Home >


Web trackers are widely present in governmental websites

Web cookies are widely spread.
C: istock

BIFOLD Researcher Prof. Dr. Georgios Smaragdakis with TU Berlin recent bachelor graduate Matthias Götze, and collaborators from IMDEA Software and Networks Institutes, and the Cyprus University of Technology performed a large-scale measurement study of more than 5,500 official government websites. The study shows that up to 90% of these official websites in some countries add third-party tracker cookies without user consent.
“We would have expected that governmental websites visited by millions of citizens every day comply with GDPR law and be held to the highest standards regarding respecting user privacy. Unfortunately, our study shows that this is not the case”, says BIFOLD Fellow Georgios Smaragdakis.

Multi-million Funding fo AI research “made in Berlin”

Berlin’s AI competence center the Berlin Institute for the Foundations of Learning and Data (BIFOLD) at Technische Universität Berlin (TUB) has now made the transition from project funding to permanent joint funding provided by the federal government and the State of Berlin. This sees the establishment of a national AI competence center in Berlin that will make an important contribution to the development and applications of artificial intelligence. Through a partnership with Charité – Universitätsmedizin Berlin, BIFOLD is set to become a cross-university central institute in the near future.

BIFOLD will receive institutional funding of 22 million euros annually from 1 July 2022.
C: istock

Facing an inconvenient truth

Jean-Pierre Seifert is professor of security in telecommunications at TU Berlin as well as a researcher at the Berlin Institute for the Foundations of Learning and Data. His research focuses on topics such as hardware security, cryptography technology, and quantum computers. He is also an established specialist for computer and communication security. Along with other experts he has been warning for some time now of the dangers of cyberattacks for private businesses and critical state infrastructures. Even before the start of the war in Ukraine his research demonstrated that almost all hardware solutions used in the commercial sector and even those intended to protect state high security areas do not function adequately.

“Too little importance and attention is given to IT security”, says Jean-Pierre Seifert.
C: pixabay

The shared scientific identity of Europe

T-SNE Visualization of the Sphaera table pages, represented as histograms by the bigram network. The two highlighted pages are numerically identical.
C: project sphere

The project Sphere: Knowledge System Evolution and the Shared Scientific Identity of Europe is one of the leading Digital Humanities projects, exploring a large corpus of more than 350 book editions about geocentric cosmology and astronomy from the early days of printing between the 15th and the 17th centuries (Sphaera Corpus) for about 76.000 pages of material. The relatively large size of this humanities dataset presents a challenge to traditional historical approaches, but provides a great opportunity to computationally explore such a large collection of books. In this regard, the Sphere project is an incubator of multiple Digital Humanities (DH) approaches aimed at answering various questions about the corpus, with the ultimate objective to understand the evolution and transmission of knowledge in the early modern period.

Flexible adjustment of computing workloads could improve carbon footprint of data centers

Many data centers are connected to so called microgrids.
C: pixabay

To reduce their carbon footprint, more and more computing systems are connected to microgrids to gain direct access to renewable energy sources. However, the local availability of solar and wind energy is highly variable and requires consumers to timely adapt their consumption to the current supply. Researchers from the Berlin Institute for the Foundation of Learning and Data (BIFOLD) have developed a new admission control approach that accepts flexible workloads such as machine learning training jobs only if they can be computed relying solely on renewable excess energy.

Two demo papers accepted at VLDB 2022

Two demonstration papers of BIFOLD researchers have been accepted at the 48th International Conference on Very Large Databases (VLDB). The VLDB 2022 will take place in Sydney, Australia (and hybrid) in September 05-09, 2022.

Wojciech Samek and Klaus-Robert Mueller published new book on XAI

To tap the full potential of artificial intelligence, not only do we need to understand the decisions it makes, these insights must also be made applicable. This is the aim of the new book “xxAI – Beyond Explainable AI”, edited by Wojciech Samek, head of the Artificial Intelligence department at the Fraunhofer Heinrich Hertz Institute (HHI) and BIFOLD researcher and Klaus-Robert Mueller, professor of machine learning at the Technical University of Berlin (TUB) and co-director at BIFOLD.

A framework to efficiently create training data for optimizers

A demo paper co-authored by Robin van de Water, Francesco Ventura, Zoi Kaoudi, Jorge-Arnulfo Quiane-Ruiz, and Volker Markl on “Farming Your ML-based Query Optimizer’s Food” presented at the virtual conference ICDE 2022 has won the best paper award.

NebulaStream aims to unify the cloud, the edge and the sensors

May, 12, 2022

More and more data will be generated by an exponentially increasing number of IoT devices.
C: iStock

NebulaStream, the novel, general-purpose, end-to-end data management system for the IoT and the Cloud, recently announced the release of NebulaStream 0.2.0., the closed-beta release. The System is developed and explored by a team of BIFOLD researchers led by Prof. Dr. Volker Markl. It addresses the unique challenges of the “Internet of Things” (IoT).

ACM SIGMOD Research Highlight Award

May, 5, 2022

The paper “Efficient Control Flow in Dataflow Systems: When Ease-of-Use Meets High Performance” of six BIFOLD researchers was honored with a 2021 ACM SIGMOD Research Highlights Award. 

