报告题目: Digital Forestry Research: Opportunities for Computer Vision, Machine Learning, and Data Science
报 告 人：Dr. Ng Tian Tsong
主 持 人：浦剑 副研究员
邀 请 人：王骏 教授、浦剑 副研究员
报告时间：2018年7月16日 周一 15:00-16:30
报告地点：中北校区数学馆201报告厅

报告人简介：
Dr. Ng Tian Tsong is a Senior Computer Scientist in Scion, a forestry research institute in New Zealand (scionresearch.com). He is a deputy program manager for smart-city video surveillance technology in Institute for Infocomm Research in Singapore. He received his M.Phil. in Signal Processing from Cambridge University in 2001 and his Ph.D. in Electrical Engineering from Columbia University in 2007. His research focus is on computer vision, machine learning, and artificial intelligence. He won the Microsoft Best Student Paper Award at ACM Multimedia Conference in 2005, the John Wiley & Sons Best Paper Award at the first IEEE Workshop in Information Security and Forensics in 2009 and I2R Best Paper Award in 2010. He is a Commonwealth Scholar and an A*STAR Overseas Graduate Scholar.

报告摘要：
Despite being a forestry research institute, Scion focuses on a wider range of research problems that are of interest to the mainstream computer science community than most people could imagine. In this talk, I will introduce Scion, and research problems in Scion that could be new but of interest to the computer science community, in the area of computer vision and machine learning. I will start with a high-level view describing the key economic and social factors that motivate research on forestry research in New Zealand. Then, I will talk about the new wave of forestry data digitalization, and how data science and bioinformatics slowly become a key part of forestry research, which leads to many opportunities for adapting the existing state-of-the-art techniques in machine learning, data science, and computer science for solving high-impact problems in forestry research. I will show snapshots of the on-going research projects within Scion. I will also talk about the opportunities that how Scion and foreign organizations can collaborate.