Friday, January 25, 2008

The unemployable programmer

The blog of the IEEE Spectrum has a posting titled “Are Future US Programmers Being Taught to be Unemployable”.  This was a follow up on an article run in the Journal of Defense Software Engineering, on the state of computer science engineering. Now even though, in all times, all places, all fields, there are those who decry the state of education – how the standards of today are a shadow of those of yore, about how we’re cheapening, commercializing, debasing, dumbing-down, (put-your-adverbial-clause-of-choice-here) the education system – there is some merit to the points raised here. The authors talk about the necessity of how formal logic, formal systems, numerical analysis, algorithmic analysis form the basic toolkit of a CS engineer, and how modern teaching approaches fail to adequately impart these skills. Much of their ire is directed against Java as an instructional programming language. To that, I would add MATLAB (as dearly as I love it). To quote the blog, which in turn is a quote from another article (talk about recursive quoting):

 

Dewar says in the interview that, " 'A lot of it is, ‘Let’s make this [computer science and programming] all more fun.’ You know, ‘Math is not fun, let’s reduce math requirements. Algorithms are not fun, let’s get rid of them. Ewww – graphic libraries, they’re fun. Let’s have people mess with libraries. And [forget] all this business about ‘command line’ – we’ll have people use nice visual interfaces where they can point and click and do fancy graphic stuff and have fun.' "

 

While the original article is directed particularly towards undergrad schooling, this is something I would subscribe to at a larger level. I find the CS courses I take extremely light and fluffy, comparatively easy – intellectually, with little or no emphasis on theory – and mostly just “application level” programming – i.e. basically a propagation of “go use some libraries to do some fancy stuff, the math or algorithms of which you don’t need to really understand” philosophy. To get some really heavy duty lifting these days, I have to look outside the department – the first recourse is to the ECE or IND_ENG depts – and if I want to step it up some more, then the MATH department (which gets way too hard for a soft, effete, CS guy like me). For e.g. I took a machine learning course offered by the CSE dept – which was nothing more than a perusal of the “standard algorithms” available and some applications thereof. Now, I’m auditing (that’s all that I dare do) on a Statistical Learning course offered by the STATS dept, which is at a whole other level of math and analysis – hypothesis testing, estimation theory, linear operator theory, functional operator theory, etc.  And this is just an introductory/overview course – it promises to get more rigorous next quarter!

 

And I think, this is not an attribute of CS education in the US alone – but of CS education in general. The other and more established engineering disciplines IMO require a larger amount of rigour and  drilling, to be good at. One reason could be because they deal with the real, physical world, and have to develop a deep appreciation of the laws of physics that govern what they do. Unlike CS – a virtual world, where anything goes (as long as it conforms to basic logic).

 

On an aside, the article states “Seeing a complete Lisp interpreter written in Lisp is an intellectual revelation that all computer scientists should experience.” This, I agree with whole heartedly. Programming the Lisp meta-circular interpreter in CSE755 was the most joy I ever had with the OSU-CSE core curriculum (minus CSE725 – Theory of Computation).

Saturday, January 19, 2008

A Weaker Cheaper MRI

The IEEE Spectrum reports on the development of an MRI machine that operates at a meagre 46 microTeslas (almost the same strength as the earth’s magnetic field , and a hundred thousandth of the field strength of conventional MRI machines, which typically operate at ~1.5Teslas). The stated advantages of these machines are:

Because it needs fewer costly magnets, a weak­magnetic-field MRI machine might cost as little as US $100 000, compared with $1 million or more for a standard MRI system ... But perhaps the most exciting thing about low-field imagers is that they can also perform another imaging technique, magneto­encephalography (MEG), .... MEG measures the magnetic fields produced by brain activity and is used to study seizures. Putting the two imaging modes together could mean matching images of brain activity from MEG with images of brain structure from MRI, and it might make for more precise brain surgery.

Low-field MRI has other advantages, says John Clarke, a physicist at the University of California, Berkeley.... “I’m personally quite excited about the idea of imaging tumors” with low-field MRI, he says. The difference between cancerous and noncancerous tissue is subtle, particularly in breast and prostate tumors, and the high-field strengths used in conventional MRI can drown out the signal. But low-field MRI will be able to detect the differences, Clarke predicts. A low-field MRI might also allow for scans during surgical procedures such as biopsies, because the weaker magnetic field would not heat up or pull at the metal biopsy needle

Now this seems a really exciting development in MRI technology – that would MRIs a practical medical device, rather than the hi-tech hi-cost curiosities they are now. And more than just the points mentioned in this article, the reason I found this technology so alluring is the potential of developing low cost, easily portable and deployable machines that can be used in the small clinics that dot the world, rather than today’s power hungry behemoths that cost a fortune to build and operate and that are available to less than 10% of the world’s population.

 

Sunday, January 13, 2008

The Princeton Companion to Mathematics

I've been reading sample articles of this book from here
If it achieves its purpose, it's a must have...

Friday, January 11, 2008

MICCAI 2008

MICCAI 2008, the 11th International Conference on Medical Image Computing and Computer Assisted Intervention, will be held from September 6 to 9, 2008 in New York City, USA. MICCAI typically attracts over 600 world leading scientists, engineers and clinicians from a wide range of disciplines associated with medical imaging and computer assisted surgery.

Topics

Topics to be addressed at MICCAI 2008 include, but are not limited to:

  • General Medical Image Computing
  • Computer Assisted Interventional Systems and Robotics
  • Visualization and Interaction
  • General Biological and Neuroscience Image Computing
  • Computational Anatomy (statistics on anatomy)
  • Computational Physiology (virtual organs)
  • Innovative Clinical and Biological Applications

Important Dates

January 20, 2008 Tutorial and workshop proposals
February 10, 2008 Acceptance of tutorials and workshops
7 March 2008 Submission of full papers
May 14, 2008 Acceptance of papers
June 9, 2008 Camera ready copy for papers
September 6 - 10, 2008 Tutorials, Conference, Workshops

Submission of Papers

We invite electronic submissions for MICCAI 2008 (LNCS style, double blind review) of up to 8-page papers for oral or poster presentation. Papers will be reviewed by members of the program review committee and assessed for quality and best means of presentation. Besides advances in methodology, we would also like to encourage submission of papers that demonstrate clinical relevance, clinical applications, and validation studies.

Proposals for Tutorials and Workshops

Tutorials will be held on September 6 and/or 9, 2008 and will complement and enhance the scientific program of MICCAI 2008. The purpose of the tutorials is to provide educational material for training new professionals in the field including students, clinicians and new researchers.

Workshops will be held on September 6 and/or 9 2008 and will provide opportunity for discussing technical and application issues in depth. The purpose of the workshops is to provide a comprehensive forum on topics which will not be fully explored during the main conference.

Executive Committee

Leon Axel, New York University, USA (General Co-Chair)
Brian Davies, Imperial College, UK (General Co-Chair)
Dimitris N Metaxas, Rutgers University, USA (General Chair)

Thursday, January 10, 2008

Imaging in Systems Biology

Sean G. Megason1, Corresponding Author Contact Information, E-mail The Corresponding Author and Scott E. Fraser1, Corresponding Author Contact Information, E-mail The Corresponding Author

1Beckman Institute and Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA

Available online 6 September 2007.

Most systems biology approaches involve determining the structure of biological circuits using genomewide “-omic” analyses. Yet imaging offers the unique advantage of watching biological circuits function over time at single-cell resolution in the intact animal. Here, we discuss the power of integrating imaging tools with more conventional -omic approaches to analyze the biological circuits of microorganisms, plants, and animals.

(link)

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