Hongwei Wang
Staff Research Scientist at Meta
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolHongwei Wang is a Staff Research Scientist at Meta Instagram with nine years of experience bridging cutting-edge research and production systems in LLMs and recommender systems. His work spans post-training and multimodal LLMs, retrieval-augmented generation and agents, as well as graph-based, generative and LLM-enhanced recommendation models—fields he advanced previously at Tencent and TikTok and during research fellowships at Stanford and UIUC. He brings deep hands-on expertise in graph neural networks and knowledge graphs, evidenced by his implementation of a TensorFlow Knowledge Graph Convolutional Network that underpins meaningful recommender-model architectures. Based in Sunnyvale, he combines rigorous academic training from Shanghai Jiao Tong University with practical leadership across industry research teams to deliver scalable models that connect multimodal understanding with user-facing recommendations. Notably, Hongwei often blends classic graph methods with generative LLM techniques to push recommendation personalization beyond traditional collaborative signals.
9 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy Computer Science, Doctor of Philosophy Computer Science at Shanghai Jiao Tong University
Github Skills (8)
machine-learning10
knowledge-graph10
tensorflow10
graph-convolutional-networks10
python10
recommender-system9
algorithm9
algorithms9
Programming languages (2)
Github contributions (5)
hwwang55/KGCN
Jul 2018 - Nov 2019
A tensorflow implementation of Knowledge Graph Convolutional Networks
Role in this project:
Back-end Developer
Back-end DeveloperContributions:55 commits, 47 pushes, 1 branch in 1 year 4 months
Contributions summary:Hongwei primarily focused on implementing the core components of a Knowledge Graph Convolutional Network (KGCN) using TensorFlow. Their contributions include the addition of `aggregators.py` and modifications to `model.py`, indicating the development of crucial model architecture and functionality. The user also made changes to `data_loader.py`, suggesting they also worked on data handling and preparation. This signifies a significant role in building the foundational elements of the knowledge graph convolutional network.
graph-convolutional-networksknowledge-graphrecommender-systems
hwwang55/JTS-MF
May 2017 - Nov 2019
Contributions:8 commits, 6 pushes, 1 branch in 2 years 6 months
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