I graduated with a BSc in Engineering Physics in 2001 from the University of Alberta. I joined the lab in 2002 as a research assistant. In June 2015, I graduated with a PhD in neuroscience from the Graduate Program in Neuroscience at UBC. My CV is on my personal website at Github.
I'm interested in networks of all kinds, but most of all, biological neuronal networks, and most especially, neuronal assemblies. My thesis, Characterizing patches of primary visual cortex with minimal bias, includes an examination of the influence of cortical states on precision and reliability of responses to natural scene movies. I think there's a lot to be said for doing both experimental neurophysiology and theoretical work, so I strive to do both.
Here's my SfN 2007 poster: Accounting for network states in cortex: are (local) pairwise correlations sufficient?
And here's my Cosyne 2006 poster: Heterogenous firing rate dependencies in simultaneously recorded neural populations in cat area 17
You can email me at mspacek (make sure to append @mail.ubc.ca).
I'm a fan of the Python programming language. It's fully object oriented. It's a scripting language, so it doesn't require compiling. If you need the speed of a compiled language, you can easily drop down into C via Cython. Python can interface with just about any library ever written, in almost any language. It's free, open source, cross platform, and widely used. And best of all, it has an extremely intuitive syntax that "fits your brain", making it easy to learn, and easy to remember.
Python, in combination with the NumPy, SciPy, matplotlib, and IPython packages makes a great replacement for MatLab (the expensive, closed-source numerical computing environment). I use Python for spike sorting, data analysis, modelling, and visual stimulus generation. Even this website happens to run on Python.
Here's some software I've written in Python.