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Johnny Guzmán

Associate Professor at Mathematics, Brown University0 Followers

Johnny Guzmán investigates challenges and opportunities in the realm of applied mathematics, with a particular focus on the numerical analysis of partial differential equations and scientific computing. As an Associate Professor at Brown University, he has dedicated his career to advancing the understanding and application of mathematical principles to solve complex scientific problems. Guzmán's academic journey began with a PhD in Applied Mathematics from Cornell University, which he completed in 2005. Following his doctoral studies, he was awarded a prestigious postdoctoral fellowship at the University of Minnesota, where he further honed his research skills and expanded his academic network. His commitment to research excellence led him to join the faculty at Brown University in 2008, where he has been a pivotal member of the Applied Mathematics department. In 2013, Guzmán was promoted to Associate Professor, a testament to his contributions to the field and his dedication to teaching and mentoring students. His research has a strong international dimension, as evidenced by his collaboration with Marcus Sarkis from Brazil's Instituto Nacional de Matemática Pura e Aplicada (IMPA). He is also planning future collaborations with faculty from Brazil’s Laboratório Nacional de Computação Científica, highlighting his commitment to fostering global academic partnerships. Beyond his research, Guzmán is passionate about education and has shared his expertise with students around the world. In 2017, he taught a course at the African Institute for Mathematics-Senegal (AIMS-Senegal), where he engaged with students from diverse backgrounds and contributed to the development of mathematical education in Africa. Throughout his career, Johnny Guzmán has been driven by a desire to push the boundaries of applied mathematics and to inspire the next generation of mathematicians. His work continues to influence both theoretical and practical aspects of scientific computing, making significant impacts in the field.

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