Hello there! I have a strong foundation in software engineering, machine learning, and continuous mathematical methods, with practical experience across industry (prev SWE @Databricks) and academia (currently @Stanford HAI). My interests include building reliable & scalable AI solutions, human-centered technology, and predictive modeling using neural networks.
- 🧠 Machine Learning (Supervised, Unsupervised, Reinforcement Learning, Q-Learning)
- 📖 Natural Language Processing
- 📈 Deep Learning
- 📊 Probabilistic & Stochastic Methods
September 2024 – December 2024
- Created a multi-model framework combining SVR and neural networks to predict NBA player rebounds.
- Achieved a profit of 25.96 units and 56.93% prediction accuracy for the 2024–2025 NBA season.
September 2024 – December 2024
- Built a Q-learning model to improve diagnostic accuracy to 91.4% using patient data and feedback loops.
January 2024 – March 2024
- Developed a meal-planning website for Stanford dining halls, accessed by 1,200+ students for real-time nutritional data.
- Email: davidmaemoto@stanford.edu
- LinkedIn: linkedin.com/in/david-maemoto
- Portfolio: davidmaemoto.netlify.app