应计算机科学与工程学院邀请，澳大利亚麦考瑞大学吴佳副教授将在线为我校师生作学术报告，具体事宜公告如下：

报告题目：Mining Complex Big Data: From Foundations to Real-World Artificial Intelligence

报告人：吴佳，澳大利亚麦考瑞大学副教授

报告地点：腾讯会议（会议ID：771-822-1642）

报告时间：2022年6月9日下午14：30

主持人：马慧芳，计算机科学与工程学院教授

届时欢迎广大师生在线参与交流！ 

    【报告摘要】

Big Data is an emerging paradigm, characterized by complex information that is beyond the processing capability of conventional tools. Traditional data analytics methods are commonly used in many applications, such as text classification and image recognition, and these data are often required to be represented as vectors for analysis purposes. While there are many real-world data objects that contain rich structure information, such as chemical compounds in bio-pharmacy, brain regions in brain networks and users in social networks. The simple feature-vector representation inherently loses the structure information of the objects. In reality, objects may have complicated characteristics, depending on how the objects are assessed and characterized. Data may also come from heterogeneous domains, such as traditional tabular-based data, sequential patterns, social networks, time series information, or semi-structured data. Processing, mining, and learning complex data refers to an advanced study area of data mining and knowledge discovery that concerns the development and analysis of approaches for discovering patterns and learning models for data with complex structures (e.g., time series, sequences, graphs, and bag constrained data). These kinds of data are commonly encountered in many artificial intelligence applications, such as brain science. Complex data poses new challenges for current research in data mining and knowledge discovery as new processing, mining, and learning methods are required. 

    【报告人简介】

吴佳，澳大利亚麦考瑞大学人工智能中心研究主管(Research Director) 、国际数据挖掘顶级期刊ACM Transactions on Knowledge Discovery Data（TKDD）副主编。2019 Heidelberg Laureate Forum Fellowship – 澳洲科学院 (Australian Academy of Science)。澳大利亚麦考瑞大学计算机学院副教授、副院长分管博士研究生。主要研究领域为数据挖掘、机器学习、人工智能，及其在商业、工业、生物信息学、医疗信息学等领域的应用。迄今，在国际学术期刊和会议上共发表论文100多篇, 包括IEEE Transactions on Pattern Analysis and Machine Intelligence、IEEE Transactions on Knowledge and Data Engineering、IEEE Transactions on Neural Networks and Learning Systems、IEEE Transactions on Cybernetics、ACM Transactions on Knowledge Discovery Data、NIPS、WWW、KDD、ICDM、IJCAI、AAAI、CIKM等。指导学生曾获得2021年顶级数据挖掘大会IEEE International Conference on Data Mining (ICDM) 最佳学生论文奖、2018顶级国际数据挖掘大会SIAM International Conference on Data Mining (SDM) 最佳论文奖-Applied Data Science Track、2017顶级国际神经网络大会International Joint Conference on Neural Networks (IJCNN) 最佳学生论文奖。