools to process and extract information from electronic copies of historical sources. BIFOLD scientists developed YOLO (You Only Look Once).
AI facilitates breakthrough in cancer diagnostics
So-called sinonasal undifferentiated carcinomas (SNUCs) are extremely difficult to diagnose. A team led by Dr. Philipp Jurmeister and BIFOLD Fellow Prof. Frederick Klauschen from the Institute of Pathology at LMU, Prof. David Capper from Charité University Hospital together with BIFOLD Co-Director Prof. Klaus-Robert Müller, has developed an AI tool that reliably distinguishes tumors on the basis of chemical DNA modifications
DSP Best Paper Prize
BIFOLD researchers Prof. Klaus-Robert Müller, Prof. Wojciech Samek and Prof. Grégoire Montavon were honored by the journal Digital Signal Processing (DSP) with the 2022 Best Paper Prize. The DSP mention of excellence highlights important research findings published within the last five years.
Software Campus grant for two BIFOLD PhD students
Two BIFOLD PhD students, Lennart Behme and Haralampos Gavriilidis, have been awarded a Software Campus 2022 grant to conduct their own research projects as junior research leads. The Software Campus (SWC), funded by the German Federal Ministry of Education and Research (BMBF), is an executive development program aimed at shaping tomorrow’s senior IT executives. It is directed at outstanding doctoral students in computer science who are interested in taking on leadership responsibilities in the future. In doing so, the program combines cutting-edge scientific research with hands-on management experience in a new and innovative concept.
Cybersecurity under scrutiny
In cybersecurity research, machine learning (ML) has emerged as one of the most important tools for investigating security-related problems: However, a group of European researchers from TU Berlin, TU Braunschweig, University College London, King’s College London, Royal Holloway University of London, and Karlsruhe Institute of Technology (KIT)/KASTEL Security Research Labs, led by BIFOLD researchers from TU Berlin, have shown recently that research with ML in cybersecurity contexts is often prone to error.
ACM honors Volker Markl
The Association for Computing Machinery (ACM) is the world's first and largest educational and scientific computing society. Once a month, the category "People of ACM" highlights the unique scientific accomplishments and compelling personal attributes of ACM members who are making a difference in advancing computing as a science. Featured ACM member in October 2022 is the head of the Database Systems and Information Management group at TU Berlin and BIFOLD Co-Director Prof. Dr. Volker Markl.
Machine Learning on large dynamic graphs
The paper „Space-Efficient Random Walks on Streaming Graphs“, by Serafeim Papadias, Zoi Kaoudi, Jorge Arnulfo Quiane Ruiz, and Volker Markl has been accepted for publication at PVLDB 16 / VLDB 2023. In their paper, the researchers present Wharf, the first step towards scalable incremental machine learning on graphs.
More AI for Berlin
BIFOLD celebrates permanent federal-state funding with an international symposium and a ceremony.
A Poetic Dialogue of Art & Science
The Italian media artist Marco Barotti is BIFOLD artist in residence 2022. The goal of the residence program titled “Art of Entanglement” is to combine artistic and scientific perspectives on artificial intelligence. Marco Barotti will receive a total of 30,000 euros to create an artistic project of his choice, shaped by his regular interaction with BIFOLD researchers. “I am very excited about the opportunity to pursue a new dimension in my art working together with researchers at BIFOLD”, so Marco Barotti.
ACM SIGMOD 2022 Reproducibility Badge
The paper “ExDRa: Exploratory Data Science on Federated Raw Data” from a group of scientists, among them many Bifold scientists, has been successfully reproduced, and was awarded the “Results Reproduced” badge by ACM. This badge is applied to papers in which the main results of the paper have been successfully obtained by a person or team other than the author.