As a researcher working at the intersection of optimal transport, generative modeling, and machine learning, my work directly aligns with VALIANT’s mission of advancing AI through interdisciplinary collaboration. My recent projects explore how geometric learning and probabilistic modeling can enhance the efficiency and interpretability of diffusion-based generative models, with potential applications in scientific domains such as biology and physics. I have also mentored students from diverse academic backgrounds-ranging from signal processing to information theory-on integrating AI tools into their research. I am particularly interested in bridging foundational mathematical tools with real-world AI applications, and I see VALIANT as an ideal environment to expand these efforts through cross-domain exchange and community-focused impact.