报告题目：DATA - LEARNING - DECISION: methodologies and Innovation  

报告人：路节

报告时间：2020年8月27日（周四）下午3：00
报告地点：悉尼智能科技学院国际会议室（科技楼6031室） 
                 ZOOM：https://zoom.us/j/9852111987

摘要：
The talk will present how machine learning can innovatively and effectively learn from data to support data-driven decision-making in uncertain and dynamic situations. A set of new fuzzy transfer learning theories, methodologies and algorithms are proposed that transfer knowledge learnt in one or more source domains to target domains by building latent space and mapping functions to overcome tremendous uncertainties in data, learning processes and decision outputs (classification and regression). Another set of concept drift theories, methodologies and algorithms are developed to handle ever-changing dynamic data stream environments with unpredictable stream pattern drifts by effectively and accurately detecting concept drift in an explanatory way, indicating when, where and how concept drift occurs and reacting accordingly. These new developments enable smart learning and therefore enhance data-driven prediction, recommendation and decision support systems in uncertain and dynamic environments.

报告人简介：
Distinguished Professor Jie Lu is an internationally renowned scientist in the areas of decision support systems, fuzzy transfer learning, concept drift, and recommender systems. She is an IEEE fellow, IFSA fellow and Australian Laureate fellow; the Director of the Australian Artificial Intelligence Institute (AAII) which has over 200 staff and students working on 50 research projects and the Associate Dean (Research Excellence) in the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). She has published six research books and over 400 papers in Artificial Intelligence, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Neural Networks and Learning Systems, Decision Support Systems and other leading journals and conference proceedings e.g. IJCAI, AAAI, ICDM; has won 20 ARC Laureate, Discovery Projects and industry projects; supervised 43 PhD students to completion. She serves as Editor-In-Chief for Knowledge-Based Systems (Elsevier) and Editor-In-Chief for International journal of computational intelligence systems. She has delivered over 25 keynote speeches at international conferences and chaired 15 international conferences. She has received the UTS Medal for Research and Teaching Integration (2010), the UTS Medal for Research Excellence (2019), the Computer Journal Wilkes Award (2018), the IEEE Transactions on Fuzzy Systems Outstanding Paper Award (2019), the Australian Most Innovative Engineer Award (2019) and other national and international awards.