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

Personal website:https://www.disim.univaq.it/ThanhPhuong

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