I completed the Ph.D in Computer Science (June-2020) at School of Computing & Information Systems (SCIS), Singapore Management University (SMU) (Rank 84 Overrall, Rank 21 in Software Engineering Research on CSRanking) and a Bachelor in Computer Science at Ho Chi Minh University of Science (2013).
During my Ph.D, I was fortunate to be advised by Prof. Lingxiao Jiang. I also received tremendous guidance from Prof.Yijun Yu from The Open University, UK. I was grateful to receive the Presidential Doctoral Fellowship in Computing and the SMU Dean’s List for outstanding research achievement. I am the first author of a few publications in top-tier academic conferences across different domains in Computer Science, such as software engineering (ICSE , ESEC/FSE, ASE), artificial intelligence (AAAI) and information retrieval (SIGIR).
- Research Scientist - Software Engineering Research Group, SMU.
- AI Residency Supervisor - FSoft AI Lab.
- Lead Research Scientist - Trustworthy Open-Source Software Engineering Lab, Huawei Ireland Research Center.
My interests lie at the intersection of Software Engineering, Machine Learning, Programming Languages and Natural Language Processing. Specifically, I am interested in the application of Artificial Intelligence (AI) to solve challenging problems for software systems (aka Machine Learning for Code), such as large-scale code search, code summarization, program synthesis, bug detection, program repair, etc. Towards the goal of automated programming, my primary focus of research is to study large scale, free source code data (Big Code) that is freely accessible on Github, Bitbucket, etc., to better understand the behaviors of software systems, and to introduce Machine Learning model to mine knowledge from these systems. This is a step forward in reducing software maintenance costs, and help software developers to understand the source code better.
More details of my research can be found in my Github.
TreeCaps:Tree-based Capsule Networks for Source Code Processing, AAAI 2021.
InferCode: Self-Supervised Learning of Code Representations by Predicting Subtrees, ICSE 2021.
Self-Supervised Learning for Code Retrieval and Summarization through Semantic-Preserving Program Transformations, SIGIR 2021.
- Apr-2020: Our paper “Corder: Self-Supervised Learning for Code Retrieval and Summarization through Semantic-Preserving Program Transformations” has been accepted as a full paper at SIGIR 2021!
- Dec-2020: Our paper “InferCode: Self-Supervised Learning of Code Representations by Predicting Subtrees” has been accepted as a full paper, Technical Track at ICSE 2021, Madrid, Spain!
- Dec-2020: Our paper “TreeCaps:Tree-based Capsule Networks for Source Code Processing” has been accepted as a full paper, Main Track at AAAI 2021, Vancouver, Canada!
- Oct-2020: I’ll serve as a Program Commitee member of the Mining Challenge Track, Mining Sotware Repositories (MSR 2021), Madrid, Spain.
- Dec-2019: I am invited to give a talk about “Machine Learning for Software” at School of Computing & Communications, the Open University, UK.
- Oct-2019: Paper “TreeCaps:Tree-Structured Capsule Networks for Program Source Code Processing” has been accepted at NeurIPS Workshop on ML for Systems, 2019, Vancouver, Canada !.
- Aug-2019: Get into Dean’s List of SMU Postgraduate Program for the outstanding research output in the Academic year of 2018 and 2019
- Aug-2019: Paper “AutoFocus: Interpreting Attention-based Neural Networks by Code Perturbation” has been accepted at Research Track, New Ideas Papers at ASE 2019, San Diego, California, United States.
- July-2019: Got the prestigious Presidential Doctoral Fellowship award from SMU!
- May-2019: Got a Bronze Medal in the ACM Student Research Competition, ICSE 2019.
- May-2019: Paper “SAR: Learning Cross-Language API Mappings with Little Knowledge” has been accepted at the 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), Research Track, Tallinn, Estonia, 2019 !!!.
- Nov-2018: Our work “Hierarchical Learning of Cross-Language Mappings through Distributed Vector Representations” got the Best Paper Awards at ICSE’2018, NIER Track.
- Nov-2018: Paper “Hierarchical Learning of Cross-Language Mappings through Distributed Vector Representations for Code” has been accepted at the 40th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (NIER), Gothenburg, Sweden, 2018 !!!.
- Get into Dean’s List for Outstanding Research Achievement at SMU Postgraduate Program, 2019
- SMU Presidential Doctoral Fellowship, 2019
- SIGSOFT CAPS Travel Grant Award - ESEC/FSE 2019
- Bronze Medal in the ACM Student Research Competition, ICSE 2019
- SIGSOFT CAPS Travel Grant Award - ICSE 2019
- ACM SIGSOFT Distinguished Paper Award - ICSE 2018