时间：10月7日（星期五）下午13:00-15:00 (GMT+08:00)

地点：腾讯会议：717-103-095

报告人：悉尼科技大学 Dr Yi Zhang

主讲人简介：

张嶷博士现为悉尼科技大学澳大利亚人工智能研究院高级讲师（终身教职），是2019年澳大利亚研究理事会DECRA（Discovery Early Career Researcher Award）基金获得者。他拥有管理科学与工程（12BET）与软件工程（悉尼科技大学）双博士学位。他是美国佐治亚理工大学公共政策学院访问学者（2011-2012）。

张嶷博士专注于文献计量学与技术创新管理领域的研究，强调面向科技创新管理问题的智能文献智能学理论架构与方法创新。共发表学术论文100余篇（其中，2017-2022年间高被引论文4篇）。其Google Scholar 论文被引2100余次，H Index为21。

张嶷博士现担任杂志Technological Forecasting and Social Change与Scientometrics副主编，IEEE Transactions on Engineering Management杂志编委，以及Elsevier国际科学评价中心全球委员会顾问委员。

报告内容简介：

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.

（承办：知识管理与数据分析实验室、科研与学术交流中心）