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【创源大讲堂】Towards Effective Anomaly Detection

来源:计算机与人工智能学院 日期:2024/05/08 14:12:32 点击数:
时间 地点
报告人 内容简介

讲座时间:20240511日(星期11:30

讲座地点:犀浦校区3号教学楼X31541报告厅

主讲人:Samuel Moore 博士

主讲人简介:

Dr Samuel Moore is a Lecturer in Computing Science in the School of Computing, Ulster University. His research primarily concerns Artificial Intelligence, ethics and explainability of AI, and reliability of AI, the Internet of Things, Cybersecurity and Pervasive Computing. He is actively involved in research in the School of Computing, and currently is a co-investigator with the PwC ARC research project. Within the project, he is the lead of the Financial Crime workstream, where he leads a team of researchers developing a set of AI-driven tools for financial compliance. The work examines Natural Language Processing, Risk Management and Financial Crime, which aims to develop explainable AI methods for dealing with Financial Crime and KYC processes.

内容简介:

The Internet of Things (IoT) is rapidly changing the way in which we engage with technology on a daily basis. The IoT paradigm enables low-resource devices to intercommunicate in a fully flexible and pervasive manner, and the data from these devices is used for decision-making in critical applications such as; traffic infrastructure, health-care and home security, to name but a few. Due to the scarce resources available in these IoT devices, being able to reason about the reliability of them is essential. This talk will present recent research within the area of IoT reliability, anomaly detection, and the usage of Artificial Intelligence to enhance and quantify the state of performance within modern IoT systems.



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作者:邹远   编辑:蔡京君   


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