M.Phil. student BU Shi has been selected by the IEEE Educational Activities Board (EAB) to receive the 2016 IEEE Life Members Graduate Study Fellowship in Electrical Engineering. BU Shi came from mainland China to The Chinese University of Hong Kong (CUHK) to pursue higher education, where he obtained his B.Eng. degree in electronic engineering (EE) in 2014. He then continued his study as an M.Phil. student at CUHK EE. The research area of his undergraduate final year project (FYP) and master’s work is analog IC design, both under the supervision of Prof. LEUNG Ka Nang Alex. Upon his graduation in this July, he will start pursuing the Ph.D. degree in electrical engineering at the University of California, Los Angeles (UCLA) in the US.

Student LO Po Wen and student WANG Chaoqun won the First-Class Award of Information Technology at ‘Challenge Cup’ National Competition Hong Kong Regional Final in Hong Kong University Student Innovation and Entrepreneurship Competition 2016. Their project is called the Continuous Blood Pressure Monitoring System from Face Recognition. It aims at developing a novel physiological monitoring system based on optical recordings and face recognition technique in order to facilitate real time contactless monitoring over a long distance and enable physicians to monitor the real-time situation of multiple patients.

Our graduate student, ZHAO Ping who is supervised by Prof Keli WU,published in HKIE Transactions Vol 23 No 1 with title “A New Computer-aided Tuning Scheme for General Lossy Coupled-resonator Bandpass Filters Based on the Cauchy Method” has been awarded the HKIE Best Transactions Paper Prize 2016.

Congratulations!!

ImageNet Large Scale Visual Recognition Challenge (ILSVRC) is one of the most important grand challenges in computer vision. There are more than 70 top computer vision groups participated in ILSVRC 2015. The CUHK team (CUvideo) including Prof. Wanli Ouyang, Prof. Hongsheng Li, Prof. Xiaogang Wang and five PhD students from EE department participated in ILSVRC 2015 and won the challenge of object detection from videos. CUvideo achieved the mean Averaged Precision (mAP) of 67.8%, while the team in the second place only obtained the mAP of 35.9%. The challenge required detecting 30 object categories from one thousand videos and CUvideo won 28 categories out of them. The CUHK team also ranked NO.2 in object detection in images (Microsoft was the winner). It required detection 200 object categories from 40,000 images. This was the second time for CUHK to participated in this ILSVRC. In ILSVRC2014, the CUHK team ranked the second in object detection in images, while Google was the Winner.