Tag Archives: Academia

Part time academic

As is possibly quite obvious from an earlier post, I am currently engaged in a course of part time graduate studies.

I’m going to ruminate somewhat on the why and the what here, primarily because I’d like to  improve my writing skills (and therefore need to write more often).

I’ve wanted to further my education and specialise my knowledge with post-graduate study since before I completed my undergraduate, yet it took me a few years to figure out which subset of Computer Science I would attempt to become an expert in. That story, however, would be a significant divergence at this point.

In short I’m studying on a part-time, distance learning, taught Masters program in Intelligent Systems (IS) with the Centre for Computational Intelligence (CCI) at De Montfort University (DMU).

This is essentially a graduate program in Artificial Intelligence (AI), for a definition of which I turn to one of the founders of the field:

“… the science of making machines do things that would require intelligence if done by humans” – Marvin Minsky

and for a slightly longer definition I point interested readers to a definition from the Children’s Britannica by Dr Joanna J. Bryson and Dr Jeremy Wyatt.

Why AI? It’s a field I’ve been interested in since first studying a module in Soft Computing during my undergraduate.

The social scientist in me is intrigued by the idea of pure AI; creating artificial life, observing it grow and evolve, understanding how humans interact with it and how it interacts with humans, etc.

The pragmatist (and idealist) in me, however, is extremely intrigued by the application of computational intelligence techniques to augment the human condition. A future where humans can avoid the 3 D’s of robotics – tasks which are dangerous, dirty and dull.

Many examples of such life enhancing work exists. Originally I had thought to mention (and link to) a great many, but instead I’ve opted to mention only a few current projects I’ve read about recently:

It’s worth noting that I don’t believe the two notions of pure AI and applied AI to be contrary. Indeed it seems that many well respected practitioners work on both theoretical and applied elements of CI. I hope to write more on this in the future.

Why DMU and the CCI? Last autumn I took the free Stanford online AI class and had really enjoyed the fact that I could work through the class without being beholden to a strict schedule which might interfere with my 8-10 hour work days. I wanted to continue this with my further education.

With this in mind I did some research into available distance learning programs and the CCI offers a great course structure with interesting modules taught by a department with a strong publication record and experience of real-world applications of CI techniques.

How is the course so far? I’m a huge fan of the organisation and assessment, so far as I’ve experienced in the single module that I’ve completed this far. The course encourages reading papers and practical application of the techniques.

I can’t wait for the next term to start!

Celebrating the life and work of Alan M. Turing

This past weekend I had the pleasure of attending the ACM’s A.M. Turing Centenary Celebration in San Francisco. It was a fantastic event, as one audience member put it – “it’s like opening a computer history book and having all of the characters step out of the page”.

The celebration featured a diverse range of talks and panels and really emphasised how much impact Turing had on the scientific field he’s arguably the Father of (not to mention the other scientific fields he influenced).

Judea Pearl, Barabra Grosz, Raj Reddy and Edward A. FeigenbaumRon Rivest and Adi ShamirVint Cerf"Information, Data, Security In A Networked Future" PanelDonald E. Knuth"The Algorithmic Universe" Panel
Niklaus Wirth"Programming Languages - Past Achievements And Future Challenges" Panel"Computer Architecture" PanelEdmund ClarkDana S. Scott"The Turing Computational Model And How It Shaped Computer Science" Panel
Alan C. KayFernando J. Corbato and Ken Thompson"Systems, Architecture, Design, Engineering, And Verification - The Practice In Research And Research In Practice" PanelButler LampsonRaj Reddy, Barabra Grosz, Edward A. Feigenbaum and Judea PearlEdward A. Feigenbaum
"Human And Machine Intelligence" PanelTelling Mrs Turing About The Turing AwardBlind ChessRhododendron Invitation"Turing The Man" Panel

Each panel and talk was recorded and webcast on the day and are now available online for viewing, I highly recommend viewing them!

Introspection following a literature review

I’ve just submitted the first paper for my graduate studies – a literature review. Having not yet taken the (mandatory) research methods module offered as part of my program and having spent 2 of the ~4 weeks I had to work on the paper travelling and at conferences – I am left with the feeling that I’ve not done as well as I’d like. Though I’m happier with the paper than I was 24hrs before the submission deadline I’m trying to analyse my process and work out the kinks.

My basic process for this paper was:

  1. Choose a rough topic (we had a choice of two from the module leader).
  2. Find ~15-20 papers on this topic – collect them with some paper managing software and (automatically) tag them with related metadata.
  3. Start reading papers.
    1. Take notes whilst reading the paper.
    2. As soon as possible after reading the paper write a quick summary/review.
    3. Note interesting referenced papers and add them to the collection.
  4. Stop at 11 papers, reject one as not good enough to include in the review.
  5. Figure out a layout for the review based on the themes of the reviewed papers.
  6. Transpose the summary/review pieces into the paper layout.
  7. Iterate over the paper fleshing out the summary/reviews and determining some form of conclusion.
  8. Conclude – in this case pretty poorly.
  9. More iterations for flow, grammar, style, etc. until the deadline arrives.

I think my biggest mistakes were:

  • Curating most of the papers to review before starting to read – I think I could curate a set of papers with a higher correlation, that therefore lead to a stronger conclusion, by starting with a smaller set of papers and utilising more of the references in those papers.
  • Not giving myself enough time to actually pull the reviews together – this wasn’t a conscious decision, mind you.

Having not written a real paper before (discounting any undergraduate efforts) and missing the techniques from the research methods class I’m curious to hear how other folks handle such work?

P.S: my first real use of LyX, what a great program!