Peter Zhong was an intern at IBM Research Australia in 2013. He worked on building a streaming infrastructure for wireless sensor networks deployed for wildfire monitoring. Peter completed the Ph.D. degree at the Department of Electrical and Electronic Engineering from the University of Melbourne in 2014. During his Ph.D., he investigated a novel plant water-stress sensor using laser speckle analysis techniques. From 2014 to 2016, Peter was a postdoctoral research fellow at the Department of Infrastructure Engineering, University of Melbourne, working on the Resilient Information Systems for Emergency Response (RISER) project. His research focused on collating and processing new spatiotemporal data streams, such as automated sensor networks and human user generated content, to monitor fire hazard and the propagation of firefront in real-time. He investigated the spatiotemporal behavior of bushfire, developing online spatiotemporal algorithms, and building information systems that can transform the data streams into useful bushfire information. In 2016, He joined IBM Research Australia as a staff researcher in the Physical Analytics team, working on satellite imagery analytics for emergency management. In 2017 Peter joined the Decision Science team, leading the development of data-driven decision heuristics. He developed a stock trading strategy, which uses web search traffic to track stock movement. His current research focus is natural language processing. In general, Peter's research interests lie in the areas of machine learning, information science, decision science, spatiotemporal streams processing, disaster management, points pattern recognition, and GIS.