“I want to move beyond purely ‘explaining’ AI”

April, 28, 2022

Prof. Wojciech Samek receives his certificate of appointment from the President of TU Berlin, Prof. Geraldine Rauch.
C: private

BIFOLD researcher Dr. Wojciech Samek has been appointed Professor of Machine Learning and Communications at TU Berlin with effect from 1 May 2022. Professor Samek heads the Department of Artificial Intelligence at the Fraunhofer Heinrich-Hertz-Institute. His goal is to further develop three areas: explainability and trustworthiness of artificial intelligence, the compression of neural networks, and so-called federated leaning. He aims to focus on the practical, methodological, and theoretical aspects of machine learning at the interface to other areas of application.

The Art of Entanglement

March, 17, 2022

The Berlin Institute for the Foundations of Learning and Data (BIFOLD), together with the Science Gallery at Technische Universität Berlin, has announced a new artist in residence program called “Art of Entanglement”. The goal of the program is to combine artistic and scientific perspectives of artificial intelligence.
The program is endowed with a gross total of 30,000 euros. The open call was published on sciencegallery.submittable.com. Applications are open to artists based in Berlin who are interested in working intensively with topics and scientists in the fields of Big Data Management and Machine Learning as well as their intersection.
The selected artist will have the opportunity to realize an artistic project of their choice at BIFOLD, the national Berlin Center of Excellence for Artificial Intelligence at TU Berlin, and the Science Gallery platform.

(Copyright: BIFOLD)

Successful seed funding for IoT projects

March, 15, 2022

The seed project established by Danh Le Phuoc focuses on IoT and Edge computing.
(Copyright: pixabay)

TU Berlin, Siemens AG (SAG) and University of Oxford (UoO) recently partnered in a trilateral seed fund to stimulate joint research project bids. One of the altogether five successful seed projects was initiated by BIFOLD Junior Fellow Dr. Danh Le Phuoc, a DFG principle investigator at TU Berlin, and focuses on IoT and Edge computing, in particular for smart factory, autonomous vehicle, smart city and smart energy network. The seed projects will run during 2022 and are aimed at developing large-scale public funding bids.

Function determines Form

February, 21, 2022

Inverse molecular design reverses the structure-property relationship.
(Copyright: Pixabay)

An interdisciplinary research group has developed an algorithm which uses AI to implement inverse chemical design and thus generates targeted molecules based on their desired properties. The BIFOLD researchers expect that such algorithms, used in concert with other AI-driven approaches and quantum chemical methods, can greatly accelerate the search for new molecules and materials in many practical areas.

Shining a Light into the Black Box of AI Systems

February, 17, 2022

Schematic representation of the different methods.

In the paper “NoiseGrad — Enhancing Explanations by Introducing Stochasticity to Model Weights,” to be presented at the 36th AAAI-22 Conference on Artificial Intelligence, a team of researchers, among them BIFOLD researchers Dr. Marina Höhne, Shinichi Nakajima, PhD, and Kirill Bykov, propose new methods to reduce visual diffusion of the different explanation methods, which have shown to make existing explanation methods more robust and reliable.

Lifting the curse of dimensionality for statistics in ML

December 21, 2021

(Copyright: Unsplash)

The paper “Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation” by BIFOLD researcher Dr. Robert A. Vandermeulen and his colleague Dr. Antoine Ledent, Technical University Kaiserslautern, was presented at the Conference on Neural Information Processing Systems (NeurIPS 2021). Their paper provides the first solid theoretical foundations for applying low-rank methods to nonparametric density estimation.

Tracking Spooky Action at a Distance

December 15, 2021

Naostrukturen von Molekülen
Being able to predict and model the individual steps of a chemical reaction at the molecular or even atomic level is a long-held dream of many material scientists.
(Copyright: istock.com/peterscheiber.media)

The use of AI in classical sciences such as chemistry, physics, or mathematics remains largely uncharted territory. Researchers from the Berlin Institute for the Foundation of Learning and Data (BIFOLD) at TU Berlin and Google Research have successfully developed an algorithm to precisely and efficiently predict the potential energy state of individual molecules using quantum mechanical data. Their findings, which offer entirely new opportunities for material scientists, have now been published in the paper “SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects” in Nature Communications. 

Benchmarking neural network explanations

December 15, 2021

Benchmarking neural network explanations
(Copyright: Wojciech Samek)

Neural networks have found their way into many every day applications. During the past years they reached excellent performances on various largescale prediction tasks, ranging from computer vision, language processing or medical diagnosis. Even if in recent years AI research developed various techniques that uncover the decision-making process and detect so called “Clever Hans” predictors – there exists no ground truth-based evaluation framework for such explanation methods. BIFOLD researcher Dr. Wojciech Samek and his colleagues now established an Open Source ground truth framework, that provides a selective, controlled and realistic testbed for the evaluation of neural network explanations. The work will be published in Information Fusion.

Two BIFOLD Papers Ranked as ESI Highly Cited and Hot Papers

December 12, 2021

Two machine learning papers by BIFOLD researchers received the “Essential Science indicators” (ESI) “Highly Cited” and “Hot Papers” labels for their impact in the science community.

