We are creating a fitness application based on movement recognition. The app will ensure you do your sport exercise correctly and give feedback in real-time. • Front-End: Flutter + Native plugins (IOS & Android) to enhance app performance.• Back-End: AWS, including App Sync, DynamoDB, and more.

The goal of my research is to investigate promising ventilation systems in terms of Indoor Air Quality (IAQ), energy consumption, and comfort. More precisely, I have been:• Combining transient (dynamic) and machine learning models to replicate a classroom environment. I designed and assessed several ML models to replicate human behavior, and successfully implemented them into commercial energy software. • Monitoring and investigating the IAQ of New Zealand classrooms. I collected, cleaned, and analyzed a large amount of classroom environmental data. I performed statistical analysis and calculated exposure metrics.• Creating partnerships with large building companies to fund school refurbishments. I secured funding for the installation of smart windows and a heat-recovery ventilation unit. • Part of the RICS research team of the year.

• I optimized and increased the functionalities of a VBA software to estimate the effectiveness of active paints (paints that eliminate air pollutants). The software has been tested and used in the AIMANT study.

• Investigation of the potential of solar air panels as IAQ treatment. Using the software CONTAM, I investigated the effectiveness of different ventilation strategies to reduce CO2 in schools and proposed design amelioration.• Creation of data pipelines and automatic reports to analyze air quality sensor measurements. I used data visualization to summarize the most relevant information and presented it to non-expert stakeholders.