Research
The Aga Khan University Data Innovation Office (DIO) carries out research to offer insight on how to utilize constrained resources using analytics from low and middle income countries to foster development through innovative and impactful solutions.
The university invested in the creation of the Data Innovation Office that is focused in supporting research projects that employ data intensive methodologies. The DIO deploys all projects on a modern data stack utilizing cloud technologies and open-source algorithms. A key mandate for the DIO is to leverage data in innovative ways to address population health challenges in East Africa thereby leapfrogging over many traditional Western methodologies.
All research projects supported by the DIO team embrace a 'cloud-first, open-source' architecture approach, ensuring efficient and scalable solutions. We remain agile, constantly iterating based on emerging open-source algorithms, standards, and methodologies. Our practices are deeply rooted in compliance with data protection laws, prioritizing alignment with the regulatory landscape of our country. Operating within the constraints of low- and middle-income countries (LMICs), we are mindful of budgetary limitations, optimizing our strategies to deliver impactful outcomes cost-effectively. Our commitment to leveraging cutting-edge technologies within these parameters underscores our dedication to advancing research and innovation in AI and data science.
What is an example of your office supporting researchers?
A researcher wants to undertake a study on prevalence of heart attacks amongst elderly population in the urban areas of Kenya.
Data Source: We provide anonymized medical records from the health data repository to support their grant application.
Data Preparation: Our data engineers clean and process the data to make it ready for analysis.
Data Infrastructure: The Data Innovation Office establishes systems for storage and processing of data to make sure they’re compatible and compliant with data privacy regulations.
Consultation and training: We advice on applicable AI models that can be used for predictive analysis
Privacy and Ethics: We ensure compliance with data privacy regulations and ethical guidelines throughout the pipeline.