Learning about Population Health from Twitter Texts

December 02, 2021

(Copyright: Unsplash)

Is it possible to learn about the health status of a population and potential side effect of medicationsby analyzing social media conversations? BIFOLD researchers tackled the challenge of making social media posts of medical laypersons concerning diseases and medications understandable for machines. At the BioCreative VII Challenge Evaluation Workshop 2021, they recently explored how a combination of background knowledge and a language transformer model can increase the precision of medical information extraction from Twitter texts.

BIFOLD Researchers Honored with BBAW Membership

December 02, 2021

At the “Einsteintag 2021” event on November 26, which honored Albert Einstein – prominent member of a predecessor institution of the Berlin-Brandenburg Academy of Sciences and Humanities (BBAW) – both BIFOLD Co-Director Volker Markl and BIFOLD Fellow Frank Noé were announced as new BBAW members.

Machine Learning Consultation

December 01, 2021

(Copyright: Unsplash)

Machine learning (ML) and artificial intelligence (AI) have permeated the sciences and large parts of working life. Today many people use machine learning techniques without being a proven expert. Consequently, many questions and problems arise while using these techniques. BIFOLD accommodates distinguished machine learning experts from different areas and offers a weekly consultation on machine learning for students, but also for companies and institutions.

BIFOLD Colloquium “Scalable and Fast Cloud Data Management”

Event date: December 06, 2021

Norbert Ritter (University of Hamburg), Felix Gessert (Baqend), and Wolfram Wingerath (Baqend) will talk about their scalable and fast cloud data management research at University of Hamburg and Software-as-a-Service company Baqend.

Science and Startups launches AI Initiative

November 23, 2021

Science & Startups is the association of the four startup services of Freie Universität Berlin, Humboldt-Universität zu Berlin, Technische Universität Berlin and Charité – Universitätsmedizin Berlin. Now they officially launched their new focus programme: K.I.E.Z. (Künstliche Intelligenz Entrepreneurship Zentrum). K.I.E.Z. will be carried out in close cooperation with the Berlin Institute for the Foundations of Learning and Data (BIFOLD).

United against Cyberattacks

November 19, 2021

DDOS ATTACK " and Alert icon on display of computer for management server in data server room
There is currently no effective solution to mitigate DDoS attacks.
(Copyright: istock.com/Anucha Cheechang)

BIFOLD Researchers, together with colleagues from Deutsche Commercial Internet Exchange (DE-CIX) and Brandenburg University of Technology, show that the exchange of information about ongoing cyberattacks has the potential to detect and mitigate substantially more attacks and protect critical parts of the Internet infrastructure.

Scheduling Computing Tasks can reduce Emission

November 12, 2021

(Copyright: Unsplash)

To reduce the carbon footprint of cloud computing, researchers from the Berlin Institute for the Foundation of Learning and Data (BIFOLD) investigated the potential of shifting delay-tolerant compute workloads, such as batch processing and machine learning jobs, to times where energy can be expected to be green. Their publication “Let’s Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud,” was now accepted at Middleware’21. 

Intelligent machines also need control

November 10, 2021

Dr. Marina Höhne
(Copyright: Christian Kielmann)

Dr. Marina Höhne, BIFOLD Junior Fellow, was awarded two million euros funding by the German Federal Ministry of Education and Research to establish a research group working on explainable artificial intelligence.

Award for paper on processing semantic data streams

October 29, 2021

Congratulations to BIFOLD Fellow Prof. Dr. Manfred Hauswirth and BIFOLD Junior Fellow Dr. Danh Le-Phuoc: At the International Semantic Web Conference 2021 (ISWC-2021), their paper “A Native and Adaptive Approach for Unified Processing of Linked Streams and Linked Data” achieved 2nd place for the “SWSA Ten-Year Award” with an honourable mention.

New Berlin Cell Hospital announced

October, 25, 2021

The Berlin Cell Hospital brings together experts from clinical practice, biomedical research, technology, data science, mathematics and engineering science. (Copyright: Unsplash)

On October 13, 2021, at an event celebrating the 200th birthday of the famous pathologist, physician and socialist politician Rudolf Virchow, the Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) and the Charité – Universitätsmedizin Berlin, together with the Berlin Institute for the Foundations of Learning and Data (BIFOLD) and several other Berlin research institutions declared the founding of the Berlin Cell Hospital. The new Cell Hospital wants to shape and develop the cell-based medicine of the future.

Preventing Image-Scaling Attacks on Machine Learning

October 07, 2021

BIFOLD Fellow Prof. Dr. Konrad Rieck, head of the Institute of System Security at TU Braunschweig, and his colleagues provide the first comprehensive analysis of image-scaling attacks on machine learning, including a root-cause analysis and effective defenses. Konrad Rieck and his team could show that attacks on scaling algorithms like those used in pre-processing for machine learning (ML) can manipulate images unnoticeably, change their content after downscaling and create unexpected and arbitrary image outputs. The work was presented at the USENIX Security Symposium 2020.

