Air Force Research Laboratory
Machine Learning Research Intern
Explainable (XAI) Hierarichal Temporal Memory (HTM) models for anomaly detection and forecasting within Satellite systems
Applied Mathematics Student & ML Researcher
Hi! I'm Aaron, a Korean-American from Cypress, Texas. Currently, I am a Junior at Texas A&M University, studying Applied Mathematics.
I have a strong interest in computational neuroscience and bio/brain-inspired computing, areas that explore how we can use principles from the brain to design smarter, more adaptive technologies.
My journey into this field is personal. I was diagnosed with periventricular leukomalacia (PVL) as a baby, which sparked a lasting curiosity about the brain and its complexities. That early experience continues to inspire my passion for understanding neural systems and building brain-like models through math and computation.
Jun 2024 - Present
Explainable (XAI) Hierarichal Temporal Memory (HTM) models for anomaly detection and forecasting within Satellite systems
Sep 2023 - Present
Biologically motivated Convolutional Neural Networks inspired by the V1 Cortex
Aug 2023 - May 2024
DoD tool enhancement
Jun 2023 - Aug 2023
NLP-powered tool for analyzing temporal academic trends
Developing an application incorporating a Neural Network to generate 3D representations of 2D images.
Technologies: HTML, CSS, JavaScript, Python, PyTorch, Blender API
A convolutional neural network to upscale a video's FPS.
Technologies: Python, PyTorch, OpenCV, CUDA
In preparation for submission to IEEE Aerospace 2026
AI4ALL Student Symposium '25
Developed a ResNet model for automated neuron counting within stained mice brain tissue.
View Publication GitHub RepositoryPersonal Technical Report
A research assistance tool, aimed to offer a streamlined and efficient way to identify trending topics in scientific and academic research.
View Report News Article
© 2025 Aaron Kim