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Angel Njoku

Exploring Neurotechnology | Building Software | Designing Experiences

Designation: Software Developer

Core Directives: Creating intuitive, human-centered solutions at the intersection of neuroscience and AI.

Location: Edmonton, AB

Tech Stack: JavaScript | Python | Java | C/C++ | HTML/CSS | Swift

Frameworks & Libraries: React.js | Node.js | Django | TensorFlow | Firebase | MySQL | PostgreSQL

Tools & Technologies: AWS | Docker | Git/GitHub | CI/CD

[ EDUCATION MODULE ]

B.Sc. Computer Science, University of Alberta

[ EXPERIENCE LOG ]

Neuroengineering Research Student, TUM: Conducted research on wireless brain stimulation and modeled electric coils with Sim4Life and COSMOS.

VP Internal, UABSA: Managed digital platforms for newsletters, scholarships, and student opportunities.

Curriculum and Resource Developer: Created multimedia lesson plans and digital resources for educational engagement.

Description: Auralis is a neurotech project created for natHACKS 2024 that analyzes speech to detect early cognitive decline using NLP and machine learning trained on DementiaNet.

Technoloiges: React.js, Python, Flask, Firebase, TensorFlow, OAuth, Figma.
Status: Backend available on GitHub but not integrated with the live site.
Repository: GitHub
Demo: Live Site
Other: Devpost

Description: Golden Pathways is an AI-powered survey-based system that matches students with academic programs based on their preferences.

Technoloiges: React.js, Python, spaCy, NLTK, OpenAI GPT-4, Figma.
Status: Frontend is fully implemented, backend is in development.
Repository: GitHub
Demo: Coming soon.

Description: Alberta Heart is an interdisciplinary team of engineers researching, designing, and prototyping a Total Artificial Heart for the Heart Hackathon 2025.

Technoloiges: Jetson nano
Status: Conceptual Phase — Currently researching and conceptualizing, with early code development underway.

Description: BoreMe is a neurotechnology-driven system designed for speed-dating that analyzes EEG data in real-time to assess user engagement and determine interest in potential romantic partners.

Technoloiges: Python, Machine Learning, EEG Data Analysis, Adafruit Feather v2, 3D Printing.
Status: Prototype Ready. Basic functionality is complete.
Repository: GitHub
Other: Devpost

Get in touch

Prefer Email? Reach me at: [ eb.angelnjoku@gmail.com ]