Personal Interest

Computational Cancer Research

Continuously seeking novel and cutting-edge algorithms and pipelines that can be applied to real-time patient decision-making.

Data Science and Machine Learning

Exploring how historical data can be leveraged to rationally predict current outcomes in a real-world context.

Gastrointestinal Cancer Predisposition

Searching new germline variants that could assist families in making informed decisions to prevent cancer within a public context.

Biomarkers in GI tumors

Unraveling how limited data from poorly preserved FFPE samples can contribute to making decisions regarding treatment prediction and survival prognosis.