Matteo Paltenghi

[firstname].[lastname] at
Institut für Softwaretechnologie
Universitätsstr. 38
70569 Stuttgart

I am a researcher and PhD student at University of Stuttgart, advised by Prof. Dr. Michael Pradel. My driving interest consists of applications of Data Science and Software Engineering to solve challenging problems. My research focuses on Explainable AI techniques to increase programmer's usage of machine learning solutions.

Previously, I researched on anomaly detection methods at CERN Cloud Team, where I laid the foundation of their first anomaly detection system togheter with PhD. Domenico Giordano. I completed my Double M.Sc. in Computer Science Engineering (specialization in Data Science) at Politecnico di Milano and Technical University of Berlin as a part of EIT Digital Master School. I am naturally curious and I love to face challenging situations that make me grow.

My long-term objective is to convert innovative research results into products to assist software engineers in their work. In fact, in my spare time I love to reason on business plan ideas, stay informed about start-ups and participate in hackathons.

Education and Internships

PhD student at University of Stuttgart
Since December 2020
Advisor: Prof. Dr. Michael Pradel
Internship at CERN
Geneva, Switzerland
March 2020 – November 2020
Technical Student Programme and Master Thesis
Supervisors: PhD Domenico Giordano, Team: IT-CM-RPS
Master studies in Data Science and in Computer Science Engineering
Politecnico di Milano, Italy
September 2018 – October 2020
Bachelor studies in Computer Science Engineering
Politecnico di Milano, Italy
September 2015 – September 2018

Peer-Reviewed Publications

  • Bugs in Quantum Computing Platforms: An Empirical Study
    Matteo Paltenghi, Michael Pradel.
    In the OOPSLA issue of the Proceedings of the ACM on Programming Languages (PACMPL) (OOPSLA ’22).
    [paper] [dataset and code]
  • Thinking Like a Developer? Comparing the Attention of Humans with Neural Models of Code
    Matteo Paltenghi, Michael Pradel.
    In Research Papers of IEEE/ACM International Conference on Automated Software Engineering (ASE ’21).
    [paper] [dataset and code] [video] [slides]


  • Master Thesis (2020)
    Time Series Anomaly Detection for CERN Large-Scale Computing Infrastructure
    Matteo Paltenghi
    Work done during an internship at CERN, supervised by PhD Domenico Giordano (CERN), Prof. PhD. Giacomo Boracchi (POLIMI), Prof. Dr. Klaus-Robert Müller (TUB), M.Sc. Lukas Ruff (TUB).


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