Shuhan Yao

Monash University AI Master’s graduate with expertise in deep learning, machine learning, and Python. Experienced in developing and deploying predictive models for NLP, computer vision, and time-series forecasting, achieving 15%+ performance improvements. Detail-oriented and skilled in project management and critical thinking, with a proven track record of delivering production-ready AI solutions that enhance operational efficiency.

• Career Essentials in Generative AI by Microsoft and Linkedln
• Alibaba LLM trainer

Projects

Multi-Agent Pacman Game AI | Monash University | 2024

• Designed and implemented multiple intelligent agents in Pacman to autonomously plan routes and counter player strategies.
• Applied pathfinding algorithms (A*), adversarial search, and reinforcement learning to enable dynamic, real-time decision-making.
• Achieved 90%+ win rate against human players in testing, demonstrating strong optimization in agent coordination and route planning.

Quarterly Revenue Forecasting with LSTM | Monash University | 2024

• Developed machine learning and deep learning models to predict next-quarter revenue using commercial business datasets.
• Implemented LSTM neural networks and feature engineering for seasonality and trend detection, outperforming baseline regression models by 12% in RMSE reduction.
• Delivered a data pipeline from preprocessing to visualization, enabling stakeholders to make proactive business decisions.