School of Electronic Engineering and Computer Science

Miss Xindi Zhang


Room Number: Engineering, Eng 104


Big Data Processing (Undergraduate)

Parallel computing, which implies the simultaneous execution of several processes for solving a single problem, is a mainstream subject with wide ranging implications for computer architecture, algorithms design and programming. The UK has been at the forefront of this technology through its involvement in the development of several innovative architectures. Queen Mary has been actively involved with Parallel Computing for more than a decade. In this module, you will be introduced to parallel computing and will gain first hand experience in relevant techniques. Laboratory work will be based on the MPI (Message Passing Interfaces) standard, running on a network of PCs in the teaching laboratory. The module should be of interest to Computer Scientists and those following joint programmes (eg CS/Maths, CS/Stats). It is also suitable for Chemistry and Engineering students and all those who are concerned with the application of high performance parallel computing for their particular field of study (eg Simulation of chemical Behaviour). The 12-week module involves two hours of timetabled lectures per week. Laboratory sessions are timetabled at two hours per week, normally spanning half the semester only. The module syllabus adopts a hands-on programming stance. In addition, it focuses on algorithms and architectures to familiarise you with messagepassing systems (MPI) as adopted by the industry.

Image Processing (Undergraduate/Postgraduate)

This course gives students an introduction to image processing. Areas covered include image representation, and image transforms, image enhancement using point and spatial operations, image filtering, image restoration, image compression and image segmentation.

Introduction to Multimedia (Undergraduate)

This module unit focuses on the basics concepts on multimedia systems. It introduces the student to the building elements of multimedia computing and their relation with human perception. By the end of the module students should be able to: * understand the difference between analogue and digital * cover the underlying theory of quantisation and sampling for audio, images and video * learn the high-level functioning of the human year and human eye * understand the different colour space representations * understand how to characterise different media through their features * study practical examples of multimedia systems