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Matthew Bedder
M. Bedder

IGGI - Elective modules

Monday 28th of September, 2015

Onto the second year of IGGI!

(Has it really been a year already? This is passing by scarily quickly!)

In the second year of IGGI we have to undertake 30 credits worth of modules to justify our EPSRC funding broaden our knowledge of our research areas. Unlike in the first year, however, we get to pick how we get these credits.

There are, of course, some requirements.

First off, the credits have to come from Master's Degree level courses. That's not really a concern for me as it was something that I hadn't really considered - although it might be tempting to take easy modules to fill the requirements, doing so would almost certainly guarantee that all time you spend on it would be wasted. It'd be better to take a harder class so the time is spent learning, right?

The second requirement it that (barring exceptional circumstances) the modules have to be taken in your home institutions. Again, no complaints from me here, as I'd have not wanted to take a course at distance, or commute to London or Colchester.

The third requirement is that the course can be justified as being useful. Again, a bit obvious - as much as I'd like to have taken a course on neurodegenerative diseases so I could better understand the context of some of my old research, it wouldn't really help towards me graduating IGGI. (And I'd likely not understand what the heck is going on).

The final requirement was that it had to be a course that I hadn't already taken in my undergrad degree, or be too similar to one I'd done before.


So I did an undergraduate MEng in CS and AI at York, so I had pretty much exhausted the list of modules that are relevant to my research topic before starting my Ph.D.. Finding three relevant modules (as M-level modules are usually 10 credits at York) would be more difficult than I'd like.

So this year the topics that I will be studying are as follows:

Bio-Inspired Computation (????)

This module is taught in York Department of Electronics by Dr James Walker and is meant to look at a wide variety of bio-inspired computation techniques including neural nets, "normal" genetic approaches, but mostly Cartesian Genetic Programming (CGP). I've come across CGP a bit in some of my previous research, and I think there's the potential for it (and lots of research from our Electronics department) to be exploited more in the area of games AI. Watch this space! :D

It'll also be really interesting to see the differences between the teaching in the Electronics and Computer Science departments here in York, as the departments are separated both academically and geographically despite being very similar.

But alas! As the module isn't from the CS department there is no nice 4-letter code to refer to it by.

Adaptive and Learning Agents (ALAS)

Speaking of ALAS, next up on the modules I'll be taking is Adaptive and Learning Agents by Dimitar Kazakov. This is I think the only Masters-level AI module I was unable to take during my undergrad due to timetable clashes, something I really ended up regretting as my friends raved about it. It's good that I'll get a chance to take it this year, then!

Quantum Information Processing (QIPR)

So the final module choice might seem a bit odd - Quantum Information Processing. Why did I pick this? Well, I can give you three reasons.

First off is the lecturer - Dr Sam Braunstein is a great lecturer. I took the pre-requisite course for QIPR during my MEng and I really enjoyed his teaching style.

Secondly, the topic is really interesting. In the previous course I learnt about quantum algorithms for tasks such as factorisation, which is incredibly important but is not the only interesting potential from the use of quantum computers. Quantum cryptography - that is the use of quantum computers to allow secure communication - is a much more interesting topic for me.

Finally, the module code. QIPR is meant to be pronounced "kipper". I do like me a good module name.