Andrew-Le D. Dung
Research Scientist at VinUniversity
Vietnam, Singapore
Summary
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RockstarAndrew-Le D. Dung is a research scientist and assistant professor with eight years of experience at the intersection of machine learning and recommender systems, based between Vietnam and Singapore. He brings hands-on ML engineering depth, notably implementing the Indexable Bayesian Personalized Ranking (IBPR) model into the popular Cornac multimodal recommender framework. His work spans research and production-ready algorithm integration, translating academic ideas into usable open-source tools. Known for bridging classroom research and practical system development, he focuses on scalable personalization methods that are reproducible and extensible.
8 years of coding experience
Github Skills (10)
algorithm10
pytorch10
machine-learning10
recommendation-engine10
recommender10
recommendation-system10
python10
recommender-system9
collaborative-filtering9
matrix-factorization9
Programming languages (3)
Github contributions (5)
PreferredAI/cornac
Oct 2018 - Jan 2019
A Comparative Framework for Multimodal Recommender Systems
Role in this project:
ML Engineer
ML EngineerContributions:26 commits, 13 PRs, 3 pushes in 3 months
Contributions summary:Andrew-Le implemented the Indexable Bayesian Personalized Ranking (IBPR) model, a recommendation algorithm, within the cornac framework. The contributions involve defining the model's parameters, fitting the model to training data, and creating a prediction function. Key changes include adding and modifying the core IBPR files, indicating a focus on integrating a new recommendation algorithm into the existing system.
multimodal-learningrecommendation-algorithmspythonrecommendermultimodal-representation
Andrew-DungLe/andrew-dungle.github.io
Apr 2018 - Feb 2025
Contributions:99 pushes, 1 branch in 6 years 10 months
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