Prof. Dr. Volker Markl
Full Professor and Chair | Database Systems and Information Management (DIMA) Group at Technische Universität Berlin
Chief Scientist and Head | Intelligent Analytics for Massive Data (IAM) Research Group at the German Research Center for Artificial Intelligence (DFKI)
Co-Lead | Technical Enablers and Data Science Working Group of the German Platform for Artificial Intelligence („Plattform Lernende Systeme“), 2018.
Speaker | Forum Digital Technologies
Volker Markl is a German computer scientist, database systems researcher, and a full professor. He leads the Chair of Database Systems and Information Management and is Director of the Berlin Institute for the Foundations of Learning and Data at the Technische Universität Berlin. He is also Chief Scientist and Head of the Intelligent Analytics for Massive Data Research Group at the German Research Center for Artificial Intelligence in Berlin. He has served as the President of the VLDB Endowment and has held an adjunct professorship at the University of Toronto. He currenty serves on the academic advisory council to the Alexander von Humboldt Institute for Internet and Society as well as the scientific advisory board to Software AG. Additionally, he co-chairs the Technological Enablers and Data Science Interdisciplinary Working Group of the ‘Plattform Lernende Systeme,‘ a platform of leading experts who are developing a roadmap for the responsible use of self-learning systems and AI, sponsored by BMBF, the German Federal Ministry of Education and Research. He is a strong proponent of data literacy, systems-oriented research, and computer science education in general.
Volker’s research interests lie at the intersection of distributed systems, scalable data processing, and machine learning. He has published over 200 research papers at world-class scientific venues, and served as an editor for ten academic journals. He has given over 250 presentations in numerous industrial settings, research institutions, and major conferences worldwide, including keynotes at premier scientific venues, such as VLDB, ICDE, and DEBS. In 1999, he earned his PhD in Computer Science under the direction of Prof. Rudolf Bayer at the Technische Universität München.
Over the years, Volker has received numerous honors and awards. He was recognized as ACM Fellow for his contributions to query optimization, scalable data processing, and data programmability. He is a member of the Berlin-Brandenburg Academy of Sciences. In 2014, he was elected one of Germany’s leading “Digital Minds“ (Digitale Köpfe) by the German Informatics Society. Additionally, his achievements have been recognized by the European Union and industry. In particular, he received a European Information Society and Technologies Prize by the European Commission, the Trusted Cloud Award by the German Ministry of the Economy, an IBM Outstanding Technological Achievement Award, an IBM Faculty Award, and several Hewlett Packard Open Innovation Awards. Moreover, his research has received numerous recognitions, including Best Paper Awards at VLDB, SIGMOD, ICDE, and EDBT as well as two ACM SIGMOD Research Highlight Awards.
Volker has a well-established track record of innovation and technology transfer. His inventions have resulted in the awarding of eighteen patents. His doctoral research led to the development of the UB-Tree multidimensional indexing technology, which was transferred to Transaction Software, a German SME company, and garnered him a European IST Prize. For creating information marketplaces, he earned the Trusted Cloud Award from BMWi, the German Federal Ministry for Economic Affairs and Energy. Furthermore, many of his technological ideas were transferred into IBM commercial products, during the period he was industrial researcher at the IBM Almaden Research Center. Moreover, for supporting entrepreneurially-minded students and helping them to acquire seed funding, he was awarded an Innovation Supporter Award by TU Berlin.
From 2010 through 2019, Volker led the DFG funded Stratosphere project, which led to the establishment of Apache Flink, an open-source big data analytics system, and earned him a Humboldt Innovation Award. With a community of over 26,000 members and over 1000 code contributors, Flink is recognized as a highly flexible, scalable, and extensible processing framework for data streams that incorporates novel methods for fault tolerance. He has been co-founder, advisor, and mentor to several successful startups, including dataArtisans, Parstream, and Aklamio. In addition, he advises and collaborates with several IT companies, including IBM, SAP, Microsoft, Deutsche Telekom, HP, Oracle, Amazon, Huawei, Zalando, as well as many SMEs. Furthermore, he serves as an advisor to the German Federal Government and the European Union on Big Data and AI.
|ICDE Best Demonstration Award
|ICDE 2021 Best Paper Award;
|BTW 2021 Best Paper Award
|ACM SIGMOD 2020 Best Paper Award
|EDBT 2019 Best Paper Award
|BTW 2017 Best Paper Award
|EDBT 2017 Best Demonstration Award
|Germany´s “Leading Digital Mind” (“Digitale Köpfe”) Award
|VLDB Best Paper award
|IBM Faculty Award, a Trusted-Cloud Award for Information Marketplaces by the German Ministry of Economics and Technology
|IBM Shared University Research Grant
|HP Open Innovation Award
|IBM Outstanding Technological Achievement Award
|Pat Goldberg Memorial Best Paper Award
|2001 – 2006
|Seventeen Invention Achievement Awards, IBM
|2001 – 2006
|Four Invention-Plateau Awards, IBM
|Best Mentor Award, IBM
|European Information Society and Technology Prize
- Novel hardware architectures for information management
- Scalable processing and optimization of declarative data analysis programs
- Data infrastructures
- End-to-end machine learning
- Information marketplaces
- Technological enablers for responsible data management
- Scalable data science, including graph mining, text mining, and machine learning
- Berlin-Brandenburg Academy of Sciences and Humanities
- Scientific Advisory Board of Software AG
- Academic Advisory Council of Alexander von Humboldt Institute for Internet and Society’s (HIIG)
- Gesellschaft für Informatik (GI) – FG Datenbanken
- ACM Fellow
- Autonomic Task Force within the IEEE Computer Society
- Trustee Emeriti of the VLDB Endowment
- Founding Member of the Big Data Value Association/Big Data Value PPP
Dwi P. A. Nugroho, Philipp M. Grulich, Steffen Zeuch, Clemens Lutz, Stefano Bortoli, Volker Markl
Benchmarking Stream Join Algorithms on GPUs: A Framework and Its Application to the State of the Art
Serafeim Papadias, Zoi Kaoudi, Varun Pandey, Jorge-Arnulfo Quiane-Ruiz, Volker Markl
Xiao Li, Huan Li, Hua Lu, Christian S. Jensen, Varun Pandey, Volker Markl
Kaustubh Beedkar, Bertty Contreras-Rojas, Haralampos Gavriilidis, Zoi Kaoudi, Volker Markl, Rodrigo Pardo-Meza, Jorge-Arnulfo Quiané-Ruiz
Varun Pandey, Alexander van Renen, Eleni Tzirita Zacharatou, Andreas Kipf, Ibrahim Sabek, Jialin Ding, Volker Markl, Alfons Kemper
The installation CORALS by BIFOLD Artist in Residence Marco Barotti addresses the effects of climate change using coral reefs as an example. With the help of machine learning models, the artist modulates satellite data and shapes it into a mystical tapestry of sound.
The open-source big data stream analytics platform Apache Flink won the 2023 ACM SIGMOD Systems Award. The SIGMOD Systems award is one of the world's most prestigious awards in the field of data management. The origins of Apache Flink can be traced back to Berlin.
On May 26, 2023, BIFOLD welcomed a delegation from the National Center for High Performance Computing (NCHC).
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.
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.
BIFOLD celebrates permanent federal-state funding with an international symposium and a ceremony.
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.
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.
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.
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.
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).
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.
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.
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.
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.
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.
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.
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.
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.
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?”
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.
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.
TU Berlin, DFKI and NUS paper on parallelizing intra-window join on multicores was accepted at SIGMOD 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.
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.
TU Berlin and DFKI vision paper on data science ecosystem “Agora” was accepted for publication in SIGMOD record
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.
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.
Major extension of the EDBT 2019 best paper by TU Berlin and DFKI researchers accepted for publication in TODS
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.
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.
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.
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.
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.
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.
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.
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.
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).