時間：10月7日（星期五）下午13:00-15:00 (GMT+08:00)
地點：騰訊會議：717-103-095
報告人：悉尼科技大學 Dr Yi Zhang
主講人簡介：
張嶷博士現為悉尼科技大學澳大利亞人工智能研究院高級講師（終身教職），是2019年澳大利亞研究理事會DECRA（Discovery Early Career Researcher Award）基金獲得者。他擁有管理科學與工程（偉德國際1946bv官網）與軟件工程（悉尼科技大學）雙博士學位。他是美國佐治亞理工大學公共政策學院訪問學者（2011-2012）。
張嶷博士專注于文獻計量學與技術創新管理領域的研究，強調面向科技創新管理問題的智能文獻智能學理論架構與方法創新。共發表學術論文100余篇（其中，2017-2022年間高被引論文4篇）。其Google Scholar 論文被引2100余次，H Index為21。
張嶷博士現擔任雜志Technological Forecasting and Social Change與Scientometrics副主編，IEEE Transactions on Engineering Management雜志編委，以及Elsevier國際科學評價中心全球委員會顧問委員。
報告內容簡介：
Intelligent bibliometrics, highlighting the development and application of computational models incorporating AI and data science techniques with bibliographical information for broad studies in science, technology, and innovation scenarios. Its main tasks include topic extraction, relationship measurement and discovery, and prediction. Some representative works include embedding-based models for topic extraction and classification, heterogeneous network analytics for relationship discovery and prediction, etc. We have successfully applied intelligent bibliometrics to a wide range of ST&I scenarios, e.g., profiling large-scale coronavirus literature, discovering gene-disease associations, detecting emerging technologies, recommending knowledge trajectories of scientific researchers.
In this seminar, I will describe how my efforts take actions on recombining AI and data science with practical scenarios, problems, and issues, particularly in the case of bibliometrics and ST&I studies. I will showcase intelligent bibliometrics modelling through two cases: (1) Bi-layer bibliometric network analytics for characterising emerging general-purpose technologies; and (1) streaming data analytics-based analysis for monitoring topic disruption, evolution, and resilience in early COVID-19 crisis.
（承辦：知識管理與數據分析實驗室、科研與學術交流中心）
