Daokun Zhang
Research Fellow at Monash University
Melbourne, Victoria, Australia
Summary
🤩
Rockstar🎓
Top SchoolDaokun Zhang is a research fellow and graph machine learning specialist with nine years of experience applying representation and structure learning to real-world problems from drug discovery to geographic forecasting. Based at Monash University and collaborating with leading researchers like Prof Geoff Webb, he blends deep academic training (PhD in Data Mining) with hands-on engineering—contributing key implementations to the popular StellarGraph library. His work spans node classification, link prediction, knowledge graph alignment, and combinatorial optimization, and he’s supervised multiple graduate projects while teaching graduate courses in NLP and optimization. Notably, his open-source contributions include implementing Attri2Vec components and demos for StellarGraph, helping a library with thousands of users bridge research and applied ML.
8 years of coding experience
2 years of employment as a software developer
Master of Engineering - MEng, Data Mining, Master of Engineering - MEng, Data Mining at Northwest A&F UniversityDoctor of Philosophy (Ph.D.), Data Mining, Doctor of Philosophy (Ph.D.), Data Mining at University of Technology Sydney
Github Skills (9)
algorithm10
graphdb10
machine-learning10
machine-learning-algorithms10
graphml10
python10
data-science9
graph-neural-network9
deep-learning9
Programming languages (1)
Github contributions (5)
stellargraph/stellargraph
Aug 2019 - Jun 2020
StellarGraph - Machine Learning on Graphs
Role in this project:
ML Engineer & Data Scientist
ML Engineer & Data ScientistContributions:204 commits, 13 PRs, 106 pushes in 10 months
Contributions summary:Daokun's commits indicate contributions focused on implementing and refining machine learning models, specifically within the context of a graph machine learning library. They added the definition and implementation of the `attri2vecLinkGenerator` and the `attri2vecLinkGenerator` class, demonstrating an understanding of the underlying algorithms and the library's architecture. The user then rewrote and updated the attri2vec demo, incorporating the new Attri2Vec model, Attri2VecNodeGenerator, and Attri2VecLinkGenerator. Finally, the user added additional demos for different use cases with attri2vec.
pythonheterogeneous-networkssaliency-mapfraud-preventiongraph-machine-learning
HaoweiGis/stellargraph
Nov 2019 - Jan 2020
StellarGraph - Machine Learning on Graphs
Contributions:77 commits in 1 month
dataminingdata-sciencemachine-learninggraphsgraphneuralnetwork
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