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Elements of Big Sensor Data and Computing
====================================================================== Joint Seminars by Dr. Mike LIANG, Dr. Dongmei ZHANG and Dr. Feng ZHAO Date: Thursday, 17 May 2012 Venue: LTK (2/F, near lifts 31 or 32), HKUST ====================================================================== Speaker: Dr. Mike LIANG MSRA Title: "Elements of Big Sensor Data and Computing" Time: 2:30pm - 3:30pm Abstract: Given the ubiquity of networked sensors and actuators, proliferation of smartphones, and ever-increasing urgency to address societal scale challenges, future mobile and sensing systems will have a significant impact on our everyday lives. What is interesting is the fact that data flows within this ecosystem have different characteristics from traditional data previously studied: spatial, environmental, human-behavioral and time-sensitive. And, the volume of these data grows at an increasing rate. Over the past few years, the community has realized the value in gaining insights from these big sensor data, such as the potential in maximizing the business operation efficiency, automating human tasks and so on. To this end, we have been working towards a generalized big sensor data computing framework that consists of data collection, data repository, analytics pipelines, and actuation feedback loop. In this talk, I will introduce the mobile and sensing research at Microsoft Research Asia that surrounds sensory computing. I would like to motivate with interesting scenarios that we have been enabling and also discuss challenges that we have been solving. ***************** Biography: Chieh-Jan Mike Liang is a researcher in the Mobile and Sensing Systems (MASS) group at Microsoft Research Asia. Mike obtained his PhD in computer science in 2011 from the Johns Hopkins University. His research focuses surround the system and networking aspects of sensory and mobile computing. He has published extensively in first-tier conferences, such as ACM SenSys, IPSN, KDD. Among other projects, Mike has been involved in building many large-scale sensor networks, such as the DCGenome project where data centers are instrumented with thousands of sensors to track environment dynamics and equipment bookkeeping.