Phuong T. Nguyen

Registered user since Thu 13 Dec 2018

Name:Phuong T. Nguyen
Bio:

I am an assistant professor (tenure track) 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 Computer Networks, Semantic Web, Recommender Systems, and Machine Learning. Recently, I have been working to develop recommender systems in Software Engineering for mining open source code repositories.

Country:Italy
Affiliation:University of L’Aquila
Research interests:Computer Networks, Recommender Systems, Machine Learning

Contributions

ICSE 2024 Committee Member in Artifact Evaluation within the Artifact Evaluation-track
MSR 2023 Committee Member in Program Committee within the Technical Papers-track
Author of Dealing with Popularity Bias in Recommender Systems for Third-party Libraries: How far Are We? within the Technical Papers-track
ESEC/FSE 2023 Committee Member in Program Committee within the Research Papers-track
ESEIW 2023 Committee Member in Program Committee within the ESEM Technical Papers-track
ICSME 2023 Committee Member in Program Committee within the Research Track-track
EASE 2023 Author of Fusion of deep convolutional and LSTM recurrent neural networks for automated detection of code smells within the Short Papers and Posters-track
Author of Too long; didn't read: Automatic summarization of GitHub README.MD with Transformers within the Vision and Emerging Results-track
ICSE 2023 Author of A GNN-based Recommender System to Assist the Specification of Metamodels and Models within the Showcase-track
Committee Member in Artifact Evaluation within the Artifact Evaluation-track
Committee Member in Posters within the Posters-track
CAIN 2023 PC Member in Program Committee
TechDebt 2023 PC Member in Technical Papers within the Technical Papers-track
MODELS 2022 Author of Finding with NEMO: A Recommender System to Forecast the Next Modeling Operations within the Technical Track-track
Author of MemoRec: a recommender system for assisting modelers in specifying metamodels within the Journal-first-track
ASE 2022 Committee Member in Program Committee within the Artifact Evaluation-track
ISSTA 2022 Committee Member in Artifact Evaluation Committee within the Artifact Evaluation-track
EASE 2022 Committee Member in Program Committee within the Vision and Emerging Results Track-track
MSR 2022 Committee Member in Program Committee within the Technical Papers-track
Session Chair of Session 11: Machine Learning & Information Retrieval (part of Technical Papers)
TechDebt 2022 Author of PILOT: Synergy between Text Processing and Neural Networks to Detect Self-Admitted Technical Debt within the Technical Papers-track
ASE 2021 Author of Adversarial Attacks to API Recommender Systems: Time to Wake Up and Smell the Coffee? within the Research Papers-track
Author of A Replication of Adversarial Attacks to API Recommender Systems: Time to Wake Up and Smell the Coffee? within the Artifact Evaluation-track
MODELS 2021 Author of A GNN-based Recommender System to Assist the Specification of Metamodels and Models within the Technical Papers-track
ESEC/FSE 2021 Session Chair of Analytics & Software Evolution—Libraries and APIs 2 (part of Research Papers)
Session Chair of Analytics & Software Evolution—Recommender Systems (part of Research Papers)
Session Chair of Analytics & Software Evolution—Mining Software Repositories (part of Research Papers)
Session Chair of SE & AI—Machine Learning for Software Engineering 2 (part of Research Papers)
Session Chair of SE & AI—Machine Learning for Software Engineering 1 (part of Research Papers)
Session Chair of SE & AI—Search Based Software Engineering (part of Research Papers)
EASE 2021 Author of A Multinomial Naive Bayesian (MNB) network to automatically recommend topics for GitHub repositories within the EASE 2020-track
Author of Adversarial Machine Learning: On the Resilience of Third-party Library Recommender Systems within the Vision and Emerging Results Track-track
MODELS 2020 Author of Using the Low-code Paradigm to Support the Development of Recommender Systems within the Posters-track
ICSE 2019 Author of FOCUS: A Recommender System for Mining API Function Calls and Usage Patterns within the Technical Track-track