AI Research in Environmental Monitoring

During my AI Research Fellowship at Creative Inquiry, I worked on developing cutting-edge solutions for environmental monitoring. Our team created an AI model for air quality prediction using LSTM-FCN architecture, capable of processing both spatial and temporal environmental data.

Leading a team of 5 members, I learned valuable lessons about project management and technical leadership. We focused on optimizing our data collection process, achieving a 30% reduction in collection time while maintaining high accuracy standards.

The project involved extensive work with public APIs and data validation, teaching me the importance of data quality in machine learning applications.