Han Shao studies the theoretical foundations of machine learning algorithms, including challenges like hallucination and model collapse in large language models.
UMD researchers are exploring how the diverse microbial communities in soil can affect agricultural output, the environment, and human and animal health.
The award recognizes his contributions to the parallel random-access machine theory and as the inventor of fundamental work-efficient parallel algorithms.
