GC-SAML (Genetic Construct Sensitity Analysis & Machine Learning) aims towards understanding the complex interactions between different characteristics of genetic constructs through the use of MGDrivE simulations analyzed through the MoNeT pipelines.
MGSurvE (MGSurvE: Mosquito Gene SurveillancE) is a software package created to optimize the distribution of mosquito traps in complex heterogeneous landscapes.
MoNeT (Mosquito Networks Taskforce) was born in efforts to come up with standardized methods to understand and analyze complex spatial mosquito behavior.
MGDrivE (Mosquito Gene Drive Explorer) is a mathematical model created to test and compare gene-drive constructs to reduce the spread of mosquito-borne diseases in complex spatial contexts.
PajaroLoco was a Mathematica package developed to perform linguistic analysis on birds’ tagged songs through the use of network theory and clustering techniques.
SoNA3BS (Social Networks Aedes aegypti Agent-Based Simulation) was a NetLogo simulation developed to understand and teach about the community effects of mosquito-transmitted diseases through the use of network theory.
Before shifting to working in Public Health, I did some work in computer vision and humanoid robots as part of a couple of research internships.