Welcome

I am a PhD candidate in statistics at Queen's University in Kingston, Ontario, Canada. My academic supervisor is Dr. David Thomson, originator of the multitaper method of spectrum estimation. Our group at Queen's does research in time series analysis and spectrum estimation, with applications in the natural sciences. I'm currently working on several research projects...

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At Queen's

My thesis research deals with time series analysis in situations when the times are uncertain -- this type of problem arises in the context of paleoenvironmental studies where samples are obtained as a function of depth rather than time. Other research projects that I have been involved with while at Queen's include: forecasting solar activity, interpolation of ground-level ozone records, and data rescue of geomagnetic records from analog images, among others. I have taught the introductory statistics course STAT 263 once and the upper-level/graduate statistics course STAT 462/862 on computational data analysis twice while at Queen's.

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At SFU

I hold a Master of Resource Management degree from Simon Fraser University, British Columbia, Canada. My academic supervisor at SFU was Dr. Sean Cox. My research project was a spatial analysis of British Columbia sablefish fishery catch records. Fishery catch records are often used to compute catch per unit of effort (CPUE) statistics, which are assumed to be an index of fish abundance. However, there is a decoupling of CPUE and fish abundance if fishing operations are able to target high abundance locations preferentially (e.g. Newfoundland cod stocks). By averaging CPUE over space rather than by fishing event, this type of bias can be reduced and a more representative index of abundance results. I have taught the graduate courses REM 612 Simulation Modelling in Natural Resource Management and REM 614 Advanced Methods in Fisheries Assessment while at SFU.

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Other Interests

In my spare time I enjoy running, cooking, skating, homebrewing, and photography. All photos on this website are mine.

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