Research
My current research follows the One Health framework, where the interconnection of different health spheres - animal health, environmental health and human health - is considered. I want to develop data analytics tools to support evidence-based public health decisions. Currently, I am involved in a project to model potential applications of antimicrobial peptides in the poultry chain and how these applications may impact the burden of Salmonella in poultry and people. In addition, I am also incorporating wastewater signals in the development of short-term predictive models of disease outcomes.
My Ph.D. work developed new algorithms to analyze single-particle tracks. I used tools from applied probability, Bayesian nonparametric, multi-model inference, and diffusion processes. These new algorithms infer multi-states and the parameters associated with which state (diffusivity and transition probability).
- SPT-2E: Two-state hidden Markov model, where each state follows a Brownian motion with experimental errors.
- SPT-infinity: Bayesian nonparametric framework to estimate the number of states that best explain the data. Infinite-state hidden Markov model, where each state follows a Brownian motion with perfect measurement.
- SPT-infinityE: Bayesian nonparametric framework to estimate the number of states that best explain the data. Infinite-state hidden Markov model, where each state follows a Brownian motion with additional noise due to experiments.
- Constrained SPT-2: Constrained two-state hidden Markov model, where transitions between states are constrained to a region of the space.
From September 2020 to December 2020, I worked as a researcher from UBC together with MNP’s data science team. We developed a model to predict and provide a risk assessment of Covid-19 exposure to businesses.
From March 2020 to August 2020, I worked as a math modeller at BCCDC on modelling the Covid-19 epidemic in BC. We focused on the impact of non-pharmaceuticals interventions such as contact tracing and physical distancing. I also designed a model to study the possible vaccination scenarios and their implication on the epidemic curves.
From July 2019 to November 2019, I held a Data science intern position at Visier. There, I developed an algorithm to clean human resources data, improving its consistency and standardization regarding job titles and functions.
In my master, I worked on the study of the fragmentation of a disk by an impact projectile. Using a statistical model for the cracks, the distribution of the area of the fragments was calculated based on how the energy input propagates and dissipates over the material.