| November 8, 2024 | |
| • | Registration is now open until December 6, 2024. For details, please refer to the "Registration" section. |
| • | Registration for and attendance at this workshop are free of charge. |
Scientific computing, fundamentally, involves employing computational methods to address partial differential equations that stem from real-world phenomena. It acts as a conduit between theoretical models and practical implementations, empowering researchers to simulate, analyze, and forecast complex phenomena that are either too intricate or too expensive to investigate through experimentation. This discipline is pivotal for deepening our comprehension of various processes in the world and for crafting innovative solutions to urgent challenges within a spectrum of scientific and engineering fields.
Random matrix theory has emerged as a powerful tool with applications spanning from number theory and statistics to wireless communications. Over the past decades, significant theoretical advancements and practical applications have broadened its scope and impact. This workshop aims to foster collaboration among experts in probability theory, statistics, operator algebras, and theoretical physics, driving progress on longstanding conjectures and uncovering novel applications in statistics, machine learning, and quantum information theory.
This workshop brings together researchers from diverse backgrounds and career stages. We particularly emphasize mentoring opportunities for early-career researchers and promoting inclusive excellence in mathematical sciences. The event aims to strengthen international collaborations while fostering the development of the next generation of mathematicians. This workshop is jointly organized by HKUST Jockey Club Institute for Advanced Study (IAS), Hong Kong Women in Mathematics Society, and East Asia Section of Society for Industrial and Applied Mathematics (EASIAM).
