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Head of the Research Department Intelligent Analytics for Massive Data

Prof. Dr. Volker Markl

Organizational unit Intelligent Analytics for Massive Data
Contact

Prof. Dr. Volker Markl

Publications

Satellite Image Search in AgoraEO

Ahmet Kerem Aksoy; Pavel Dushev; Eleni Tzirita Zacharatou; Holmer Hemsen; Marcela Charfuelan Oliva; Jorge Arnulfo Quiane Ruiz; Begüm Demir; Volker Markl

In: Fatma Ozcan; Juliana Freire; Xuemin Li (Hrsg.). Proceedings of the 48th International Conference on Very Large Databases. International Conference on Very Large Data Bases (VLDB-2022), September 5-9, Sydney, Australia, Pages 3646-3649, Vol. 15, No. 12, VLDB Endowment Inc, 8/2022.

To the publication

NebulaStream: Data Management for the Internet of Things

Steffen Zeuch; Xenofon Chatziliadis; Ankit Chaudhary; Ariane Ziehn; Dimitrios Giouroukis; Philipp M. Grulich; Dwi Prasetyo Adi Nugroho; Volker Mark

In: Datenbank-Spektrum (Spektrum), Vol. 22 (2), Pages 131-141, Springer, 5/2022.

To the publication

Materialization and Reuse Optimizations for Production Data Science Pipelines

Behrouz Derakhshan; Alireza Rezaei Mahdiraji; Zoi Kaoudi; Tilmann Rabl; Volker Markl

In: SIGMOD '22: Proceedings of the 2022 International Conference on Management of Data. ACM SIGMOD International Conference on Management of Data (SIGMOD), June 12-17, Philadelphia, USA, The ACM Special Interest Group on Management of Data, 2022.

To the publication
All publications

Profile

Volker Markl is both Chief Scientist and Head of the Intelligent Analytics for Massive Data Research Department at the German Research Center for Artificial Intelligence (DFKI). In addition, Dr. Markl is the director of the Berlin Institute for the Foundations of Learning and Data (BIFOLD), which was founded through the merger of the Berlin Big Data Center (BBDC) and the Berlin Center for Machine Learning (BZML). At the Technische Universität Berlin (TU Berlin) he is Full Professor and Chair of the Database Systems and Information Management Group (DIMA).

His current research interests include 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, and scalable data science, including graph mining, text mining, and machine learning.

  • Since 2020 Director of the Berlin Institute for the Foundations of Learning and Data (BIFOLD)
  • 2018 – 2020  Co-Director of the Berlin Machine Learning Center (BZML)
  • Since 2018  Chief Scientist at the German Research Center for Artificial Intelligence (DFKI)
  • Since 2014  Head of the Intelligent Analytics for Massive Data Research Department at the German Research Center for Artificial Intelligence (DFKI)
  • 2014 – 2020  Director of the Berlin Big Data Center (BBDC)
  • Since 2008  Full Professor and Chair of the Database Systems and Information Management (DIMA) Group at the Technische Universität Berlin (TU Berlin)
  • 2001 – 2008  Project Leader at the IBM Almaden Research Center, San Jose, California, USA
  • 1997 – 2000  Research Group Leader at FORWISS, the Bavarian Research Center for Knowledge-based Systems, Munich, Germany

 

Entrepreneurial Activities (extract)

2014 – 2018 (exit)  Co-founder and Advisor, data Artisans, Berlin, Germany (Acquired by Alibaba)
2010 – 2016 (exit)  Advisor, Parstream, Cologne, Germany, 2010 – 2016 (Acquired by Cisco)

Professional Memberships (extract)

  • Elected President of the VLDB Endowment Inc. (VLDB / 2018 – 2021)
  • Co-lead, Technical Enablers and Data Science Working Group of the German Platform for Artificial Intelligence („Plattform Lernende Systeme“), 2018, acatech – DEUTSCHE AKADEMIE DER TECHNIKWISSENSCHAFTEN
  • Founding Member of the Big Data Value Association/Big Data Value PPP

Honors and Awards (extract)

