Khanh Nguyen-Phuoc worked on the pytorch/torchrec repository, focusing on improving the accuracy of offline evaluation for multitask recommender systems. He addressed a bug in the NDCG metric implementation for multitask scenarios, reducing the risk of misranking in complex pipelines. His approach involved updating the Python-based evaluation logic and developing comprehensive unit tests using pytest to validate correctness across multiple tasks. By integrating these tests with the continuous integration workflow, Khanh enhanced the reliability of TorchRec’s evaluation tools. His work demonstrated depth in data science and machine learning, contributing to more robust and trustworthy model assessment for TorchRec users.