Proposed state-of-the-art distributed computation algorithms for big data processing, where the core is to speed up Top-K items query from distributed large databases with a controllable communication cost. The results have been published in six publications, e.g., IEEE ICASSP, and IEEE GlobalSIP, etc., while two more journal papers with further improvement are near ready for submission to IEEE Transactions on Signal Processing, and Information Theory.

Helped advisor writing a research proposal for big data fusion in Feb., 2016, and gotPhase I approved with $150K.

Served as an engineer at Peking University, and worked for a company having partnership withadvisor in Master study. Used C/C++, OpenCV, and machine learning tools on Windows andLinux, and implemented image processing and pattern recognition systems, including blackscreen detection, image anomaly detection, license plate recognition, and pedestrian detectionon Linux and Windows.

Designed and developed bulletin board systems (BBS), blogs, Web communities, andinformation issuing and management systems for several organizations in Peking University,which included database scripting, management, back-up and recovery systems.

Leading a team of five students for Texas Instruments (TI) Digital Signal Processor (DSP)contests. My role in the project was to preinstall necessary Apps on a TI development board,modify the code on PC and cross-compile it into an executable file on the board, and usePHP+MySQL+Apache to design a UI interface. We won the second prize out of 200+ teamsnational wide, which was the best achievement ever in Peking University. Due to our goodperformance, we were invited to TI DSP Taiwan-Mainland China University DSP InvitationalContest half year later, and won the outstanding prize.