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© Library of the MPI for the History of Science
Digital Humanities| December 05, 2022

Detecting Visual Elements in Historical Documents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).

© Jurmeister et al.
Machine Learning| November 30, 2022

AI facilitates breakthrough in cancer diagnostics

So-called sinonasal undifferentiated carcinomas (SNUCs) are extremely difficult to diagnose. An interdisciplinary team of researchers has developed an AI tool that reliably distinguishes tumors on the basis of chemical DNA modifications 

Machine Learning| November 14, 2022

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 Haralampos Gavriilidis and Lennart Behme
© TUBerlin / Montage BIFOLD
Data Management| November 10, 2022

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.


© pixabay
November 02, 2022

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.

Prof. Dr. Volker Markl
Data Management| October 21, 2022

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. 

Data Management| October 20, 2022

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.

(C) BIFOLD/Michael Setzpfandt
BIFOLD Update| September 16, 2022

More AI for Berlin

BIFOLD celebrates permanent federal-state funding with an international symposium and a ceremony.

Artist in Residence| September 01, 2022

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.

Data Management| August 24, 2022

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.