The SIAM-Simons Undergraduate Summer Research Program establishes five sites across the United States each year for a summer program of research and learning in applied mathematics and computational science.
Each year, the SIAM-Simons Undergraduate Summer Research Program will establish five sites across the United States for a program of research and learning in applied mathematics and computational science. One mentor and two students at each site will work together as participants learn how to conduct scientific research, effectively communicate mathematics and computational science principles, and gain an improved understanding of how they can pursue a career in applied mathematics and computational science. Students and mentors from the five sites will come together via video conference to present their work, participate in professional development activities, and engage in community-building initiatives to bring all participants together and foster a strong sense of belonging.
Students accepted to the program will:
This program targets U.S. students from groups underrepresented in applied mathematics and computational mathematics in the U.S., specifically ethnic minorities (African American/Black, Hispanic, Native American/Indigenous Peoples, Native Alaskan, Native Hawaiian/Other Pacific Islander). The program is intended to broaden participation in mathematics by students who are currently underrepresented and historically marginalized in our discipline.
Mentors are selected from SIAM’s experienced and highly qualified member base to work closely with the student participants and SIAM. While mentors do oversee the research activities of the participants, they also serve as a primary connection between the participants and the applied math community broadly, helping them feel connected and welcomed.
You are eligible to apply to be a mentor if you:
*Note that SIAM is not able to sponsor or take over sponsorship of an employment visas.
Mentors will be asked to provide the following as part of their application.
As this program is intended to broaden participation in mathematics by students who are underrepresented and historically marginalized in our discipline, we welcome applications from mentors who also belong to such groups.
Apply now! Log in with your SIAM credentials using SIAMOpenID.
Review of applications will begin September 18, 2023.
The application for summer 2024 will open in December 2023.
You are eligible to apply if you:
Note that this program targets U.S. students from groups underrepresented in applied mathematics and computational mathematics in the U.S., specifically ethnic minorities (African American/Black, Hispanic, Native American/Indigenous Peoples, Native Alaskan, Native Hawaiian/Other Pacific Islander). The program is intended to broaden participation in mathematics by students who are currently underrepresented and historically marginalized in our discipline.
Applicants will be asked to submit:
The Simons Foundation, co-founded in 1994 by Jim and Marilyn Simons, works to advance the frontiers of research in basic science and mathematics. The foundation provides grants to individual investigators and their projects through academic institutions and conducts in-house scientific research supporting teams of top computational scientists through its Flatiron Institute. Jim and Marilyn Simons co-chair the foundation’s board..
SIAM is incredibly grateful to the Simons Foundation for funding this important new program (award number 1036702) that will provide support and career advancement opportunities for undergraduate students who are historically underrepresented in the mathematical and computational sciences.
Computational Methods for Inverse Problems in Imaging In this project, we will work on developing computational methods for solving inverse problems arising from imaging systems. Most of these problems are ill-posed, which means, in most cases, that the solution is very sensitive to the data. Since the data usually contain errors produced by the different imaging systems (e.g., cameras, sensors, etc.), robust and reliable regularization methods need to be developed for computing meaningful solutions. Furthermore, in most imaging systems, massive amounts of data are produced which makes the acquisition and the storage of data and the computational cost of the inversion process intractable. To deal with these issues, we will investigate the algebraic tensor structure of the data, apply dimension reduction techniques and study its impact in the inversion process.
Participants: Kelsi Anderson and Ashley Ramsay-Allison
Mentor: Malena Español
Program MASTER: Modeling, Analysis and Simulation for the grand challenges through innovative Training, Education and Research Over the years, the importance of mathematical modeling and its applications to solve real-world challenges has been rapidly increasing. Also, there is a great demand for combining modeling with multidisciplinary problem-solving competencies and life-long learning skills for addressing the global challenges such as, understanding the dynamics of COVID-19 epidemic to impact of Domestic Violence. This program will expose two motivated undergraduate students to advanced topics in mathematics, problem-solving, data driven approaches, computing, visualization techniques and multidisciplinary applications. The program will also greatly enhance the awareness of the ever-increasing utility of mathematical approaches in understanding biological, engineering and bio-inspired systems and how they can help contribute to the scientific and professional development of students at all levels.
Participants: Adan Baca and Diego Gonzalez
Mentor: Dr. Padmanabhan (Padhu) Seshaiyer
Identifying Novel Biomarkers for Cancer Treatment Personalization This project will focus on analyzing clinical data and developing mathematical models to identify novel biomarkers for cancer treatment personalization. We are situated in the unique Integrated Mathematical Oncology (IMO) department at Moffitt Cancer Center, the only math department within an NCI-designated cancer center. The IMO is a highly interdisciplinary and collaborative department with researchers from various backgrounds.
Participants: Moriam Animashaun and Layla Montemayor
Mentors: Dr. Heiko Enderling and Dr. Renee Brady-Nicholls
Minimum Cycle Basis for Pose Graph Optimization Pose graph optimization (PGO) is a fundamental problem that arises in various research disciplines, like simultaneous localization and mapping (SLAM), structure from motion, calibration of multi-camera rig, and sensor network localization. For this project, we will focus on the minimum cycle basis problem and its usage for pose graph optimization.
Participants: Rachel Ahumada and Drake Lewis
Mentor: Dr. Illya V. Hicks
Cost/benefit analysis of yearly mammograms: a social justice approach to individualized medicine The current U.S. guidelines state that women over 40 need to get a mammogram every year. Some researchers claim that the recent decrease in breast cancer deaths can be attributed to this recommendation. However, mammograms are invasive and known to have a high rate of false positive diagnosis. Other countries have piloted different requirements depending on family history, breast density, among other factors. In this project we will take a data driven approach to propose personalized testing protocols that will take to account factors such as family history and breast density while trying to offer solutions that take into account access to health care, economic background, race and other markers that have a significant impact on health outcomes.
Participants: Amira Claxton and America Jarillo-Montero
Mentor: Dr. Alicia Prieto-Langarica
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