Jiaqi Hu

Currently pursuing an IT master degree with a focus on artificial intelligence and machine learning. I am passionate about the research of Al algorithms and have gained extensive hands-on experience in projects, including data analysis, model construction and optimization.

• IoT-based AI Solution for Smart Cities (09/2024 - 11/2024)

Contributed to a team project developing an interactive tool for time-series data analysis, allowing users to upload PKL files and receive sensor classifications and future value predictions.

— Work I did:

Worked on both the backend and AI teams to deliver key functionalities for this project, I mainly focused on preprocessing and training the XGBoost model for forecasting tasks, ensuring accurate predictions for time-series data. Moreover, I implemented all APIs to enable smooth communication between the React frontend and the AI models.

— Technologies used:

Frontend: React, Material-UI, Axios

Backend: Flask, Flask-CORS

Models: K-Means, XGBoost, LSTM, RandomForest, MLP, Scikit-learn

Innovator Pro Certification

- An AHEGS recognised program delivered by University of New South Wales Employability.

• Comfortable presenting ideas effectively, ensuring efficient resource utilization and team collaboration.
• Skilled in frontend building with React, backend development with Python, Flask, and Docker, with experience deploying models and APIs for applications.
• With hands-on experience in AI tasks, using libraries like scikit-learn, xgboost, lstm.