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Inference Engines for Consumer Electronics

Context aware applications can sense, infer, and predict a user's environment in order to provide services that benefit the user by automating processes, providing relevant information, and predicting events or behavior. With the increasing computing power of mobile devices and the increase in bandwidth for wireless communications, mobile devices become a logical platform for context aware applications. Context aware applications for mobile devices can fall into several categories including, but not limited to the following four categories. 1) Adaptive applications alter the state of the mobile device depending upon the context. 2) Sharing applications allow multiple users to share context (e.g., location and presence), media, and/or other information with each other. 3) Context aware search applications allow users to search for more information, which can include looking up a specific topic on the Internet, finding relevant points of interest, and finding locations of friends. 4) Assistive applications aid the user in completing a task more efficiently and smoothly. In Motorola's Application Experience Research Center, we studied driving context, immediate device handling context, and users' lifestyle and usage context to build the next-generation automotive and personal devices. In this talk, I will cover part of our research in developing the driver assistance system, sensor phone and automatic traffic advisory system, such that we can envision that context aware features including a user modeling component will become essential in supporting new applications and concepts that connect consumers with media and services through multiple devices in the office, car, or home.

About the Speaker

Keshu Zhang received the B.S. and Ph.D. degrees with honors from the Mathematics Department of Sichuan University, China, in 1998 and 2002, respectively. Based on the mutual agreement, she also enrolled in the graduate program of the Electrical Engineering Department at the University of New Orleans, where she received the M.S. and Ph.D. degrees in 2001 and 2003.  

Since December 2004, she has been a senior research engineer at Intelligent Systems Lab, Motorola Inc. In July, 2008, she became a principle research engineer at Application and Software Research Center (ASRC) at Motorola, Inc. Her research interests include information fusion, estimation and detection, multi-sensor target tracking, machine learning and information retrieval, data compression, signal processing, and computer vision.  


12032008Zhang.pdf (Presentation PDF)

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