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Dr Ang Mia Yang is a researcher and educator specializing in clinical bioinformatics. His academic trajectory has been supported by competitive government funding, notably the MEXT Scholarship from the Japanese government for his doctoral training at The University of Tokyo, and a JPA scholarship for his local studies in Malaysia.

His research focuses on the transition toward data-driven precision medicine by integrating multi-omics data with machine learning to identify specific genetic and environmental markers of health. Through various research collaborations, he performs advanced bioinformatics analyses to map complex biological landscapes, such as the genetic drivers of obesity to pinpoint potential causal genes and therapeutic targets.

Another core component of his expertise lies in microbial genomics and the development of specialized bioinformatic tools designed to facilitate research. He co-developed the AMRColab platform, a tool for antimicrobial resistance surveillance supported by the Bill & Melinda Gates Foundation via PHA4GE. He also co-developed several tools for microbial genome analysis, including FusoBase and MycoBase, which provide the scientific community with accessible infrastructure for comparative genomics.

His technical background is further supported by experience in managing High-Performance Computing (HPC) environments and building reproducible bioinformatic pipelines. Dr Yang's professional work spans academia, government-linked scientific initiatives, and industry. He is an Affiliate Member of the Young Scientist Network - Academy of Sciences Malaysia (YSN-ASM) and serves as a Key Opinion Leader (KOL) in Bioinformatics, AI, and Machine Learning for the private sector.

His professional footprint includes ongoing international collaborations, particularly with partners in Japan, China, Indonesia, the Philippines, and the UAE. In his teaching role, Dr Yang utilizes hands-on, project-based learning to prepare the next generation of biomedical scientists. His approach emphasizes the practical application of industry-standard computational tools and the development of systematic analytical frameworks, ensuring that students are prepared to navigate the evolving demands of the global life sciences landscape.