Didar Ali Didar is technical advisor for monitoring, evaluation, research, and learning (MERL) in Abt’s International Technical Practice (ITP). He has more than 10 years of experience in MERL, project design, and management in the areas of agriculture, food security, economic inclusion, civil society, governance, health, and education. He also has experience in women’s rights advocacy, including designing and implementing advocacy plans and organizing national and international events.
Under the Abt-led, Asian Development Bank-funded Integrated Project Management, Didar provides technical MERL advice to teams to develop and manage the design and monitoring framework for the Asia Pacific Vaccine Access Facility in Samoa, Tonga, Tuvalu, and Vanuatu.
Before joining Abt, Didar worked for the Aga Khan Foundation (AKF) as National MERL manager in Afghanistan. At AKF, he led and managed the M&E for various projects, including the Department of Foreign Affairs and Trade-funded Australia Afghanistan Community Resilience Scheme. He also managed a research project to test the feasibility of using proxy indicators and big data through machine learning to monitor women’s empowerment in Afghanistan. Before that, he worked at the Human Rights Research and Advocacy Consortium to promote women’s leadership in Afghanistan. He has mainly worked in Afghanistan, but also supported projects and innovations implemented in Tajikistan, Pakistan, and Kyrgyzstan.
Since 2015, Didar has supported the United Nations Institute for Training and Research (UNITAR) program as a coach, mentor, and resource person to train Afghan youth leaders.
- Monitoring, evaluation, research and learning
- Design theory of change
- Gender equality
- Participatory and process evaluation (People out of Poverty Index) to identify vulnerable households for emergency response projects
- Asia Pacific Vaccine Access Facility (Samoa, Tonga, Tuvalu and Vanuatu)
- Australia Afghanistan Community Based Resilience Scheme
- Remote Monitoring (feasibility study for using big data, proxy indicators, and machine learning for monitoring women’s empowerment in Afghanistan)
- Afghanistan Health System Action Plan