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Lianhua Chi is a postdoctoral research scientist in the Cognitive Analytics team at IBM Research Australia. Her research interests lie broadly in machine learning and data mining. Areas of focus include cognitive data analytics (in particular on text analysis in social media and correlation analysis between events and time series), hashing algorithm innovations on big data classification (especially on large-scale graph stream classification), hospital resource optimization and text annotation.
She is currenly working on a Watson Health project to annotate documents with Machine Learning and Natural Language Processing.
She received her dual B.S. degree in Computer Science and English from Wuhan University of Science and Technology (WUST), China in 2008. In 2015, she earned her dual Ph.D. degree in Machine Learning and Data Mining at University of Technology Sydney (UTS), Australia, and Huazhong University of Science and Technology (HUST), China.
Dr. Chi received a Best Paper Award in the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining for her work "Fast Graph Stream Classification Using Discriminative Clique Hashing”. In 2016, she was named among the top 200 of the most qualified young researchers globally to attend the Heidelberg Laureate Forum, and received the Romberg Grant Award from the University of Heidelberg. In 2017, she was selected as one of 100 outstanding Young Global Changers to attend the Think 20 Summit – GLOBAL SOLUTIONS (T20), mandated by the 2017 German presidency of the Group of Twenty (G20).