Jonas Traub

Researcher at Technische Universität Berlin and the German Research Center for Artificial Intelligence (DFKI). Working with Volker Markl at DIMA and IAM.

I am a Research Associate at TU Berlin and a PhD candidate supervised by Volker Markl. I wrote my master thesis during a year abroad at the Royal Institute of Technology (KTH) and the Swedish Institute of Computer Science (SICS) / RISE in Stockholm under Supervision of Seif Haridi and Volker Markl and advised by Paris Carbone and Asterios Katsifodimos. I graduated with a M.Sc. in computer science in April 2015 at TU-Berlin.

Prior to that, I received my B.Sc degree at Baden-Württemberg Cooperative State University (DHBW Stuttgart) and worked several years at IBM in Germany and the USA.

I am alumnus of Software Campus, Studienstiftung des deutschen Volkes, and Deutschlandstipendium.

My research interests include data stream processing, sensor data analysis, and data acquisition.



Jonas Traub

Address

Technische Universität Berlin
- Room EN 709 -
Fak. IV, FG DIMA, Sekr. EN7
Einsteinufer 17, 10587 Berlin, Germany

e-mail/phone

firstname.lastname@tu-berlin.de
+49 30 314-23515

Publications

DEBS 2019
 Git  PDF  Poster
Generating Reproducible Out-of-Order Data Streams
Philipp M. Grulich, Jonas Traub, Asterios Katsifodimos, Sebastian Breß, Tilmann Rabl, Volker Markl. ACM International Conference on Distributed and Event-based Systems (DEBS), 2019. [BibTeX]
EDBT 2019
 Best Paper  Git
 PDF  Poster  Slides
Efficient Window Aggregation with General Stream Slicing
Jonas Traub, Philipp Grulich, Alejandro Rodríguez Cuéllar, Sebastian Breß, Asterios Katsifodimos, Tilmann Rabl, Volker Markl. In International Conference on Extending Database Technology (EDBT), 2019. [BibTeX]
VLDB 2019
 PDF
Analyzing Efficient Stream Processing on Modern Hardware
Steffen Zeuch, Bonaventura Del Monte, Jeyhun Karimov, Clemens Lutz, Manuel Renz, Jonas Traub, Sebastian Breß, Tilmann Rabl, Volker Markl. Proceedings of the VLDB Endowment (PVLDB), 2019. [BibTeX]
EDBT 2019
 Best Demo  Git
 PDF  Poster
Resense: Transparent Record and Replay of Sensor Data in the Internet of Things
Dimitrios Giouroukis, Julius Hülsmann, Janis von Bleichert, Morgan Geldenhuys, Tim Stullich, Felipe Gutierrez, Jonas Traub, Kaustubh Beedkar, Volker Markl. In International Conference on Extending Database Technology (EDBT), 2019. [BibTeX]
EDBT 2019
 Git  PDF  Poster
Adaptive Watermarks: A Concept Drift-based Approach for Predicting Event-Time Progress in Data Streams
Ahmed Awad, Jonas Traub, Sherif Sakr. In International Conference on Extending Database Technology (EDBT), 2019. [BibTeX]
ICDE 2018
 Git  PDF  Poster
 Slides
Scotty: Efficient Window Aggregation for out-of-order Stream Processing
Jonas Traub, Philipp M. Grulich, Alejandro Rodríguez Cuellar, Sebastian Breß, Asterios Katsifodimos, Tilmann Rabl, Volker Markl. IEEE International Conference on Data Engineering (ICDE), 2018. [BibTeX]
EDBT 2018
 Git  PDF  Poster
Scalable Detection of Concept Drifts on Data Streams with Parallel Adaptive Windowing
Philipp Marian Grulich, René Saitenmacher, Jonas Traub, Sebastian Breß, Tilmann Rabl, Volker Markl. In International Conference on Extending Database Technology (EDBT), 2018. [BibTeX]
EDBT 2018
 Git  PDF  Poster
Efficient SIMD Vectorization for Hashing in OpenCL
Tobias Behrens, Viktor Rosenfeld, Jonas Traub, Sebastian Breß, Volker Markl. In International Conference on Extending Database Technology (EDBT), 2018. [BibTeX]
SoCC 2017
 PDF  Poster  Slides
Optimized On-Demand Data Streaming from Sensor Nodes
Jonas Traub, Sebastian Breß, Tilmann Rabl, Asterios Katsifodimos, and Volker Markl. In ACM Symposium on Cloud Computing 2017 (SoCC '17), Sep 25 - 27, 2017, Santa Clara, CA, USA. [BibTeX]
EDBT 2017
 Best Demo  Git  Rec
 PDF  Poster  Slides
I²: Interactive Real-Time Visualization for Streaming Data
Jonas Traub, Nikolaas Steenbergen, Philipp M Grulich, Tilmann Rabl, and Volker Markl. Proceedings of the 20th International Conference on Extending Database Technology (EDBT'17), March 21-24, 2017, Venice, Italy. [BibTeX]
CIKM 2016
 PDF  Slides
Cutty: Aggregate Sharing for User-Defined Windows
Paris Carbone, Jonas Traub, Asterios Katsifodimos, Seif Haridi, and Volker Markl. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (CIKM'16), October 24 - 28, 2016, Indianapolis, Indiana, USA. [BibTeX]
it-Inf.T. 2016
 PDF
Apache Flink in current research
Tilmann Rabl, Jonas Traub, Asterios Katsifodimos, and Volker Markl. it-Information Technology, 58(4), 157-165, De Gruyter Oldenbourg, 2016. [BibTeX]
LWA 2015
 PDF  Poster  Slides
Die Apache Flink Plattform zur parallelen Analyse von Datenströmen und Stapeldaten
Jonas Traub, Tilmann Rabl, Fabian Hueske, Till Rohrmann, Volker Markl. Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB. October 7 - 9, 2015, Trier, Germany. [BibTeX]
US Patent
 PDF
Adaptive Fragment Assignment for Processing File Data in a Database
Andrey Balmin, Romulo Antonio Pereira Goncalves, Fatma Ozcan, and Jonas Traub. US Patent 9,576,000 Β2, 2014. [BibTeX]

