About

See below for a brief background

Education

M.S. in Biomedical Engineering, GPA 3.926/4.0. Expected graduation May 2027.
University of Texas at Dallas
B.S. in Biomedical Engineering, GPA 3.77/4.0. Graduated May 2024.
University of Texas at Dallas

Technical Skills

Tools: 3D CAD, FEBio, Meshlab, 3D Slicer, Gantt Chart
Machine Learning: PyTorch, TensorFlow, MATLAB Deep Learning Toolbox
Computer Language Python MATLAB, Bash, Powershell, HTML, CSS, JavaScript

Experience

Texas Biomedical Device Center, UT Dallas
Software Developer, Research Assistant. Mar. 2025 - Present.

Developed a peripheral nerve stimulation device, enabling synchronized hardware communication, data analysis, and stimulation
Analyzed electromyography data of vocalization muscle, isolating motor unit signals along 64 channels

Neuronal Networks and Interfaces Laboratory, UT Dallas
Research Assistant. Jan. 2021 - Mar. 2024.

Analyzed neural activity in rat motor cortex through implanted microelectrode arrays, improving signal stability and duration by 8-fold
Implemented Butterworth filter on neuronal data, reducing noise by 30%
Handled, habituated, anesthetized, and injected rats to observe change in collection of neuronal activity

Accelerated Research Initiative , UT Austin
Research Intern. Jun. 2018 - Aug. 2018.

Projects

Sleep Structure Study Using Oura Ring

Analyzed continuous sleep structure data over 2 months period, resulting in machine learning models with R² of 0.74
Implemented an ETL pipeline on sleep structure data, reducing misdiagnosis of sleep stage by 70%
Deployed a predictive model to generate sleep debt data, increasing data volume by 8-fold

Deep Learning Model for Age Prediction with Brain MRI
Collaborative work with Dr. Joseph Maldjian and Dr. Kuan Zhang from UTSW Medical Center.

Developed a deep learning model that predicts age from brain MRI volume, resulting in accuracy of +/- 5 years
Implemented an end-to-end automated pipeline for data preparation, visual feature extraction, and regressorage prediction, enabling easy deployment and reproducibility

Bleeding Control Trainer with Augmented Reality Interface
Capstone project sponsored by UTSW Medical Center.

Developed a Unity/C# based AR application for traumatic hemorrhage treatment training
Managed the team using Gantt chart and Work Breakdown Structure, reducing development timeline by 2 weeks

Publications

Jeakle, E. N., et. al. (2023). Chronic stability of local field potentials using amorphous silicon carbide microelectrode arrays implanted in the rat motor cortex. Micromachines, 14(3), 680. https://doi.org/10.3390/mi14030680

Additional Information

Eligible in the U.S. for internships & full-time - no restrictions
English (native) and Japanese (native)