Ricercatore TD/b

Phuong Thanh Nguyen


Software Engineering; Recommender Systems; Machine Learning
06 Ingegneria del Software
INF/01 - Informatica
Computer Science and Operations Research

Curriculum   Scholar DBLP Scopus Research Gate


I am a tenure track assistant professor (RTD/b) at the University of L’Aquila, Italy. I obtained a Ph.D. in Computer Science from the University of Jena, Germany. I was a postdoctoral researcher at Polytechnic University of Bari and the University of L’Aquila. My research interests include Recommender Systems, Mining Software Repositories, and Machine Learning. Recently, I have been working to develop recommender systems for Software Engineering, mining open source code repositories to support software programmers.

Research interests:

  • Mining Software Repositories. Open-source software (OSS) forges, such as GitHub or Maven, offer many software projects that deliver stable and well-documented products. Most OSS forges typically sustain vibrant user and expert communities which in turn provide decent support, both for answering user questions and repairing reported software bugs. Moreover, OSS platforms are also an essential source of consultation for developers in their daily development tasks. We have conceptualized techniques and tools to assist developers in their programming tasks.
  • Recommender Systems. Recommender systems for software engineering (RSSEs) have been conceptualized on a comparable basis, i.e., they assist developers in navigating large information spaces and getting instant recommendations that are helpful to solve a particular development task. In this sense, RSSEs provide developers with useful recommendations, which may consist of different items, such as code examples, topics, third-party components, to name a few.
  • Machine Learning and Deep Learning. The proliferation of disruptive Machine Learning (ML) and especially Deep Learning (DL) algorithms has enabled a plethora of applications across several domains. Such techniques work on the basis of complex artificial neural networks, which are capable of effectively learning from data by means of a large number of parameters distributed in different network layers. We have successfully studied and deployed various Machine Learning techniques in Software Engineering and other domains.


I got the Italian habilitation (Abilitazione Scientifica Nazionale) as Associate Professor for the following two independent sectors:

Academic service:


I have been teaching the following courses:

AY 2023 -- 2024:

AY 2022 -- 2023:

Office hours (for receiving students):

  • Monday:  14h15 -- 16h15
  • Tuesday: 09h15 -- 11h15

Edificio Alan Turing, Room 211, Via Vetoio snc., 67100 L'Aquila, Italy


I have been a reviewer for the following conferences:




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