报告人:周晓康 日本滋贺大学数据科学学院

报告时间:2024年3月18日(星期一)下午4:30

报告地点:bat365官网登录235智慧教室

报告摘要:

The high development of emerging computing paradigms, such as Ubiquitous Computing, Mobile Computing, and Social Computing, has brought us a big change from all walks of our work, life, learning and entertainment, along with increasing attention from both academia and industry. In this talk, we concentrate on "Deep Neural Networks for Big Data Analytics in CPSS", specifically, discuss models and methods on big data aggregation, organization and mining using machine learning/deep learning techniques. As for implementations, mechanisms and algorithms are introduced based on the design of several deep neural network models for smart applications, including personalized recommendation, anomaly detection, object detection, data augmentation, developed in modern cyber-physical-social systems.

报告人简介:周晓康，现任日本滋贺大学数据科学学院副教授。2014年毕业于日本早稻田大学，获人类信息科学(Human Sciences)博士学位。2012至2015年，于早稻田大学人间科学学术院任研究助手(Research Associate)。2017年起，于日本理化研究所革新知能综合研究中心（AIP）兼职任客员研究员。主要从事计算机科学，数据科学，及社会人类信息学的跨学科多领域研究工作。研究兴趣包括：大数据、机器学习、行为认知、普适计算智能与安全。发表学术期刊/会议论文170余篇，其中SCI期刊论文110余篇(中科院1区，IEEE/ACM Trans 70余篇，入选ESI高被引15篇，ESI热点7篇)。入选2023斯坦福大学发布全球前2%顶尖科学家。荣获多项国际性奖励与荣誉，如2023, 2020 IEEE SMC Society Andrew P. Sage Best Transactions Paper Award最佳汇刊论文奖, 2023 IEEE Industrial Electronics Society TC-II Best Paper年度最佳期刊论文，2022 IEEE HITC Award for Excellence in Hyper-Intelligence (Early Career Researcher)优秀青年科学家，2021滋贺大学董事长奖，2020 IEEE TCSC Award for Excellence for Early Career Researchers优秀青年科学家等。目前在AIHC担任区域编委，TCE, IoTJ, Big Data Mining and Analytics, JCSC, CAEE, HCIS等担任副编委，并于多个IEEE重要国际学术会议担任程序委员会主席。目前为美国IEEE CS, ACM，日本IPSJ, JSAI，中国CCF会员。