daltonpaynedeveloper@gmail.com

Dalton Payne

Data Analytics

&

Artificial Intelligence

Experience

Founder & Lead Developer, Menova AI

Aug 2023 – Present

menovaai.com

  • Founded and developed the App Store's first AI-powered brain-computer interface application for iOS, enabling users to control devices with thought-based commands through the Muse Athena S headband
  • Engineered end-to-end ML pipeline for on-device training and inference on EEG and fNIRS brain data, ensuring user privacy through local processing with zero data sharing
  • Built comprehensive feature set including real-time EEG/fNIRS visualization, custom neurofeedback triggers, 3D brain heat-map analysis, and user-defined state training for personalized brain-computer interaction
  • Designed and implemented intuitive software interface to make brain-computer interface technology accessible to everyday users, managing full product lifecycle from concept to App Store deployment


Education

Master of Science, Data Analytics & Artificial Intelligence

Nova Southeastern University, Fort Lauderdale, FL

2024 – 2026

Relevant Coursework: Data Structures & Algorithms, Database Systems, Data Warehousing, Data Mining, Data Analytics, Data Visualization, Deep Learning, Cybersecurity Fundamentals


Bachelor of Science, Biomedical Science

University of Central Florida, Orlando, FL

2018 – 2024

Relevant Coursework: Statistics, Bioinformatics, Cell Biology, Immunology, Biochemistry, Human Anatomy & Physiology

Competitions

01

  • Analyzed wrist-worn sensor data to identify and classify behavioral patterns from multi-sensor measurements
  • Processed movement, temperature, and proximity sensor data to extract meaningful behavioral indicators
  • Developed classification methodology to distinguish behavioral activities with high accuracy


2025.09.02

02

  • Analyzed satellite telemetry data to identify anomalous patterns and security vulnerabilities in forecasting systems
  • Applied statistical analysis and pattern recognition techniques to detect irregularities in multivariate time series

2025.08.29

03

  • Analyzed business traveler behavior patterns to develop personalized flight recommendation framework
  • Processed pricing, scheduling, route, and user preference data to identify key decision factors
  • Developed ranking methodology to optimize recommendations based on business travel constraints


2025.08.16

04

  • Developed models to forecast housing demand and guide real investment decisions.
  • China's first real-estate demand prediction challenge.

2025.10.22