CV

This page contains the key milestones in my career. You can export a short version of my CV using the button on the right.

Table of contents

General

Full Name Emanuele Iannone
Nationality Italian
Date of Birth September 1, 1996
Languages Italian, English

Work Experience

  • 2023.11 - curr.
    Postdoctoral Researcher
    Institute of Software Security, Hamburg University of Technology, Hamburg
    • Research on code-level security vulnerability testing.
    • Working on designing novel automated vulnerability repair solutions in the context of Horizon Europe project (Sec4AI4Sec, grant ID: 101120393).

Education

  • 2020.11 - 2024.02
    Doctor of Philosophy (Ph.D.) in Computer Science
    University of Salerno, Fisciano, Italy
    • Supervisor: Prof. Fabio Palomba
    • Thesis title: There's Something About Vulnerabilities: Empirical Comprehension and Novel Automated Approaches
      • Empirical Studies on Software Vulnerabilities
      • Mining Vulnerability Contributing Commits
      • Just-in-time Vulnerability Prediction
      • Exploitability Prediction
      • Third-party Vulnerability Testing
  • 2018.09 - 2020.09
    M.Sc. Degree in Computer Science
    University of Salerno, Fisciano, Italy
    • Supervisors: Prof. Fabio Palomba, Prof. Andrea De Lucia
    • Thesis title: Toward Automatic Exploit Generation of Known API Vulnerabilities
  • 2015.09 - 2018.07
    B.Sc. Degree in Computer Science
    University of Salerno, Fisciano, Italy
    • Supervisor: Prof. Andrea De Lucia
    • Thesis title: Automated Refactoring of Energy-Related Code Smells of Android Applications

Research Projects

  • 2023.11 - curr.
    Sec4AI4Sec (grant ID: 101120393)
    Institute of Software Security, Hamburg University of Technology, Hamburg, Germany
    • Work Package on 'Automatic Vulnerability Repair'

Research Internships

  • 2022.10 - 2022.12
    Visiting Ph.D. Student
    University of Luxembourg, SnT, Luxembourg, Luxembourg
  • 2022.05 - 2022.06
    Visiting Ph.D. Student
    Tampere University, Tampere, Finland
    • Detecting vulnerability in open-source software using crowd-sourced information.

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