This is about understanding lived realities and context before designing or scaling anything. When you need to make sense of a complex setting, map existing services, or clarify whose needs should drive strategy, I design discovery work that surfaces both human experience and system constraints.

• Research planning and stakeholder alignment across communities, implementers, and funders

• Qualitative work (interviews, focus groups, observations, participatory methods) to understand how people actually live, make decisions, and use services

• Survey and instrument design to capture key outcomes, risks, and protective factors

• Mixed-methods synthesis that triangulates qual and quant evidence

• Clear, accessible readouts that translate findings into options, trade-offs, and next steps for different stakeholders

This is about knowing what’s working, for whom, and under what conditions. I partner with program and policy teams to test interventions, delivery models, and adaptations so they can invest confidently and course-correct early.

• Experimental and quasi-experimental designs for programs, policies, and delivery models

• Pragmatic and implementation-focused trials that fit real-world constraints

• Outcome, process, and equity-focused analyses to see who is being reached and who is left out

• Segmentation and “what works for whom” analyses to inform targeting and tailoring

• Causal inference strategies that help isolate the impact of specific components or strategies

This is about making change stick. I use advanced quantitative methods and implementation science to understand how programs behave inside real systems—and what it takes to adapt, scale, and sustain them while preserving impact and equity.

• Multilevel and longitudinal modeling to understand change over time in children, families, and communities

• Mediation and moderation analyses to unpack mechanisms and identify key levers for impact

• Systems- and pathway-focused thinking to link household experience with services, policies, and structures

• Co-design with end-users and frontline workers to ensure solutions remain feasible, acceptable, and grounded in context

• Developing MEL and research operations frameworks that support consistent, high-quality learning at scale