Novel applications of statistical machine learning, and artificial intelligence (AI), are emerging everywhere!
Statistical machine learning provides a robust framework for making data-driven decisions by enabling the development of models that can accurately infer patterns and relationships from complex datasets. Additionally, it offers tools for quantifying uncertainty, allowing practitioners to assess the reliability of their predictions and make informed choices in every real-world application. As novel applications continue to evolve, they promise to drive innovation, foster economic growth, and enhance our ability to tackle complex problems, fundamentally altering the way we interact with technology and each other.
Our research in this area focuses on developing novel mathematical and statistical –based machine learning models to address problems in a wide range of fields. It includes, but is not limited to, industrial applications for smart manufacturing, conflict and political violence, video compression, climate informatics, geospatial and earth sciences, applications of information geometry, social media and sport analytics, biodiversity and species interaction, and defense and national security. We aim to build bridges among various scientific disciplines using the power of applied mathematics, computational statistics, and machine learning.