Azade Nova
I am a Research Scientist at Google Brain. Before joining Google, I was a postdoctoral researcher at Microsoft research in Data Management, Exploration and Mining (DMX) group. My research interests are in the broad areas of social network analysis, graph mining, machine learning, data mining, and database. I completed my PhD in Department of Computer Science and Engineering at the University of Texas, Arlington under the supervision of Dr. Gautam Das in Database Exploration Lab (DBXLAB). My PhD research focused on data exploration and analysis over online community networks such as GooglePlus, Twitter, and Amazon and I solved novel problems that have a practical impact and the solutions often involve the design of new techniques or adapting techniques from various fields such as graph theory, algorithms, statistics, etc. Google AI Residency has given me the opportunity to collaborate with brilliant researcher on challenging machine learning problems. Many important real-world datasets are in the form of graphs or networks: social networks, knowledge graphs, protein-interaction networks, the World Wide Web, etc. (just to name a few). Most of my current research devoted to the generalization of neural network models to such real-world datasets, where the goal is to exploit the graph structure of such datasets in the training process.
Authored Publications
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Google
UQE: A Query Engine for Unstructured Databases
Hanjun Dai
Bethany Wang
Sherry Yang
Phitchaya Mangpo Phothilimthana
Advances in Neural Information Processing Systems (NeurIPS) (2024)
Scalable Deep Generative Modeling for Sparse Graphs
Hanjun Dai
Yujia Li
International Conference on Machine Learning (2020)
