Welcome to my homepage
I am an Applied Scientist at Microsoft.
I worked as a software engineer intern at Numenta, Inc. 2011.
I received my Ph.D. degree on December 2011 from
Oklahoma State University. I have more than 4 years of wearable
computing involved experience. C#, .net, asp, C/C++, MATLAB, and Python programming is
intensively utilized in the projects.
Research Interest
• Machine learning and pattern recognition,
• Intelligent sensing and embedded computation,
• Wearable sensor based human-robot interaction,
• Human intention recognition using dynamic Bayesian network.
Education
Ph.D. in Electrical and Computer Engineering, Oklahoma State University, USA, expected Dec. 2011
• Research areas: Intelligent sensing and Human Intention Recognition.
M.S. in Electrical Engineering, Tsinghua University, Beijing, P. R. China, Jul. 2005
• Dissertation: Power Quality Transient Signal Test And Research of Harmonic Source Identification.
B.S. in Electrical Engineering, Tsinghua University, Beijing, P. R. China, Jul. 2002
• Dissertation: A DSP-based Software System for Power Quality Monitoring in the Power System.
Professional and Experience
• Applied Scientist, (Feb. 2011 - current) Microsoft, Sunnyvale, California, USA
• Software Engineer, (Jun-Aug. 2011), Numenta, Inc. Redwood City, California, USA
• Research Assistant, (Aug. 2007 – Dec. 2011), School of Electrical and Computer Engineering, Oklahoma State University, USA.
• Research Assistant, (Jul. 2001 – Jul. 2005), Dept. of Electrical Engineering, Tsinghua University, Beijing, P.R.China.
• Student Computer Network Administrator, (2000 – 2002) Tsinghua University, Beijing, P.R.China.
Project Involved
• Feb. 2012 - Present: Search engine data analysis.
• Jun.-Aug. 2011, Validated data mining algorithms for pattern recognition and future event prediction. Optimized learning performance using python in Mac Unix system.
• 2007-2011: Human gesture recognition and human behavior recognition method in a Smart Assisted Living (SAIL) System. The gesture recognition is implemented by combining the neural network, the hidden Markov models, and the Bayesian theory to spot hand gestures and body activities.
Videos can be found at http://goo.gl/PcBO8
• Feb.2008-May.2008: Course Project of ECEN5733 Neural Network Design. The convolution neural network (CNN) is implemented to solve real image-recognition problems.
• Aug.2007-Dec.2007: Course Project of ECEN5060 Embedded Sensing and Computing, won the prize of the Second Annual Fall ECEN Design Day 2007. We used the Network Simulator (NS2) as the simulator that can mimic how the networks operate with various structures and how data exchange works under different traffic source behaviors, etc.
• Jul.2001-May.2005 The on-board software system for a DSP-Based Power Quality Monitoring Device. This monitor can identify all kinds of power quality disturbances in electric networks, such as harmonics, voltage unbalance, electric transience, etc. The system was installed in many power plants and factories in China to monitor the power quality. Two conference papers and one journal paper were published on this project.
