The 9th International Workshop in Sequential Methodologies (IWSM-2026) will be held on June 1–4, 2026, at American University in Washington, DC. This conference will bring together researchers, practitioners, and students to discuss how data collected over time can be used to make better and faster decisions in areas such as healthcare, finance, security, and artificial intelligence. Sequential methods enable timely decision-making by allowing analysts to evaluate data as they are collected and to determine when sufficient information has been gathered, rather than relying on a fixed, pre-determined sample size. This flexibility can significantly reduce the cost and duration of clinical trials and increase efficiency in healthcare systems. These methods also play a key role in applications such as cybersecurity, threat detection, and industrial quality control, where rapid response to emerging patterns is critical. As modern technologies generate vast streams of real-time data, there is a growing need for methods that can adapt and respond quickly. The workshop will feature four plenary lectures, 43 invited sessions, as well as contributed and poster presentations, totaling approximately 150 presentations across four days, with more than 180 anticipated participants. The goal of this project is to support students and early-career researchers by providing opportunities to present their work, engage with leading experts, and develop professional networks. By fostering collaboration across disciplines and countries, the workshop will help advance data-driven solutions to important societal challenges and contribute to workforce development in the mathematical sciences. The conference focuses on recent advances in sequential methodologies, which are statistical and computational techniques for analyzing data observed over time or collected through adaptive, data-dependent sampling schemes. Topics include sequential testing, change-point detection, clinical trials, s