In Search for Algorithmic Fairness

September 21, 2021

Statue of Lady justice
BIFOLD researchers suggest a new machine learning model that leads to both: high accuracy and fairness. (Copyright: Pixabay)

Artificial intelligence (AI) has found its way into many work routines – be it the development of hiring procedures, the granting of loans, or even law enforcement. However, the machine learning (ML) systems behind these procedures repeatedly attract attention by distorting results or even discriminating against people on the basis of gender or race. “Accuracy is one essential factor of machine learning models, but fairness and robustness are at least as important,” knows Felix Neutatz, a BIFOLD doctoral student in the group of Prof. Dr. Ziawasch Abedjan, BIFOLD researcher and former professor at TU Berlin who recently moved to Leibniz Universität Hannover. Together with Ricardo Salazar Diaz they published “Automated Feature Engineering for Algorithmic Fairness“, a paper on fairness of machine learning models in Proceedings of the VLDB Endowment.

New Type of Algorithm for Brain Research

September 07, 2021

The new type of algorithm may help to understand which brain regions directly interact with one another.
(Copyright: Unsplash)

Together with an international team of researchers from Mayo Clinic BIFOLD Co-Director Prof. Dr. Klaus-Robert Müller developed a new type of algorithm to explore which regions of the brain interact with each other. Their results could improve brain stimulation devices to treat disease. For millions of people with epilepsy and movement disorders such as Parkinson’s disease, electrical stimulation of the brain already is widening treatment possibilities. In the future, electrical stimulation may help people with psychiatric illness and direct brain injuries, such as stroke.

Using Machine Learning in the Fight against COVID-19

September 06, 2021

Visualization of the SARS-CoV-2 virus.
(© Unsplash / Fusion Medical Information)

BIFOLD Fellow Prof. Dr. Frank Noé identified a potential drug candidate for the therapy of COVID-19. Among other methods, they used deep learning models and molecular dynamics simulations in order to identify the drug Otamixaban as a potential inhibitor of the human target enzyme which is required by SARS-CoV-2 in order to enter into lung cells. According to their findings, Otamixaban works in synergy with other drugs such as Camostat and Nafamostat and may present an effective early treatment option for COVID-19. Their work was now published in Chemical Science.

SIGCOMM 2021 Best Paper: Internet Hypergiants Expand into End-User Networks

August 26, 2021

Percentages of internet users that can be served by Hypergiants’ off-nets in their networks.
(Copyright: Petros Gigis et al.)

BIFOLD Fellow Prof. Dr. Georgios Smaragdakis and his colleagues received the prestigious ACM SIGCOMM 2021 Best Paper Award for their research into the expansion of Hypergiant’s off-nets. They developed a methodology to measure how a few extremely large internet content providers deploy more and more servers in end-user networks over the last years. Their findings indicate changes in the structure of the internet, potentially impacting network end-user experience and neutrality regulations.

VLDB2021: BOSS Workshop features Open Source Big Data Systems

August 16, 2021

(© BOSS Workshop organizers)

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

August 10, 2021

Visualization of sea surface temperature and salinity based on EO data. (Image: European Space Agency)

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

July 22, 2021

LTR: Dr. Kaustubh Beedkar, Dr. Jan Hermann, Dr. Marina Marie-Claire Höhne, Dr. Danh Le Phuoc, Dr. Kristof Schütt, Dr. Eleni Tzirita Zacharatou (© BIFOLD)

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

July 13, 2021

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

July 1, 2021

Logo from the Sphaera Project „Prudentia“. Fresco. Casa Minerbi e del Sale, Ferrara (Italy), 13th cent., detail. From Ragghianti, Carlo R. 1970. Gli affreschi di casa Minerbi a Ferrara. S. Miniato: Cassa di Risparmio di S. Miniato

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

June 23, 2021

Within a single week, Internet traffic volume increased by 25 percent. (© Unsplash)

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

June 11, 2021

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

May 31, 2021

(© Pixabay)

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

May 12, 2021

(© Stefan Chmiela)
(© Steffen Zeuch)

Research Group leaders Dr. Stefan Chmiela (l) and Dr. SteffenZeuch (r).

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 its first cohort with 12 PhD candidates

May 05, 2021

First meeting with the new BIFOLD Graduate School PhD candidates, the programme organizers and both BIFOLD directors.

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.

Using Math to Reduce Energy Consumption

April 29, 2021

Prof. Dr. Klaus-Robert Müller
(© Christian Kielmann)

Klaus-Robert Müller, professor of machine learning at TU Berlin and Co-Director of the Berlin Institute for the Foundations of Learning and Data (BIFOLD), discusses computation time as a climate killer and his predictions for science in 80 years.

ICDE 2021 honors BIFOLD researchers with Best Paper Award

April 21, 2021

(© Gábor E. Gévay)

The 37. IEEE International Conference on Data Engineering (ICDE) 2021 honored the paper “Efficient Control Flow in Dataflow Systems: When Ease-of-Use Meets High Performance” of six BIFOLD researchers with the Best Paper Award. Gábor E. Gévay, Tilmann Rabl, Sebastian Breß, Lorand Madai-Tahy, Jorge-Arnulfo Quiané-Ruiz and Volker Markl were honored during the award session of the conference on April 21, 2021.

BTW 2021 Best Paper Award and Reproducibility Badge for TU Berlin Data Science Publication

April 20, 2021

The research paper “Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing” by Alexander Kumaigorodski, Clemens Lutz, and Volker Markl received the Best Paper Award of the 19th Symposium on Database Systems for Business, Technology and Web (BTW 2021). On top, the paper received the Reproducibility Badge, awarded for the first time by BTW 2021, for the high reproducibility of its results.

