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VLDB2021: BOSS Workshop features Open Source Big Data systems
BIFOLD researchers will present three full research papers as well as three demo papers at the 47th International Conference on Very Large Data Bases (VLDB 2021), which will take place from August 16 – 29, 2021. In conjunction with VLDB, BIFOLD researchers also co-organize the BOSS 2021 workshop on open source big data systems.
Earth Observation data for Climate Change research
Many environmental reports are based on the analysis of satellite images. BIFOLD researchers are creating AgoraEO, an infrastructure for Earth Observation (EO) data that enables federated analysis across different platforms, making modern EO technology accessible to all scientists and society, thus promoting climate change innovation worldwide.
BIFOLD welcomes the first six Junior Fellows
The Berlin Institute for the Foundations of Learning and Data is very pleased to announce the first six BIFOLD Junior Fellows. They were selected for the excellence of their research and are already well-established researchers in the computer sciences. In addition, their research interests show exceptional potential for BIFOLD’s research goals, either by combining machine learning and data management or by bridging the two disciplines and other research areas. The first six Junior Fellows will cover a broad range of research topics during their collaboration with BIFOLD.
Higher impact through reproducibility
Modern science is based on objectiveness. Experimental results should be repeatable by any scientist, provided they use the same experimental setup. Since 2008, the SIGMOD conference, the international leading conference in management of data, awards the reproducibility badge to signify that a scientific work has been successfully reproduced by a third-party reviewer. In 2021, the paper “Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects” by BIFOLD researcher Clemens Lutz was awarded a prestigious reproducibility badge.
In search of Europe’s scientific identity
In the past, scholars used to pore over dusty tomes. Today Dr. Matteo Valleriani, group leader at the Max Planck Institute for the History of Science as well as honorary professor at TU Berlin and fellow at the Berlin Institute for the Foundations of Learning and Data (BIFOLD), uses algorithms to group and analyze digitized data from historical works. The term used to describe this process is computational history. One of the goals of Valleriani’s research is to unlock the mechanisms involved in the homogenization of cosmological knowledge in the context of studies in the history of science.
COVID-19: A stress test for the internet
Following an announcement of the WHO, who declared the coronavirus a global pandemic, governments around the world began enacting stay-at-home orders, regulations for working from home and homeschooling. Within a single week, Internet traffic volume increased by 25 percent – an increase which under normal circumstances is usually observed over the course of a year. Taking account of increased use during the second lockdown in fall 2020, the overall use of Internet services in 2020 increased between 35 and 50 percent, depending on the network. An international, interdisciplinary group of researchers led by Professor Dr. Georgios Smaragdakis, professor of Internet measurement and analysis at TU Berlin and Fellow of the Berlin Institute for the Foundations of Learning and Data (BIFOLD), has published these figures and other findings in a paper in Communications of the Association for Computing Machinery (ACM). The leading professional association recently named the paper a research highlight.
ACM SIGMOD 2021: 7 Data Management Papers Accepted
The upcoming 2021 ACM International Conference on the Management of Data (SIGMOD) – a top ranked international conference on database systems and information management – accepted seven papers submitted by BIFOLD Researchers. Large amounts of high-quality data are the backbone of modern machine learning applications in research, industry, and sectors, like medicine and mobility. To enable the next generation of Artificial Intelligence applications, an increasing number of different data sources need to be accessed and analyzed in a shorter period of time, while reducing computation costs, maintaining fault tolerance, and achieving high data quality. The group of BIFOLD Researchers, led by BIFOLD Co-Director Prof. Dr. Volker Markl, tackled some of these data management challenges and developed innovative solutions.
New cutting-edge IT infrastructure
A future-proof IT infrastructure is increasingly becoming a decisive competitive factor – this applies not only to companies, but especially to research. In recent months, BIFOLD has been able to invest around 1.8 million euros in new research hardware, thereby significantly increasing the institute’s computing capacity. This cutting-edge IT infrastructure was financed by the German Federal Ministry of Education and Research (BMBF).
New BIFOLD research groups established
The Berlin Institute for the Foundations of Learning and Data (BIFOLD) set up two new Research Training Groups, led by Dr. Stefan Chmiela and Dr. Steffen Zeuch. The goal of these new research units at BIFOLD is to enable a junior researcher to conduct independent research and prepare him for a leadership position. Initial funding includes their own position as well as two PhD students and/or research associates for three years.
BIFOLD Graduate School launches it's first cohort with 12 PhD candidates
In time for the summer semester 2021, the Berlin Institute for the Foundations of Learning and Data (BIFOLD) announced the launch of its Graduate School (GS): 12 PhD students from France, Russia and Germany, among them four women, make up the first cohort. The scholarship holders have obtained their master’s degrees in physics, computer science or bioinformatics; two of them are currently researching at Freie Universität Berlin, one at Universität Potsdam and nine at Technische Universität Berlin.