Séminaire : « Real-Time Intelligent Wildfire Platform – Wildfire Big Data and Machine Learning »

Présentation par Jerry Zeyu Gao de la San Jose State University aux Etats-Unis

Vendredi 1er juillet à 14h, Jerry Zeyu Gao présentera le séminaire ayant pour thème « Real-Time Intelligent Wildfire Platform – Wildfire Big Data and Machine Learning ». 
Ce dernier est un professeur invité du laboratoire et travaille pendant trois semaines avec Oum-El-Kheir. Les discussions pourront être poursuivies au delà du séminaire pendant la pause café hebdomadaire.

Abstract: Wildfires in recent years have destroyed communities, caused server damage to property and human life, and living environment. There were 3,356 fires during the last decade (2009 – 2018), which is 1.4 times greater than the per-decade average number of fires between 1979 and 2009. Total acres burned in the last decade reached 7.08 million acres, which is 1.6 times larger than average per-decade burn area. According to a recent report, there will be increasing trend on wildfires in California in the near future. This brings an urgent call for more researchers in studying and developing new machine learning models based on big data to build next-generation intelligent wildfire platforms and systems to support historical and daily wildfire risk analysis, real-time wildfire detection and tracking, and accurate regional wildfire progression forecast and alerting.
In this talk, Dr. Gao will report the current state-of-the-art research work on wildfire study and analysis using big data and machine learning, including wildfire risk analysis and prediction, detection and tracking, as well as progression forecasting. The talk first reviews and reports current existing wildfire research and systems in a comparative way. Next, it covers diverse wildfire big data and preprocessing for current wildfire research including wildfire history records, satellite images, remote sensing data, drone/aerial camera/LiDAR data, as well as weather station and ground fire sensor datasets. Furthermore, Dr. Gao will present an on-building intelligent wildfire platform, including big data collection and processing, wildfire machine learning models and solutions, system infrastructure and components, and evaluation results. Finally, the future wildfire research topics, challenges and needs are discussed and presented.

Short Bio: Jerry Zeyu Gao is a professor at the Department of Computer Engineering at San Jose State University. Now, he is the director of SJSU research center on Smart Technology, Computing, and Complex Systems. He had over 20 years of academic research and teaching experience and over 10 years of industry working and management experience on software engineering and IT development applications. He has published three technical books and over hundreds (300) publications in IEEE/ACM journals, magazines, international conferences and workshops. His current research areas include smart cities, intelligent system test automation, cloud computing, TaaS, software engineering, test automation, and mobile cloud services. In 2010, Jerry Gao has been recognized by University of Texas at Arlington as a distinguished Alumna for College of Engineering at its 50th anniversary. In 2011, he was award as a KSI Fellow in SEKE2011. In 2013, Dr. Gao has received the College of Engineering Faculty Award for Excellence in scholarship, Dr. Gao served as an editorial
board member and an associate editor for several international journals in software engineering and electronic commerce, such as IEEE Software and International Journal on Software Engineering and Knowledge Engineering. Recently, Dr. Gao has been included and listed in Marquis Who’s Who 2020-2021. In last 10 years, Dr. Gao has played as one of leaders in organizing many international conferences and workshops as a conference co-chair, program co-chair, and workshop co-chair. These include: IEEE CISOSEO2020-2021 and its six IEEE conferences, IEEE BigDataService 2021, IEEEAITest 2020, IEEE AITest2019, Smart World Congress 2017, Smart City Innovation 2017, SEKE06-2016, IEEE MobileCloud2013-2014, IEEE BigDataService 2014-2019, IEEE SOSE2011-2013, ICYCS’05, TQACBS2005-2006, WMCS2004-2010, IEEE EMOBS07-08, TEST’07, and EECC2006. In this year, he served as a conference chair IEEEMobileCloud2014, and workshop program co-chair AST2014. Besides, Dr. Gao has provided his technical consultant and training services for numerous international IT and telecommunication companies, including Fujitsu Network, Intuit, eBay, HP, IBM, Haiwei, Cisco, and UT-StartCom.