Tapping into Nature’s Wisdom

April 19, 2021

The image shows the structure of the biosensors, which is based on the leaf structure.
(© University of Korea)

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”

March 24, 2021

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“

March 22, 2021

BIFOLD Co-Director Prof. Dr. Volker Markl
(© Volker Markl)

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

March 10, 2021

Dr. Wojciech Samek
(© Wojciech Samek)

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.

Making the role of AI in Medicine Explainable

March 09, 2021

An AI identifies tumor-infiltrating lymphocytes (TiLs) in a breasi carcinoma. The headmap on the right highlights TiLs in red.
(Original pictures: © Frederick Klauschen)

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

February 23, 2021

Dr. Grégoire Montavon with the 2020 Pattern Recognition Best Paper Award in hand.
(© Grégoire Montavon)

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

February 05, 2021

Dr. Samek (l.) and Prof. Müller in front of an XAI demonstrator at Fraunhofer HHI. (© TU Berlin/Christian Kielmann)

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

January 15, 2021

Prof. Dr. Volker Markl
(© TU Berlin /PR/Simon)

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

January 13, 2020

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

January 12, 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.

TU Berlin, DFKI and NUS Paper on Parallelizing Intra-Window Join on Multicores was Accepted at SIGMOD 2021

January 05, 2021

The paper “Parallelizing Intra-Window Join on Multicores: An Experimental Study” by researchers from TU Berlin, DFKI, National University of Singapore and ByteDance was accepted for presentation at the ACM SIGMOD/PODS International Conference on Management of Data (SIGMOD/PODS 2021), which will take place from June 20 – 25, 2021 in Xi’an, China. This is the first comprehensive study on this topic.

Researchers at FU Berlin Solve Schroedingers Equation with new Deep Learning Method

December 29, 2020

BIFOLD Principal Investigator Prof. Dr. Frank Noé and Senior Researcher Dr. Jan Hermann of the Artificial Intelligence for the Sciences group at Freie Universität Berlin developed a new, exceptionally accurate and efficient method to solve the electronic Schroedinger equation. Their approach could have a significant impact on the future of quantum chemistry.

The BigEarthNet Archive now Contains Sentinel-1 Satellite Images

December 28, 2020

The satellite image benchmark archive BigEarthNet, developed by the Remote Sensing Image Analysis (RSIM) and Database Systems and Information Management (DIMA) groups at TU Berlin, has been enriched by Sentinel-1 image patches. This enhances its potential for deep learning with geo data.

© G. Sumbul, M. Charfuelan, B. Demir, V. Markl

TU Berlin and DFKI Vision Paper on Data Science Ecosystem “Agora” was Accepted for Publication in SIGMOD Record

December 22, 2020

A vision paper by researchers of the Database Systems and Information Management group (DIMA) at TU Berlin and the Intelligent Analytics for Massive Data (IAM) group at DFKI was accepted for publication in SIGMOD Record. In their paper the authors describe their vision towards a unified ecosystem that brings together data, algorithms, models, and computational resources and provides them to a broad audience.

PD Dr. Alexander Meyer Appointed as a Professor for „Clinical Applications of AI and Data Science“ at Charité

December 17, 2020

PD Dr. Alexander Meyer
(© Alexander Meyer)

PD Dr. Med. Alexander Meyer, BIFOLD Associated Investigator and Chief Medical Information Officer at German Heart Center Berlin, was appointed as a W2 professor for „Clinical Applications of AI and Data Science“ at Charité Berlin.
His professorship will focus on the application of AI and Data Science in cardiovascular medicine. The Berlin Institute for the Foundations of Learning and Data supports the professorship with two full-time positions for research assistants.

BIFOLD PI Prof. Dr. Giuseppe Caire Receives 2021 Leibniz Prize

December 11, 2020

Prof. Dr. Giuseppe Caire
(© Giuseppe Caire)

BIFOLD’s Principal Investigator Prof. Dr. Giuseppe Caire, head of the Chair of Communications and Information Theory (CommIT) at TU Berlin, has been awarded the 2021 Gottfried-Wilhelm-Leibniz-Prize. On 10 December 2020, the German Research Foundation (DFG) announced the recipients of Germany’s most important research award. Each individual award is endowed with a maximum of 2.5 million euros annually.

New Study by BIFOLD Researchers: How did COVID-19 impact Internet Traffic?

December 10, 2020

Figure1: During the first phase of the pandemic, web conferencing and gaming related traffic increased.
(© Anja Feldmann et al.)

BIFOLD PIs Prof. Dr. Anja Feldmann and Prof. Dr. Georgios Smaragdakis (INET group at TU Berlin) published a research study on the impact of the COVID-19 pandemic on the Internet traffic in the Proceedings of the ACM Internet Measurement Conference (IMC ’20).

BIFOLD PI Dr. Samek talks about Explainable AI at NeurIPS 2020 Social Event

December 09, 2020

Dr. Wojciech Samek
(© Wojciech Samek)

BIFOLD Principal Investigator Dr. Wojciech Samek (Fraunhofer HHI) talked about explainable and trustworthy AI at the “Decemberfest on Trustworthy AI Research” as part of the annual Conference on Neural Information Processing Systems (NeurIPS 2020). NeurIPS is a leading international conference on neural information processing systems, Machine Learning (ML) and their biological, technological, mathematical, and theoretical aspects.

