I am an assistant professor at McMaster University. I have a broad research interest in the areas of data mining, applied machine learning and big data analytics with a special focus on the trustworthiness of artificial intelligence.(Please refer to my “Personal website” on the right side for more up-to-date information.)
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Dr. Lingyang Chu received the doctoral degree from the University of Chinese Academy of Sciences, Beijing, China, in 2015. He joined the Department of Computing and Software on January 1st, 2021. His research works in large scale graph mining and interpretable AI have been published in top-tier venues. One of his works on interpretable AI was reported by a mainstream web portal of AI research in China in 2018.
Related Courses
Complex data in the real-world can often be represented as a graph of relationships between objects or entities. This course focuses on the computational, algorithmic and modeling challenges related to the analysis of large scale graphs and networks. Students will be introduced to machine learning techniques and data mining tools that reveal insights on a variety of graphs and networks. Topics include: graph representation learning, graph neural networks, algorithms for complex networks, reasoning over Knowledge Graphs, influence maximization, and social network analysis.
