Biography

Isiaha Akatlzin Rodriguez is pursuing a Ph.D. in Applied Mathematics in the School of Mathematical and Statistical Sciences as a Presidential Graduate Fellow. He also has an undergraduate degree in Applied Mathematics from Arizona State University (ASU). His research interests lie in dynamic systems, computational mathematics, and machine learning. Currently, Isiaha's two projects focus on population dynamics (development/analysis of a novel mathematical model of Gestational Diabetes) and studying interactions of autonomous Large Language Model agents (LLM) to investigate LLM bias. During his undergraduate career, Isiaha earned various awards for research and community work. He notably earned the Outstanding Undergraduate Award, which recognized him as one of approximately 16 students out of over 21,000 graduates at ASU for exceptional academic achievement, leadership, and community service.

Academic Status

PhD Student - 1st

Research Area/Department

Applied Mathematics

Major/Specialty

Ph.D (in progress)/Applied Mathematics.

Degrees Earned or in Progress

Bachelors of Science/ Applied Mathematics/2025

Academic Preparation

I have completed advanced coursework in Applied Mathematics, including Image Analysis (MAT 494), Mathematical Modeling (MAT 451), and graduate-level Numerical Linear Algebra and Differential Equations. In MAT 451, I developed turtleABM, a geospatial agent-based model built in Python using Mesa-Geo, GeoPandas, and xarray to simulate post-hatchling sea turtle movement in the Gulf Stream, integrating geospatial data, stochastic processes, and bootstrapped biological parameters. In MAT 494, I co-developed a CNN for cactus species classification, combining YOLOv8 object detection, image preprocessing, and the Discrete Curvelet Transform to achieve over 82% classification accuracy. These projects strengthened my skills in machine learning, numerical modeling, probabilistic simulation, and scientific computing, and together with my ongoing research using Large Language Models (LLMs), have prepared me to apply computational and analytical methods to real-world AI challenges in a research internship setting.

Research/Academic Interests

My research interests lie in dynamical systems, computational mathematics, and machine learning. I am currently pursuing two projects: developing and analyzing a mathematical model of Gestational Diabetes to study population-level disease dynamics, and investigating interactions among autonomous Large Language Model (LLM) agents to better understand and quantify bias in generative systems. Further, I am deeply committed to building inclusive communities of mathematical collaboration. I aspire to contribute both mathematically and socially, by advancing rigorous research while creating pathways for others like me to thrive in the mathematical sciences.

Computational and Data Science Areas

Applied Mathematics; Artificial Intelligence and Intelligent Systems; Statistics and Probability

Motivation

I am interested in developing new AI models and training paradigms that are ethical, equitable, and applicable to solving real-world problems. Through the Sustainable Research Pathways program, I aim to connect with potential collaborators and mentors and refine my dissertation topic in machine learning. Meeting new collaborators would allow me to form an ecosystem of connections, which would not only introduce me to the field but also form long-term projects that would give opportunities to indigenous students to participate in ML research. The Sustainable Horizons Institute's aim to develop more innovative and robust science, through creating inclusive research communities, further motivates my application. Creating and participating in these communities would benefit my research trajectory and allow me to create opportunities for other Indigenous students to engage in machine learning research. Funding to present at conferences in the area of my dissertation would enable me to establish and grow within the community of ML researchers, which serves my long-term research and academic goals.

Lightning Talk Title

Between Culture and Computation

Keywords (Maximum 20 words)

Machine learning; computational mathematics; scientific imaging; inverse problems; applied analysis; optimization; applied AI; numerical modeling; inclusive research; AI for science