

Bo-Wen Shen
Dr. Bo-Wen Shen is at the forefront of discovery in the fields of mathematics and atmospheric sciences, serving as an Associate Professor in the College of Sciences at San Diego State University. With a specialization in Mathematics and Statistics, Dr. Shen's research is pivotal in advancing our understanding of nonlinear dynamics and their applications in global weather and climate modeling. His work is instrumental in enhancing the accuracy of hurricane predictions, a critical area of study given the increasing frequency and intensity of these natural phenomena. Dr. Shen's research portfolio is marked by a deep engagement with big data analysis, which he leverages to unravel complex patterns in climate systems. His scholarly contributions include significant publications such as "Is Weather Chaotic? Coexistence of Chaos and Order within a Generalized Lorenz Model" and "Aggregated Negative Feedback in a Generalized Lorenz Model." These works reflect his commitment to exploring the intricate balance between chaos and order in atmospheric dynamics, offering insights that are crucial for both theoretical advancements and practical applications in weather forecasting. In addition to his research, Dr. Shen is dedicated to mentoring the next generation of scientists, fostering a collaborative and innovative learning environment at San Diego State University. His teaching philosophy emphasizes the integration of theoretical knowledge with practical skills, preparing students to tackle complex challenges in the field of climate science. Dr. Shen's contributions extend beyond academia, as he actively collaborates with international research communities to address global challenges related to climate change and extreme weather events. His work not only enhances scientific understanding but also informs policy and decision-making processes aimed at mitigating the impacts of climate variability and change.
Publications
, 189-203, 2016-07-08
, 2016-02-24
, 2023-08-01
, 281, 2019-06-26
, 1950037, 2019-03-01
, 2161-2182, 2024-09-25
, 2050257, 2020-11-01
, 1701-1723, 2014-04-28