Join the Symposium on the Web and Internet Policy on December 09, 2020!

November 27, 2020

(© Symposium on the Web and Internet Policy)

BIFOLD Principal Investigator Prof. Dr. Georgios Smaragdakis (Chair of the Internet Network Architectures group at TU Berlin) and Dr. Volker Stocker (Leader of the Work and Cooperation in the Sharing Economy research group at Weizenbaum Institute) are organizing a symposium on web and internet policies.

Feel free to register here!

TUB Distributed and Operating Systems Researchers will Offer Multiple Presentations at IEEE Big Data 2020

November 27, 2020

Three papers by researchers of the Distributed and Operating Systems group at TU Berlin, led by BIFOLD Principal Investigator Prof. Dr. Odej Kao, have been accepted for presentation at the 2020 IEEE International Conference on Big Data (Big Data 2020) and related workshops. The Conference will take place from December 10 – 13, 2020.

Charité ICM Researcher Achieves First Place in the MICCAI 2020 CADA-RRE Challenge

November 26, 2020

© grand-challenge.org

Matthias Ivantsits of the Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine (ICM) at Charité – Universitätsmedizin Berlin was ranked first place in the CADA sub-challenge for rupture risk estimation (RRE) of cerebral aneurysms.

Fast CSV Loading Using GPUs – TUB and DFKI Paper Accepted at BTW 2021

November 26, 2020

A paper on the accelerated loading of CSV data using GPUs and RDMA by researchers from the Database Systems and Information Management Group (DIMA) at TU Berlin and the Intelligent Analytics for Massive Data (IAM) research group at DFKI was accepted at the 19th symposium “Database Systems for Business, Technology and Web” (BTW 2021), which will take place from September 20 – 24, 2021.

TUB Internet Network Research Papers Accepted at CoNEXT 2020 and COVID-19 Network Impacts Workshop 2020

November 25, 2020

Papers by researchers in the Internet Network Architectures (INET) group at TU Berlin, headed by Prof. Dr. Georgios Smaragdakis, were accepted or presentation or publication at CoNEXT 2020, COVID-19 Network Impacts Workshop 2020 and IEEE Transactions on Network and Service Management, 2020.

BIFOLD Researchers are Among the Most Cited Worldwide

November 23, 2020

BIFOLD Co-Director Prof. Dr. Klaus-Robert Müller and Principal Investigators Prof. Dr. Giuseppe Caire and Prof. Dr. Frank Noé are featured in the 2020 Highly Cited Researchers™ list, either Cross-Field or in the Computer Sciences.

Major Extension of the EDBT 2019 Best Paper by TU Berlin and DFKI Researchers Accepted for Publication in TODS

November 09, 2020

The paper “Scotty: General and Efficient Open-Source Window Aggregation for Stream Processing Systems” by J. Traub et al. was accepted for publication at ACM Transactions on Database Systems (TODS). This extended journal paper is a major extension of the EDBT best paper titled Efficient “Window Aggregation with General Stream Slicing” from 2019 by the same authors from the DIMA group and the Intelligent Analytics for Massive Data (IAM) group at DFKI. Among other extensions, the new journal paper was extended with detailed algorithm specifications, API-examples, and examples for using Scotty in different streaming systems.

Multiple Internet Network Architectures Papers presented at IMC ’20

November 05, 2020

BIFOLD’s Principal Investigators Prof. Dr. Smaragdakis, Prof. Dr. Anja Feldmann and other researchers from the Internet Network Architectures (INET) group at TU Berlin presented four papers at the 20th ACM Internet Measurements Conference (IMC ‘20), which took place from October 27 – 29, 2020 as a virtual event. Among other topics, they examined the effects of the first pandemic lockdown on Internet traffic.

“Data is the new soil!” – Interview with Prof. Markl

November 03, 2020

(© Volker Markl)

In an interview with the German newspaper ‘Der Tagesspiegel’, one of BIFOLD’s directors, Prof. Dr. Markl, explains necessary steps to drive Europe forward in terms of data sovereignity and innovation ecosystems.

BIFOLD Researchers at DHZB Developed AI to Predict Kidney Failure

November 02, 2020

BIFOLD Associated Investigator PD Dr. Meyer (DHZB) and Principal Investigator Prof. Dr. Kühne (DHZB, Charité) developed a recurrent neural network (RNN) which is able to predict severe kidney failure better than human professionals. The corresponding paper was published in “Nature Partner Journal (npj) Digital Medicine.”

Paper über neues Sketch-Maintenance-System zur Veröffentlichung in PVLDB Vol. 14 akzeptiert

October 16, 2020

The Paper “Scotch: Generating FPGA-Accelerators for Sketching at Line Rate” by Martin Kiefer, Ilias Poulakis, Sebastian Breß and Volker Markl will be featured in Proceedings of the VLDB Endowment (PVLDB), Volume 14. In their paper, the authors propose Scotch, a novel system for accelerating sketch maintenance using the custom FPGA hardware.

