My research involves combining methods from applied probability, network science, and operations research to approach challenges in public health. I aim to follow a problem-oriented, theory-driven research approach, using data to calibrate or validate but not create models.
My primary focus lies in developing stochastic models for identifying the source and understanding the transmission of spreading processes in networks, with application to foodborne diseases.
My goal is to create a hands-on, engaging teaching environment that helps students to develop the ability to translate global phenomena into mathematical constructs.
Read about my teaching experience