About Me

I specialize in developing computational methods and machine learning algorithms for analyzing complex biological data. My work focuses on leveraging both traditional machine learning approaches and deep learning architectures to solve challenging problems in genomics and molecular biology.

Currently at Roche, I am developing bioinformatics solutions for next-generation sequencing applications, with a focus on secondary analysis pipelines. I apply various machine learning techniques, from classical statistical learning methods to modern deep learning architectures, to improve the accuracy and efficiency of genomic data analysis.

My research interests span across machine learning in genomics, optimization of bioinformatics pipelines, and the development of novel computational approaches for analyzing high-throughput sequencing data. I'm particularly passionate about making complex genomic analyses more accurate and computationally efficient through innovative machine learning solutions.

Beyond my professional work, I cherish quality time with my family. You'll often find me on the badminton court, where I enjoy both casual games and competitive matches. I'm also an avid food enthusiast, exploring the Bay Area's diverse culinary scene with my wife. When not coding or playing sports, I enjoy hiking the beautiful trails of Northern California and staying updated with the latest developments in technology and artificial intelligence.