Passy Miano

• Led finalization efforts for the Institutional- and Super Admin Dashboards within the Collaboration and Enhancement Platform (CEP).
• Provided extensive technical support to CEP users, addressing queries, suggestions, and ensuring ongoing maintenance.
• Collaborated closely with i4Policy to implement enhancements based on user feedback, focusing on improving user-friendliness and functionality.
• Documented and facilitated regular meetings between AUDA-NEPAD and GIZ, ensuring effective communication and coordination.
• Facilitated the onboarding of real-time use cases onto the CEP, conducting training sessions for government officials and stakeholders from partner countries while documenting the onboarding journey and lessons learned for future reference.

• Supported the development of the African Union Citizen Engagement Platform, focused on amplifying African citizens participation in policy-making processes. Led pilot initiatives and assessed the platform's applicability across diverse African nations.
• Build dashboard is to simplify data management by creating interactive reports on projects in the directorate Agriculture, Food Security and Environmental Sustainability. The dashboard tracks activities, outputs, and outcomes of the various projects in the directorate in an effort to improve monitoring and evaluation of programs in the institution.
• Manage data throughout its lifecycle, from collection and storage to analysis and visualization to drive project outcomes. This provides meaningful insights that inform decision making for project managers

Key Achievements

• Successful pilot implementation of the Citizen Engagement Platform in Uganda, Cameroon, and Eswatini. Collaborated effectively with key civil society groups, including IDEG and CDEA, demonstrating adaptability and achieving widespread engagement across diverse African contexts.
• Designed and implemented a dashboard that effectively reports on the progress of various projects within the directorate I was assigned to.

• Conducted in-depth research on time-frequency analysis/Machine learning and its application to carbon market forecasting.
• Designed and developed a hybrid forecasting model that combined multiscale analysis techniques with machine learning models.

Key Achievements

• Achieved significant improvement in the prediction accuracy of carbon prices through the implementation of the hybrid model with Mean Squared Error of 0.049.
• Published a research paper in the prestigious Annals of Operations Research, contributing to the field's knowledge and showcasing expertise in the domain.

• Completed data entry tasks with accuracy and efficiency.
• Sorted documents and maintained organized filing process
• Processed insurance claims in accordance with predetermined criteria provided by my supervisor.