Hello there! My name is Colin Lynch, and I am an animal behavior Ph.D. candidate at Arizona State University. I primarily leverage industrial engineering techniques to design optimal experiments for the study of emergence in complex adaptive systems, and I am looking to use these techniques to acquire a data science internship in R&D. I am specifically interested in reducing research costs by developing optimization methods that minimize sample size while still having a rich enough dataset to perform inferential and predictive analytics. I also use simulations to validate these approaches and to gain deeper insights into the underlying mechanisms that drive complicated systems.

This portfolio is a demonstration of how I use Python, R, MATLAB, JMP, and Netlogo to analyze and model data in domains ranging from biology, archaeology, and business. Examples for how I use different methodologies to address different types of problems are linked below, but if time is of the essence, please see this repository for how I have synthesized many of these skills into a single project.

• Simulations
  • MCMC
  • Discrete Event
  • Multi-Agent
• Machine Learning
  • Clustering
  • Classification
  • Species Dispersal Model
  • Developing Novel ML Algorithm
• Data Analytics
  • Survival Analysis
  • GLM
  • LMM
  • Time Series Analysis
• Optimization
  • Sequential Simplex Search
  • Pareto
  • Scalarization
  • Genetic Algorithm
  • Data Pipeline Design
• Sample Size Estimation
  • Power Analysis
  • Sample Variance Convergence
  • Generalized Power Analysis