  • ICDE 2021 Best Paper Award
  • BTW 2021 Best Paper Award
  • ACM SIGMOD 2020 Best Paper Award
  • EDBT Best Paper Award, 2019
  • 1st place in the BTW 2019 Data Science Challenge
  • EDBT Best Demonstration Award, 2019
  • ACM SIGMOD 2016 Research Highlight Award
  • Germany’s “Leading Digital Mind” (“Digitale Köpfe”) Award (2014)
  • VLDB Best Paper Award (2014)
  • Innovation Supporter Award, TU Berlin (2012)
  • Status-only Professorship Appointment, University of Toronto (2012)
  • Hewlett Packard Open Innovation Award (2009 + 2010)
  • Pat Goldberg Best Paper Award, IBM (2006)
  • Best Mentor Award, IBM (2005)
  • Outstanding Technological Achievement Award, IBM (2005)

Publications

207 publications (Citation h-index: 44) and 33 Keynote Lectures

  • BTW 2021 Best Paper Award for the Paper “Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing”
  • ICDE 2021 Best Paper Award for the Paper “Efficient Control Flow in Dataflow Systems: When Ease-of-Use Meets High Performance”
  • EDBT SIGMOD 2020 Best Paper Award for the Paper “Pump up the Volume: Processing Large Data on GPUs with Fast Interconnects”
  • EDBT 2020 Best Paper Award for the Paper “Pump up the Volume: Processing Large Data on GPUs with Fast Interconnects”
  • EDBT 2019 Best Paper Award for the Paper “Efficient Window Aggregation with General Stream Slicing”
  • 1st Place in the BTW 2019 Data Science Challenge
  • Co-lead, Technical Enablers and Data Science Working Group of the German Platform for Artificial Intelligence (“Plattform Lernende Systeme”), 2018.
  • ACM SIGMOD 2016 Research Highlight Award
  • EDBT 2017 Best Demonstration Award
  • Mitglied der Expertenkommission “Zentrum Digitalisierung Bayern“, 2015.
  • Germany’s Leading Digital Minds (“Digitale Köpfe”) Award, 2014.
  • VLDB Best Paper Award, 2014.
  • Innovation Supporter Award, TU Berlin, 2012.
  • Status-only Professorship Appointment, University of Toronto, 2012 - 2018.
  • IBM Faculty Award, 2012.
  • IBM Shared University Grant Award, 2012.
  • Trusted Cloud Award, German Federal Ministry of Economics and Technology, 2011.
  • IBM Center of Advanced Studies Award 2010, 2011, 2012.
  • Hewlett Packard Open Innovation Award, 2009, 2010.
  • IBM Shared University Grant Award, 2008.
  • Pat Goldberg Best Paper Award, IBM, 2006.
  • Outstanding Technological Achievement Award, IBM, 2005.
  • Best Mentor Award, IBM, 2005.
  • Seventeen Invention Achievement Awards, IBM, 2001 – 2006.
  • Four Invention-Plateau Awards, IBM, 2001 – 2006.
  • IST Prize for TransBase HyperCube, European Commission and EUROCASE, 2001.
  • Outstanding Computer Science Dissertation, German Computer Society (GI), 2000.
  • Siemens Nixdorf Förderkreis, Siemens AG, 1992-1995.
  • Elected Trustee of the VLDB Endowment
  • Elected Secretary of the VLDB Endowment
  • Elected President of the VLDB Endowment
  • Founding Member of the Big Data Value Association/Big Data Value PPP

  • ExDRa

    Exploratory Data Science over Raw Data

    The idea of the ExDRa project is to investigate suitable system

    support for the exploratory data science process on heterogeneous and distributed

    raw data sources and to provide it as part of a…

  • BBDCII

    Berliner Big Data Center

    Goals

    In order to optimally prepare industry, science and the society in Germany and Europe for the global Big Data trend, highly coordinated activities in research, teaching, and technology transfer…

    BBDCII

  • SePiA.Pro

    A Service Platform for the Intelligent Optimization of Production Chains

    The aim of the project SePiA.Pro is to develop an open and standardised service platform for optimization of production chains across machinery producers. The optimization parameters are based on…

    SePiA.Pro

  • STREAMLINE

    Streamlined Analysis of Data at Rest and Data in Motion

    Together with four leading European data economy enterprises as well as world-renown scientists and innovators DFKI will work in project STREAMLINE to meet modern day requirements of European online…

    STREAMLINE

  • PROTEUS

    Predictive Analytics and Real-Time Interactive Visualization for Industry

    PROTEUS mission is to investigate and develop ready-to-use scalable online machine learning algorithms and real-time interactive visual analytics to deal with extremely large data sets and data…

    PROTEUS
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