At present, I am involved in teaching at the University of Cambridge both at the
college as well as at the departmental level. At the college level, teaching involves
the so-called supervisions i.e. classes given to small groups of students
(typically 1-2 at one time). On the other hand, I also give the more traditional
lectures at the Department of Engineering.
At the moment I supervise Papers 6 and 7 for Part IB Exams, which include the following topics:
Linear systems and control,
Signal and data analysis, and
In Easter term 2006/2007 I will be giving lectures on "Photo Editing" part of the
"Image Processing" processing course at the Department of Engineering, University of Cambridge. The
syllabus includes [LINK]:
Cropping, resizing, rotation and morphing - involving basic ideas of interpolation and filtering for shifting/resampling purposes.
Colour - conversion between different colour spaces (e.g. RGB, YUV and HSV) and adjustment for colour lighting effects such as colour-cast correction and white balancing.
Histograms - their use in analysis and correction of lighting intensity problems, such as over/under exposure and shadows.
Segmentation - for purposes such as red-eye correction and independent contrast correction in areas of shadows, mid-tones and highlights.
Correcting focus problems - sharpening (debluring) filters and problems of noise amplification.
Correcting noise problems - smoothing filters, problems of blurring, and the use of spatially adaptive filters to optimise sharpening and denoising tradeoffs.
These will be illustrated with the development of Matlab solutions to a range of common photo editing functions such as found in widely used packages like Adobe Photoshop and Microsoft Digital Image Suite.
I am also currently organizing the "Biometrics" course at the British Institute of Technology & E-commerce. The course comprises
a theoretical part, which is covered by 12 lectures, each approximately 2h in length, and 7 computer assignments of total duration of 12h. The lecture syllabus is:
Lecture 1:   The genesis and history of biometry, introduction to biometric systems.
Lecture 2:   Theory of sound and image signal processing.
Lecture 3:   Evaluation of reliability and quality of biometric systems.
Lecture 4:   Fingerprint based recognition.
Lecture 5:   Hand geometry and veins of hand based recognition.
Lecture 6:   Face and face thermogram based recognition.
Lecture 7:   Iris and retina based recognition.
Lecture 8:   Voice based recognition.
Lecture 9:   Handwriting and signature based recognition.