Created the web-based Muhammadiyah Welfare Hub (voucher system + online store + task system) and supported website UI and materials; selected as a finalist among 350+ participants.

• Built the Muhammadiyah Welfare Hub for Muhammadiyah Welfare Home's residents and staff.
• Aided development with 2 teammates (data population w/ Postman, website UI, README.md).
• Developed using Clerk, MongoDB, Vercel and Springboot; deployed on Vercel.

Optimised hydrogen production methods (SMR, Carbon Capture) for cost while meeting environmental regulatory standards, and evaluated transportation options in the US.

• Minimised transportation costs across US options (pipelines and trucking) using Transportation Simplex Method.
• Produced overall analysis and improvement outlook across production and transportation methods, including future policy and long-run cost considerations.

Conducted extensive research and presented on Traditional Ecological Knowledge (TEK).

• Discussed current issues with natural resource politics.
• Considered 3 points of view relating to TEK, including indigenous knowledge adaptation, TEK’s role in climate policies, and implications for modern resource policy approaches.

Analysed both financial and non-financial factors to conclude on the most financially and environmentally feasible energy production strategy for Singapore in the long run.

• Concluded on the most financially and environmentally feasible energy production strategy for Singapore in the long run.
• Financial analysis: cash flow analysis, probabilistic risk analysis, and @Risk diagrams (Tornado, Spider).
• Non-financial analysis: Life-Cycle Analysis (LCA) and Analytical Hierarchy Process (AHP).

Produced a project management plan for the implementation of automated baggage carts within Changi Airport using common project management tools and risk strategy.

• Utilised project management tools such as Gantt charts, procurement planning, HR structuring, and project risk strategy.
• Did a final presentation on the end-to-end implementation of our initiative.

Built a diabetes classifier using various models after demonstrating data cleaning; concluded with a model achieving 93% accuracy.

• Identified the classifier model most accurate for predicting diabetes based on lifestyle factors.
• Demonstrated data cleaning and implemented models (KNN, Naive Bayes, logistic regression, decision trees).

Designed and implemented an Excel/VBA-based ride hailing price prediction tool using regression modelling and R analysis.

• Compared ride-hailing options using a regression model based on ride type and distance.
• Performed analysis on R, including p-value analysis.