Name: Elijah Valverde
Pronouns: He/Him
Institution: San Francisco State University
Department: Mathematics
Biography:
My name is Elijah Valverde. I am a 2nd year Applied Mathematics major and computer science minor at San Francisco State University. I love mathematics, learning about how math is tied to so many crucial things in our society captivates me and invokes a child-like curiosity that drives me to want to learn more. In my time at SF-State-2 years-I have made dean’s list once and maintained a 4.0 GPA. I am an academic tutor, tutoring economics courses and mathematics courses. Through tutoring I have also found that I have a passion for teaching and sharing the ideas I have learned with others.
Academic Status: Undergraduate Student
Year in program: 2nd
Research Area/Department: Applied Mathematics; Computer Science
Other, specify:
Major/Specialty: I am a major in Applied Mathematics, with a minor in computer science.
Degrees Earned or in Progress: Bachelors in Applied Mathematics, 2nd Year
What courses or academic preparation have you completed to prepare for a summer internship experience?
Differential Calculus Integral Calculus Multivariable Calculus Linear Algebra Java I Java II Modern Algebra Ordinary Differential Equations Real Analysis
Have you published any research or worked on research/technical projects? No
Where has your research been published or where have you conducted research/technical projects?
Please describe your research/academic interests:
I have a strong interest in the intersection of applied mathematics and physics; I am fascinated with differential equations and dynamical systems. Over the last two years I have also become interested in math modeling as I have progressed through my applied math degree. Additionally, my interest in math modeling piqued a fascination and desire to work with high performance computers to solve issues. Conveniently, these interests overlap with my personal interest in climatological issues. I would love to intersect my passions for climatology and mathematics by conducting research that aids in progress towards a better climate for myself and future generations.
Computational and Data Science Areas:
Applied Mathematics; Computational Science Applications, i.e., Bioscience, Cosmology, Chemistry, Environmental Science, Nanotechnology, Climate, etc.; Computer Science; Data Analytics and Visualization
Research Synergy:
Ice sheet modeling plays a crucial role in informing our climate future. Collecting ice sheet data is a process. The current methods are either labor intensive, such as the mass budget method, or, with the altimetry method, have error estimates of up to 50%. To aid in this problem, I propose using Gaussian process regression models to create highly accurate estimates of real world ice sheet modeling data. The primary objective is to leverage high performance computing to compute the large kernel matrices needed for this type of model modification. This will help create predictive distributions of ice sheet measurements that can be utilized for research and predicting outcomes related to sheet ice. By creating predictive distributions of ice sheet measurements we can improve upon current models as well as alleviate the burden of current retrieval methods. This can also accelerate conclusions based on ice sheet data. My objectives include developing a Bayesian model that utilizes Gaussian processes to estimate ice sheet measurements, assuming a Gaussian distribution on ice sheet data such as thickness, flow velocity or temperature. This will also allow us to quantify error which is a very important part of providing a reliable model. We can compare this error with current models such as Ice Sheet and Sea-Level System model (ISSM) I expect to find that the Bayesian Gaussian process model helps improve predictive accuracy and that the uncertainty associated with the model can be minimized compared to current methods. Additionally, it can provide researchers with more data to work with since the model can help improve the data retrieval process. Understanding the behavior of ice sheets and incorporating effective models that aid in the process is vital to our climate future. Modeling ice sheet data can be difficult but I believe that by leveraging a Gaussian process technique we can aid in minimizing this problem and advance our abilities to predict ice sheet dynamics for the future.
Motivation:
My motivation derives from a deep passion for exploring the world of mathematics. Being a first generation college student, my love for math was not always seen as a viable career path. Fortunately, though my parents did not go to college, they were able to work hard and assist me with enough to pursue a college education. Now that I have the opportunity to pursue mathematics, I wish for that pursuit to be generative to society. More specifically, generative for the climate movement. My passion for climate change and the environment is not only due to fear for myself and future generations but also out of a love for the planet. I would relish the opportunity to contribute to climate change research and impacting the planet in a positive way.
Lightning Talk Title: Elijah Valverde: Utilizing Bayesian Gaussian Processes for Ice Sheet Modeling