My research focuses on developing intelligent, data-driven systems for decision-making, with a particular interest in monitoring, fault detection, and diagnosis in complex processes. I work at the intersection of multivariate statistical analysis, machine learning, and artificial intelligence to uncover meaningful patterns in sensor data and enhance system performance. I am especially drawn to the interpretability and applicability of models—how we can move beyond technical accuracy to create solutions that are robust, insightful, and impactful. For me, research is not just about building algorithms; it's about shaping the way we think with data. I strive to ask better questions, challenge assumptions, and transform raw information into actionable knowledge. Ultimately, I see data not as static input but as a dynamic resource—one that, when approached critically and creatively, can lead to innovation, understanding, and change.