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学术海报:A Panel Session on Big Data and AI in Transportation Application

发布时间:2018-05-15 10:08:14.0   阅读次数:

主讲人:傅立平,Matthew Muresan,Jameson Yu,蒋朝哲

时间:2018年5月18日16:00

地点:犀浦校区交运大楼417会议室


嘉宾简介

傅立平,男,汉族,1963年9月出生,加拿大国籍,籍贯浙江诸暨,加拿大滑铁卢大学土木工程系教授、滑铁卢大学创新运输系统实验室主任、加拿大土木工程学会运输委员会主席、交通运输研究年会辅助公交委员会委员。加拿大阿尔波特大学博士。西南交通大学特聘教授,2011年入选四川省“百人计划”。傅立平教授是大型复杂交通运输服务系统的优化与评估、管理与运营的决策支持系统领域的国际知名专家。主要研究成果有:专著1部、期刊和会议学术论文100余篇(其中被SCI数据库收录39篇,EI数据库收录55篇)、论文的他引达2686次, h-index为26(其中单篇最高被引用达290次)、授权国际发明专利1项;主持完成了加拿大自然科学基金、加拿大运输部、加拿大安大略省运输部等在内的国家级项目30余项。傅立平教授于2011年荣获加拿大交通运输协会优秀学术贡献奖(该奖项是由加拿大运输部支持,每年评选1-2名在交通领域拥有优秀的领导力、卓越才干、丰硕成果的专家学者。)

Matthew Muresan is a Ph.D. Candidate at the University of Waterloo’s Innovative Transportation Solutions Laboratory currently supervised by Dr. Fu. Matthew’s research is in the area of machine learning and traffic control, specifically the use of Deep Reinforcement Learning as well as applications of Big Data (e.g. Bluetooth and WiFi detections) to solve today’s transportation problems. Prior to this he completed his Master’s degree under the supervision of Dr. Fu and his Bachelor’s from the University of Toronto. He has been awarded scholarship under the NSERC PGS-D program and is a former recipient of the Ontario Graduate Scholarship. In 2017 he was awarded a Mitacs Globalink award to support an academic visit to Wuhan Institute of Technology.

Jameson Yu, a recent University of Waterloo graduate. His major was Software Engineering and he will be starting full time at Amazon in September. He enjoys developing new software and exercising in transportation area.

蒋朝哲,西南交通大学交通运输与物流学院副教授,博士生导师,加拿大滑铁卢大学土木与环境工程系研究员,ITSS-RC实验室执行主任。主持主研国际国家课题10余项,发表学术论文60余篇,SCI收录20余篇,出版著作与教材10余部。主要研究领域:交通规划与管理,交通运输系统工程,交通工程,交通大数据与人工智能,供应链金融等。


演讲内容简介

Matthew Muresan ‘s current research aims to apply machine learning techniques such as Deep Reinforcement Learning (DRL) as an adaptive traffic signal control strategy. His talk discusses an application of DRL to a demonstration case in a simulation environment. An overview of the tools used, including Tensorflow, VISSIM and Python is discussed, including the results of work presented at the previous Transportation Research Board conference.

Jameson’s talk on Apache Spark is intended to give an introduction behind the start of big data. Specifically, how we solve big data problems. From this introduction we lead into Apache Spark, a framework used to tackle the mentioned issues. Demo of a Spark application will be shown during the presentation.