Talks / Miscellaneous

USA Excursion 2019
 Web  PDF
 Slides  Video
Series of Talks: Database Research at TU-Berlin and DFKI IAM
Jonas Traub, Sebastian Breß, Andreas Kunft, Martin Kiefer, Juan Soto, Volker Markl. Hosts include: New York University (Center for Data Science), Harvard University (Data Systems Lab), Johns Hopkins University (Institute for Data Intensive Engineering and Science), Northeastern University (Data Lab), MIT (Database Group), University of Washington (Database Group), UC Berkeley (Database Group), Stanford University (Infolab), Confluent, IBM Almaden Research Center, Intel, Microsoft, Oracle, Snowflake, Workday.
FlinkForward 2018
 Git  PDF
 Poster  Slides
Talk - Efficient Window Aggregation with Stream Slicing
Jonas Traub, Philipp Marian Grulich.
FlinkForward, Berlin, 2018. [BibTeX]
BIRTE@VLDB 2018
 Slides
Panel - Are we making any attempts towards solving the hardest problems in stream processing today?
Panelists: Manpreet Singh (Google), Karthik Ramasamy (Stremlio), C. Mohan (IBM), Badrish Chandramouli (Microsoft), Neng Lu (Twitter), Alok Pareek (Striim), Jonas Traub (TU-Berlin). BIRTE Workshop at the 44th International Conference on Very Large Data Bases (VLDB), Brasil, Rio de Janeiro, September 2018.
Stream Reasoning 2018
 PDF  Poster  Slides
Talk - Optimized On-Demand Data Streaming from Sensor Nodes
Jonas Traub. Stream Reasoning Workshop 2018 at University of Zurich (UZH), Switzerland, January 2018. [BibTeX]
BDAHM/SDIC 2017
 Slides
Talk - Efficiently Handling Streams from Millions of Sesors
Jonas Traub. 2nd BMBF Big Data All Hands Meeting (BDAHM) and 2nd Smart Data Innovation Conference (SDIC), 11-12 October 2017, Karlsruher Institut of Technologie (KIT).
BDAHM/SDIC 2017
 Slides
Talk - Research and Innovation in the Berlin Big Data Center
Jonas Traub and Chen Xu with materials from Tilmann Rabl and Volker Markl. 2nd BMBF Big Data All Hands Meeting (BDAHM) and 2nd Smart Data Innovation Conference (SDIC), 11-12 October 2017, Karlsruher Institut of Technologie (KIT).
FlinkForward 2017
 Git  PDF
 Slides  Video
Talk - I²: Interactive Real-Time Visualization for Streaming Data with Apache Flink and Apache Zeppelin
Jonas Traub, Philipp Marian Grulich. FlinkForward, Berlin, 2017. [BibTeX]
BOSS@VLDB 2016
 Slides
Tutorial - Apache Flink Tutorial at the Big Data Open Source Systems Workshow
Konstantinos Kloudas (dataArtisans), Vasia Kalavri (KTH Stockholm), Jonas Traub(TU Berlin). Big Data Open Source Systems Workshow (BOSS) at VLDB, New Delhi, India, 2016.
WBDB 2015
 PDF
Programm Commitee / Reviewer - Big Data Benchmarking
T. Rabl, R. Nambiar, C. Baru, M. Bhandarkar, M. Poess, S. Pyne (Eds.). 6th International Workshop, WBDB 2015, Toronto, ON, Canada, June 16-17, 2015 and 7th International Workshop, WBDB 2015, New Delhi, India, December 14-15, 2015, Revised Selected Papers. [BibTeX]
DB2 User Grp. 2015
Talk - Apache Flink - Stream and Batch Data Processing at Scale
Jonas Traub. DB2 User Group Meeting 2015, IBM Böblingen Research Lab.

Theses & Teaching

Thesis Supervision

  • Alexander Dadiani: A Catalogue of Sampling Algorithms for Sensor Data
  • Chiao-Yun Li: Automatic Tuning of Read-Time Tolerances for on-demand Data Streaming
  • Vianney de Cibeins: A Benchmark for Adaptive Data Collection in the Internet of Things
  • Yusuf Güven Toprakkiran: Machine learning from streaming data in heterogeneous computing environments
  • Alejandro Rodriguez Cuellar: Window aggregate sharing for out-of-order stream processing
  • Jerred Blankenburg: Performance Analysis of a Complex Event Processing Engine on classical data-stream-processing workloads
  • Robin Rabe: Scalable Data Stream Processing Using Cloud-Based Database Management Systems

Teaching

Winter Term 2018/2019

Summer Term 2018

Winter Term 2017/2018

Summer Term 2017

Winter Term 2016/2017

Summer Term 2016

Winter Term 2015/2016

Summer Term 2015


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