About

About

Welcome to My Professional Portfolio

I am George Chumbipuma, a Ph.D. student in Computational & Applied Mathematics at Rice University. My academic journey has been shaped by a deep passion for leveraging computational mathematics to solve real-world problems. From numerical methods to high-performance computing, my work integrates mathematical rigor with practical applications.

Research Interests

My research focuses on developing and implementing numerical methods for partial differential equations (PDEs), optimization techniques, and high-performance computing (HPC). Current areas of exploration include:

  • Porous Media Modeling: Learning to apply discontinuous Galerkin methods to solve the Biot equations for coupled flow and deformation.
  • Fracture Mechanics: Investigating phase-field modeling to simulate crack propagation in heterogeneous materials.
  • Scalable Computing: Gaining expertise in parallel computing frameworks such as PETSc and MPI to solve large-scale scientific problems.

I am particularly motivated by applications in energy systems, environmental sustainability, and computational physics. You can explore my ongoing projects and aspirations on the Research page.

Teaching, Mentoring, and Outreach

I am deeply committed to education and mentorship, especially for underrepresented groups in STEM. As a math educator, I strive to create inclusive learning environments that foster curiosity and growth. My experience includes:

  • Serving as a Virtual Math Instructor with the Art of Problem Solving Academy.
  • Founding Pumatics, a tutoring service offering personalized instruction in math, science, computer science, and test preparation. Learn more about this venture on the Tutoring page.
  • Participating in diversity-focused conferences such as the Blackwell-Tapia Conference, GEM Annual Board Meeting, and SACNAS CareerCon, which have inspired me to advocate for inclusivity in academia and beyond.

Education

Rice University, Houston, TX

Doctor of Philosophy – Computational and Applied Mathematics
August 2023 – May 2028 (Expected)

  • GPA: 3.94/4.0
  • Advisor: Dr. Beatrice Riviere
  • Key Courses: Functional Analysis, Advanced Numerical Analysis, Modeling Mathematical Physics, High-Performance Computing

San José State University, San Jose, CA

Master of Science – Mathematics
August 2020 – August 2022

  • GPA: 3.9/4.0
  • Honors: Phi Kappa Phi
  • Advisor: Dr. Slobodan Simić
  • Key Courses: Advanced Matrix Theory, Numerical Partial Differential Equations, Stochastic Processes, Numerical Linear Algebra
  • Research: Applied dynamical systems techniques to analyze stability in cosmological models within the Lambda Cold Dark Matter (ΛCDM) framework.

University of California, Irvine, Irvine, CA

Bachelor of Science – Double Major in Electrical Engineering and Physics
Minor: Information and Computer Science

  • Honors: Tau Beta Pi
  • Key Courses: Data Structures, Numerical Analysis, Statistical Physics, Engineering Probability, Machine Vision, Computer Organization

Vision

Looking ahead, I aspire to become a research scientist at a national laboratory, contributing to advancements in computational science and engineering. I aim to leverage my expertise in scalable numerical methods and HPC to address global challenges in energy, sustainability, and physical sciences.

Feel free to explore the rest of my site for more information about my work, education, and initiatives. Together, let’s build a future powered by innovation and inclusivity.