Writing code is a natural component of my regular workflow. I have experience building software with system-level languages like C and Java, as well as employing scripting languages like Python to process and clean raw data files. A full list of familiar languages and software tools can be found on my resume.
I believe that looking
at the data is a
critical step in almost
any data analysis. As
part of the InfoVis
group at UBC, I have
evaluations since 2005.
In my own experience, I
for exploration of
static tables, and GNU
and R for iterative exploration while developing algorithms.
Stats/ML are a suite of techniques that help build models of data distributions as well as give guidance about how much confidence to put in those models. As a doctoral student, I have devised "unsupervised learning" techniques for data exploration. As a quant, I have used a variety of supervised learning techniques for fitting model parameters and statistical hypothesis testing for confirmatory analyses.
Familiarity with computer graphics APIs like OpenGL has yielded at least two benefits for me as a researcher/analyst. First, I have leveraged the graphics pipeline to build novel visualization techniques that scale to large datasets. Second, I have exploited the parallelism of graphics processors (GPUs) to speed up existing analysis techniques.
My exposure to finance is on the trading side of things. I have researched the following:
Order-book-level market-impact analysis
Long-term trading system development (monthly)
Short-term trading system development (daily)
Trading algorithm ("Algo") development
Automated trading system ("Bot") development
I have been involved in several projects to help researchers navigate unordered collections of documents. These projects are:
My experience with scientific computing has focused on numerical linear algebra and nonlinear optimization, having taken graduate courses in both these topics. In my own research, I have experience with
Nonlinear optimization techniques like Quasi-Newton methods
Fast methods for exact matrix inverses like matrix reordering.
Fast methods for approximate matrix inverses like Krylov subspace, and multigrid methods.
I consulted with BC Cancer Agency to development software for analyzing DNA copy number alterations. The project involved collaborating with the lead researcher, Sohrab Shah, to design a visual console for analyzing copy numbers and labels across chromosomes.