My research focuses on solving critical decision-making challenges in logistics, healthcare, sustainable energy, and public safety. By integrating combinatorial optimization, machine learning (ML), and artificial intelligence (AI), I develop innovative solutions that provide actionable insights for organizations facing complex, real-world problems, such as drone-aided delivery, radiotherapy in cancer treatment, and the design of large-scale inland wind farms. My work on novel modeling and ML-enhanced strategies for branching, variable reduction, and decomposition has led to breakthroughs in solving these problems optimally, as exemplified by RouteOpt, our open-source software achieving leading performance in optimizing vehicle routes for last-mile delivery. I am also interested in developing zeroth- and first-order methods with provable convergence rates to tackle large-scale, high-dimensional problems arising in modern AI/ML applications and business analytics. Collectively, these efforts promote strategic planning and operational efficiency across engineering and business domains.