BIFOLD Database Systems Research Papers were Accepted at CIDR 2021

October 16, 2020

Researchers at the Database Systems and Information Management (DIMA) group at TU Berlin and the Intelligent Analytics for Massive Data (IAM) group at DFKI have been informed that their papers were accepted for presentation at the 11th Annual Conference on Innovative Data Systems Research (CIDR ’21) which will be held as a virtual event on January 11-15, 2021.

BIFOLD Research Paper on Machine Learning for Quantum Chemistry published in Nature Communications

October 16, 2020

The Paper “Quantum chemical accuracy from density functional approximations via machine learning” by Mihail Bogojeski, Leslie Vogt-Maranto, Mark E. Tuckerman, Klaus-Robert Müller, Kieron Burke was published in Nature Communications. In this paper, the authors leverage machine learning to calculate coupled-cluster energies from DFT densities, reaching much better quantum chemical accuracy on test data than achieved with previous available methods. Moreover, their approach significantly reduced the amount of training data required.

Deep Reinforcement Learning enables Robot to Beat Humans in Olympic Sport

September 25, 2020

(© Korea University)

A Deep Reinforced Learning framework, developed by BIFOLD Co-director Prof. Dr. Klaus-Robert Müller and his colleagues at the Department of Brain and Cognitive Engineering of the Korea University in Seoul, enabled the robot “Curly” to beat top-level athletes in the Olympic sport of curling. The work was recently featured in Nature Research Highlights.

Using Machine Learning to Combat the Coronavirus

September 23, 2020

A joint team of researchers from TU Berlin and the University of Luxembourg is exploring why a spike protein in the SARS-CoV-2 virus is able to bind much more effectively to human cells than other coronaviruses. Google.org is funding the research with 125,000 US dollars.

Prof. Müller Presents Berlin’s AI Research Network at ELLIS Berlin Inauguration

September 17, 2020

In a virtual inauguration event, the European Laboratory for Learning and Intelligent Systems (Ellis) network welcomed new regional network units.  Prof. Dr. Klaus-Robert Müller presented the AI research network in Berlin as well as BIFOLD’s approach of combining Machine Learning and Big Data research.

TU Berlin and DFKI Database Systems Researchers Offer Multiple Presentations at VLDB 2020

September 15, 2020

Alexander Renz-Wieland presents his Paper “Dynamic Parameter Allocation in Parameter Server” at VLDB 2020.
(© Alexander Renz-Wieland)

Researchers at TU Berlin Database Systems and Information Management (DIMA) group and Intelligent Analytics for Massive Data (IAM) group at DFKI presented one full paper, one demo paper and three PhD thesis papers at the 46th International Conference on Very Large Databases (VLDB 2020).

Bauen mit Molekülen dank Reinforced Learning

September 15, 2020

(© Forschungszentrum Jülich / Dr. Christian Wagner)

In a cooperation between the Machine Learning group at TU Berlin, led by Prof. Dr. Klaus-Robert Müller (Co-Director BIFOLD) and Jülich’s Quantum Nanoscience institute, led by Prof. Dr. Stefan Tautz, researchers enabled a robot to selectively grip and move single molecules from a layer, by applying reinforced learning. This work was announced a Scientific Breakthrough by the Falling Walls Foundation at this years Berlin Science Week.

An Overview of the Current State of Research in BIFOLD

August 06, 2020

Since the official announcement of the Berlin Institute for the Foundations of Learning and Data in January 2020, BIFOLD researchers achieved a wide array of advancements in the domains of Machine Learning and Big Data Management as well as in a variety of application areas by developing new Systems and creating impactfull publications. The following summary provides an overview of recent research activities and successes.

Newest work on the NebulaStream System by Database Systems Researchers of TU Berlin and DFKI will be Presented at VLIoT 2020

July 16, 2020

The Paper “NebulaStream: Complex Analytics Beyond the Cloud” by Steffen Zeuch et al. was accepted for presentation at the 2020 International Workshop on Very Large Internet of Things (VLIoT 2020). VLIoT 2020 will take place in conjunction with the VLDB 2020 conference.
In this paper, the NebulaStream (NES) project team in DFKI’s IAM group and TU Berlin’s DIMA group shows why there is a need for a new End-to-End data processing systems for the Internet of Things (IoT).

TU Berlin Datalog Research Paper was Accepted for Presentation at LSGDA 2020

July 09, 2020

The Paper “Distributed Graph Analytics with Datalog Queries in Flink” by TU Berlin Database Systems Reasearchers Muhammad Imran, Gábor Gévay, Volker Markl will be presented at the 2nd International Workshop on Large Scale Graph Data Analytics (LSGDA 2020) in conjunction with the 2020 VLDB Conference in Tokyo, Japan, at September 4, 2020.

TU Berlin Master’s student wins 2nd place at the SIGMOD 2020 Student Research Competition

July 01, 2020

TU Berlin’s student Hendrik Makait reached the 2nd place at the ACM SIGMOD 2020 Student Research Competition at the 2020 ACM SIGMOD/PODS International Conference on the Management of Data with his paper “Rethinking Message Brokers on RDMA and NVM”. This is a joint work with the Data Engineering Systems Group at the Hasso Plattner Institute in Potsdam led by Prof. Rabl.

