I am an AI Research Scientist with a PhD in Control and Systems Engineering focused on Computational and Systems Biology, working at the intersection of interpretable machine learning, mechanistic modeling, and systems immunology. My research centers on large-scale multi-omic data integration and gene regulatory network analysis to uncover meaningful biological patterns that advance precision medicine and therapeutic discovery. 

I develop scalable, reproducible AI frameworks using machine learning, deep learning, graph neural networks, and large language models to translate high-dimensional data into interpretable and actionable insights. With over ten years of progressive experience in computational biology and artificial intelligence, I have built high-performance predictive models achieving high accuracies while enabling causal inference and extracting meaningful translational insights from complex, multi-modal biological data. 

I am highly proficient in Python, R, and Bash, experienced in high-performance computing environments, and passionate about collaborative, data-driven biomedical research. Outside of my professional work, I enjoy running, yoga, reading, cooking, and listening to light, relaxing music.