alec wong
M.S. ThesisA thesis on sampling methodologies and analytical frameworks for animal abundance estimation. Useful for researchers considering scat surveys with detection dogs, or adaptively-sampled surveys of rare species.
A 'shiny' app for exploring spatial capture-recaptureSCR is a method of estimating animal density from repeated observations of an individual in space. This tool lets you play around with the parameters to see what they all mean.
A distributed computing structure for embarrassingly-parallel tasksUsing SQL, R, your favorite cloud storage, and various packages, easily scale up your embarassingly-parallel computing jobs using a two-layer distributed computation system.
From point processes to kriging, spatial analysis has long been an interest and a focus for my work. Ecological applications are numerous, including the spatially-explicit capture-recapture models of my thesis, and a project involving modeling of infection of a parasite in deer scats as a marked point process.
In business, time-series analysis is de rigueur so my future curriculum will incorporate more of this.
I am extremely familiar with R, comfortable in Python. I'm currently having a lot of fun with bash scripting and operating in linux environments.
I am just a little obsessed with git, having tried to introduce it to two of my teams now.
On github, I have contributed bug-fixes to the R package `boxr` using pull requests from a forked repo.
I have found that sharing knowledge has been a common and rather satisfying thread in my career. I have always identified as a scientist, and whether I end up back in science or remain in business, I will always value the scientific culture of sharing in discovery.
I am working in the Claims Control Staffing & Efficiency department.
In the half-a-year that I have been working here, my work has evolved to have a few foci:
In this course I taught fundamental principles of programming in R. I developed a curriculum to teach syntax, logic, control structures, vectorization, functional programming, and visualization using ggplot, ggvis, and plot.ly. Anonymous evaluations rated overall course satisfaction rated at 9.1 and material retention at 7.3 out of 10.
I developed several analytical methods for sampling moose (Alces alces) in New York and other rare species, assessing their capabilities and limitations via simulation studies. The first of these hierarchical Bayesian networks allow sampling that is conditional on the presence or absence of the species without biasing estimation of density, and the second allows quantification of animal density from surveys of scats using dogs.
I worked to produce a relational database of all wetlands research performed in Nebraska.
I worked to collect forest health data in Van Cortlandt park in an effort to inform restoration activities in parks throughout NYC. Typically, we censused vegetative species, and collected health measurements of the trees we encountered. We also included ground cover and soil descriptions in our assessments.
I assisted an ongoing research study which is a collaboration between The New School, Columbia University, the New York City Department of Parks & Recreation, and the MillionTreesNYC Bloomberg initiative. We censused woody & herbaceous vegetation in long-term ecological research plots across the city, and took soil core samples for determination of the effects of tree & shrub diversity on plot health & incidences of invasive species.
I've had photography as a hobby since around 2013. Here are a few selected works.
See my other websites for more:
