This advanced PhD-level course explores cutting-edge developments and emerging trends in computational science, focusing on both theoretical foundations and practical applications. The curriculum is designed to equip students with the latest knowledge and skills required for conducting original research at the intersection of computer science, mathematics, physics, engineering, and data science. Key topics will vary from semester to semester depending on the assigned instructor, ensuring that the course content remains current and relevant. The topics may include high-performance computing, machine learning, computational modeling and simulation, big data analytics, and interdisciplinary computational approaches. Students will engage in critical discussions, hands-on workshops, and projects that challenge them to apply these concepts to real-world problems. By the end of the course, students will have a deep understanding of current research frontiers and be well-prepared to contribute innovative solutions in their respective fields.

CILO-1: Explain and evaluate advanced computational techniques used in scientific simulations. CILO-2: Apply computational methods to solve complex mathematical problems. CILO-3: Conduct independent research using computational methods. CILO-4: Communicate research findings effectively. CILO-5: Collaborate in teams to solve computational challenges.