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Georgios Gousios
TU Delft EWI / ST
Building 28
Room W4.560
van Mourik Broekmanweg 6
2628 XE, Delft
the Netherlands

+31 (0) 15 278 5546
g.gousios@tudelft.nl

Welcome to my home page!

As of Nov 2020, I am on leave from TU Delft, working as a research engineer at Facebook.

I am associate professor of software engineering at the Software Engineering Research Group group, Delft University of Technology, leading the group’s Software Analytics lab and co-leading the group’s Machine Learning for Software Engineering lab. I do research in the broad area of software engineering. I am teaching Big Data Processing at the BSc level and Machine Learning for SE at the MSc level. I am also speaking, blogging and consulting.

Latest news

  • Nov 2021» ASE paper on how adding team features to task duration prediction models helps improve predictions by up to 30% (at ING).
  • Oct 2021» JSS paper on how dependency updates can be made safer by using static analysis.
  • Aug 2021» ESEC/FSE 2021 was succesfuly organized in Athens, Greece. Watch the introductory video and read the proceedings.
  • Jul 2021» TOSEM paper on pre-emptive conflict resolution (at Microsoft).
  • Jul 2021» TSE paper on what affects on-time deliveries in agile settings (at ING).
  • Jun 2021» Paper on ML-based off-by-one error detection.
  • Jan 2021» Technical report on fine-grained dependency management for Rust. An analysis of the whole Rust ecosystem at the function call level.

Old news

Current Projects

  • FASTEN: Making software ecosystems robust by making package management more intelligent.
  • AI4Fintech: Making large software-based organizations more efficient. Leader of the software analytics track.

Current Team

I have the pleasure of working with the following people (alumni):

PhDs

  • Joseph Hejderup (Feb 2017): Dependency management and static analysis
  • Elvan Kula (May 2019): Software process optimization, also at ING
  • Mehdi Keshani (May 2019): Dependency management and static analysis
  • Amir Mir (Oct 2019): Dependency management and machine learning