Prof. Dr. Kutyniok coordinates new DFG priority program on artificial neural networks

June 18, 2020

Prof. Dr. Gitta Kutyniok is coordinator of the new DFG (German Research Foundation) priority program „Theoretical Foundations of Deep Learning“, which aims to develop a comprehensive theoretical basis for artificial neural networks.

Dr. Huziel E. Sauceda nominated Reviewer of the Month by Communications Physics

June 17, 2020

Dr. Huziel E. Sauceda, postdoctoral researcher in Prof. Dr. Klaus-Robert Müller’s group, was nominated as Reviewer of the month by the Nature Research journal Communications Physics.

Database Systems Research Paper Accepted for Publication in PLVDB Vol. 13

June 16, 2020

The Paper “Dynamic Parameter Allocation in Parameter Servers” authored by Alexander Renz-Wieland, Rainer Gemulla, Steffen Zeuch and Volker Markl from was accepted for publication in Proceedings of the VLDB Endowment Vol. 13.

Cloud Computing contributes to Cancer Research

June 04, 2020

PCAWG, the largest cancer research consortium in the world, has set itself the task of improving our understanding of genetic mutations in tumors. A new study by the international research group, to which researchers in BIFOLD senior researcher Dr. Roland Schwarz’ group at the Max Delbrück Center for Molecular Medicine (MDC) substantially contributed, is now being published in the journal Nature.

New Research Fellow Olga Nicolaeva

June 04, 2020

Prof. Dr. Matteo Valleriani’s research group at MPIWG will expand by one research fellow: Olga Nicolaeva. In the frame of BIFOLD they will create a predictive Machine Learning model, which is able to establish a causal connection between distribution of ‘knowledge atoms’ (illustrations, tables, text parts) in the corpus of early modern textbooks on geocentric cosmology.

Paper on Adaptive Sampling and Filtering for IoT accepted at DEBS 2020

June 02, 2020

The paper “A Survey of Adaptive Sampling and Filtering Algorithms for the Internet of Things”, authored by D. Giouroukis et al. has been accepted for presentation at the 14th ACM International Conference on Distributed and Event-Based Systems (DEBS 2020), 13. – 17. July 2020 in Montreal, Canada.

BIFOLD-Forschende Erhalten SIGMOD 2020 Best Paper Award

May 22, 2020

Database systems researchers at TU Berlin, HPI and DFKI were highly successful this year. Four of their papers were accepted at the 2020 ACM SIGMOD/PODS International Conference on the Management of Data. And, in particular, one of the paper’s received the 2020 ACM SIGMOD Best Paper Award. The paper entitled “Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects,” by Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl (now at HPI), and Volker Markl explores the use of GPUs to accelerate database query processing.

Machine Learning meets quantum physics

May 13, 2020

BIFOLD researchers contributed to an in-depth referenced work on the physics-based machine learning techniques that model electronic and atomistic properties of matter.

Researchers in Prof. Abedjan’s group win SIGMOD Reproducibility Award

May 6, 2020

The paper “Raha: A Configuration-Free Error Detection System” by Mohammad Mahdavi, Ziawasch Abedjan, Raul Castro Fernandez, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, and Nan Tang won the ACM SIGMOD Most Reproducible Paper Award.

Join the MICCAI 2020 CADA challenge!

April 28, 2020

This year’s MICCAI Conference on Medical Image Computing and Computer Assisted Intervention in Peru will feature Grand Challenges in biomedical image analysis. In Partnership with Charité, Fraunhofer MEVIS and Helios, BIFOLD supports the CADA challenge on the automated and semi-automated analysis of image data of cerebral aneurysms.

Three papers presented at EDBT 2020

April 14, 2020

Researchers in TU Berlin’s Database Systems and Information Management (DIMA) Group and DFKI’s Intelligent Analytics for Massive Data (IAM) Group presented three systems papers at EDBT 2020, the 23rd International Conference on Extending Database Technology, held from March 30 to April 2. Originally planned to take place in Copenhagen, Denmark, this year’s EDBT conference was held online instead.

European AI research network ELLIS established a new Unit at TU Berlin

April 14, 2020

In positive response to a request by Prof. Dr. Klaus-Robert Müller (head of the Machine Learning Department at TU Berlin and one of the directors of BIFOLD) and other scientists, the Technische Universität Berlin became part of the European AI research network European Laboratory for Learning and Intelligent Systems (ELLIS).

Four papers authored by TU Berlin and DFKI researchers have been accepted at SIGMOD 2020

March 24, 2020

Data management systems researchers in the Database Systems and Information Management (DIMA) Group at TU Berlin and the Intelligent Analytics for Massive Data (IAM) Group at DFKI (the German Research Institute for Artificial Intelligence) were informed that their papers have been accepted at the 2020 ACM SIGMOD/PODS International Conference on the Management of Data.

BIFOLD officially announced

(© TU Berlin / Felix Noak)

January 15, 2020

On January 15, 2020 the Berlin Institute for the Foundations of Learning and Data (BIFOLD) was officially announced at Forum Digital Technologies in Berlin. Please also see the official press release of the Federal Ministry of Education and Research and Technische Universität Berlin (both in German).