Five MCL Members Attended Viterbi PhD Hooding Ceremony
Five MCL members attended the Viterbi PhD hooding ceremony on Thursday, May 14, 2014, from 8:30-11:00 a.m. in the Bovard Auditorium. They were Sachin Chachada, Xiang Fu, Pang-Chang Lan, Sudeng Hu, and Joe Yuchieh Lin. Congratulations to them and their families for their accomplishments in completing their PhD program at USC.
Sachin Chachada received his B.E. degree in Electronics and Communication Engineering from S.R.K.N.E.C., RTM Nagpur University and an M.S. degree in Electrical Engineering from the University of Southern California (USC). Since 2009, he has been a member in the Media Communications Lab at USC, participating in the fields of statistical signal processing, and machine learning with applications to image and audio analysis. His dissertation, entitled “Environmental Sound Recognition: Classification and Retrieval,” discusses the algorithms that can be used to advance general audio understanding and management. His work demonstrates superior performance of ensemble learning algorithm for environmental audio classification, with use of classical, contemporary and a new set of time-frequency features. His work also includes novel algorithms for environmental sound retrieval for a large database, with promising applications for audio content management.
Xiang Fu received his B.S. degree in Electronic Engineering from Shanghai Jiao Tong University (SJTU), China in 2009, and his M.S. degrees in Electrical Engineering and in Computer Science, both from University of Southern California (USC), Los Angeles in 2011 and 2014, respectively. Since 2011, he has been pursuing his Ph.D. degree in Electrical Engineering with Media Communications Lab (MCL) at USC advised by Prof. C.-C. Jay Kuo, and has been working on various research areas including image/video segmentation, spectral clustering, visual tracking, object recognition, video surveillance, and machine learning. His dissertation, entitled “An Information Fusion Approach to Visual Data Segmentation”, discusses feature fusions [...]









