Prof. Dr. Tilmann Rabl

Dr. Pedro Silva

Former PostDoc at HPI


I’m  a post-doc researcher working at the Data Engineering Systems team
at the HPI.

Currently I'm working with graph stream processing systems and benchmarking,
but I'm also interested in data stream processing on complex virtualized
infrastructures such as Edge, Fog and Cloud computing.

Between 2018 and 2019 I worked as a post-researcher at the Inria
team Kerdata in Rennes, France. I received my PhD from the Université de Lyon, France, in 2017, and my
Master’s and Bachelor degrees from the University of São Paulo, Brazil in 2013 and 2011, respectively.


Research Interests

  • Data stream processing
  • Stream graph processing and graph databases
  • Benchmarking
  • Cloud and Edge computing
  • Resource management in distributed systems

Recent Publications

Daniel Rosendo, Pedro Silva, Matthieu Simonin, Alexandru Costan, Gabriel Antoniu. E2Clab: Ex-ploring the Computing Continuum through Repeatable, Replicable and Reproducible Edge-to-CloudExperiments. Cluster 2020. (PDF File)


Silva, P., Yue, W., Rabl, T. . Grand Challenge: Incremental Stream Query Analytics.Proceedings of the 14th ACM International Conference on Distributed and Event-based Systems (DEBS ’20). bl. 6 (2020). *Winners of the Grand Challenge Performance and Audience Awards. (PDF File)


Kévin Fauvel, Daniel Balouek-Thomert, Diego Melgar, Pedro Silva, Anthony Simonet, et al.. A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning. AAAI 2020 - 34th AAAI Conference on Artificial Intelligence, Feb 2020, New York, United States. *Outstanding Paper Award: Special Track on AI for Social Impact* (PDF File)


Pedro Silva, Alexandru Costan, Gabriel Antoniu: Investigating Edge vs. Cloud Computing Trade-offs for Stream Processing. IEEE BigData 2019. (PDF File)


Pedro Silva, Alexandru Costan, Gabriel Antoniu: Towards a Methodology for Benchmarking Edge Processing Frameworks. IPDPS Workshops 2019. (PDF File)


Prosperi L., Silva, P. , Costan A., and Antoniu, G., Planner: Cost-efficient Execution Plans Placement for Uniform Stream Analytics on Edge and Cloud. 13th WORKS 2018 Workshop (2018) — co-located at Supercomputing 2018. (PDF File)


P. Silva and C. Perez, An Efficient Communication Aware Heuristic for Multiple Cloud Application Placement. 23rd International European Conference on Parallel and Distributed Computing (Euro-par 2017) (PDF File)

 P. Silva, C. Perez, and F. Desprez, Efficient Heuristics for Placing Large-Scale Distributed Applications on Multiple Clouds.  CCGrid 2016 (PDF File)


Recent Teaching

  • Master Project: Compilation Techniques for  Dynamic Stream Processing - Winter Semester 2021
  • Bachelor Project: End-to-end ML System Benchmarking - 2020/2021.
  • Big Data Systems (Graph processing lectures, RDMA lectures, Exercise sessions) - Winter Semester 2021 (Master level, HPI)
  • Data Processing on Modern Hardware - Summer Semester 2020 (Master level, HPI)
  • Big Data Systems (Graph processing lectures) - Winter Semester 2020 (Master level, HPI)
  • Big data systems (Stream processing lectures) - Summer Semester 2020 (Master level, INSA de Rennes)
  • Big data systems (Stream processing lectures) - Summer Semester 2019 (Master level, INSA de Rennes)
  • Cloud and big data systems (Stream processing lectures) - Summer Semester 2019 (Master level, Université de Rennes 1)

Recent Event Organization

6th BOSS Workshop (colocated at VLDB 2020): Chair

SIGMOD 2020: Demo session chair