Career


Brief Profile:

I hold a PhD in Computer Science from the University of Groningen, the Netherlands. I was awarded an MSc in Computer Science from the Makerere University 2003, and BSc in Mathematics from Makerere University in 1997. I also hold several other postgraduate and professional certificates and diplomas from across the globe.


I have demonstrable skills and good experience in systems analysis, software design, implementation of Management Information Systems, Social registries, and identification systems. I have also demonstrated the ability to work with stakeholders from the diverse backgrounds on complex issues of national and regional importance that have enabled me to lead teams that produce excellent consultancy reports/ outputs within the agreed timeframes.
Currently, I am a consultant for the World Bank, UNICEF, & Development Pathways. I am specifically involved in the establishment of grievance redress and case management systems, social registries, social protection information systems, knowledge management and other undertaking analytic works using statistics and machine learning models
I have been instrumental in the planning and implementation of private sector institutions including ICT Consults Ltd and Uganda Technology and Management University (UTAMU).

Experience with the design and development phases of Integrated Information Management Systems

I have designed and implemented flexible interoperability layers that enable applications to link with each other for automated data transfer and data verification through APIs and RESTful web services. This is demonstrated through several projects I have worked on. Key projects are highlighted below.
I have been providing Technical Assistance and Advisory Services to Ghana, Liberia, Kenya, Malawi, and Sierra Leone, for the development of National Social Registries. Social registries provide a gateway for households to register and be considered for potential inclusion in one or more social programs based on an assessment of their needs and conditions. The assessment usually considers measures of socio-economic status, categorical factors, or a combination of both, which are often criteria used by programs in prioritizing eligibility for benefits and services.

The technical assistance includes a range of activities from conceptualisation, design of national social registries and identification systems using global good practices (e.g. universal access, multifunctional usage, and interoperability).
Below is a list of technical assistance activities, I have been involved in:

  1. Recommendations on design, including:
    • Design options, including cost-benefit analysis of different options, to increase enrolment and coverage.
    • Design options to integrate civil registries, National lD and beneficiary management systems.
    • Guidance on appropriate technology (e.g. enrolment, database structures, interoperability, credential options, deduplication, and cybersecurity).
    • Design sustainable business models of ID systems; and
    • Design authentication systems.
  2. Integrate identification systems into service delivery programs.
  3. Monitoring and evaluation mechanisms.
  4. Ensuring end-user engagement from design through implementation

I have worked extensively with the Governments, large not-for-profit entities (UNICEF, GIZ, UNESCO, etc.), Regulators, Innovators, Accelerators, Incubators, Consumers, startups, and Technology Companies focusing on enhancing the inclusion of Technology to automate business processes. For example, I conceptualised, designed, and implemented the first of the kind paperless public works program in Ghana. This was possible through the use and adoption of open, flexible, inter-operability architecture which could take root and thrive on sub-optimal infrastructure. Such architecture was dependent on: (i) a technology-neutral scaling model, i.e. able to function across the paper, stand-alone mobile devices, and both cable and broadband connection; and (ii) an open standard data transmission and exchange, allowing various sub-systems to integrate through the data repository.
I have provided technical assistance in developing standardization of technical interfaces for the Business Correspondents which allow interoperability and seamless service delivery between citizens.I have undertaken development engagements as an advisor and/or as an implementation partner of new products for monitoring information across social programs. I have detailed experience in the design of Integrated Management Information Systems. The systems I have developed for governments and monitoring authorities have resulted in remarkable improvement in the disbursement of benefits to identified social beneficiaries and equipped authorities with real-time information for making informed decisions.

Contributions to Science


I developed the Astro-WISE (www.astro-wise.org) dependency-based data model that supports scientific use-cases for detecting and analysing Quasi-stellar objects. Quasi-stellar objects (QSOs or quasars) are the active cores of distant galaxies and belong to the most distant objects that can be detected. Galaxies with a massive black hole in their center can have phases of extreme activity in their nuclei due to accretion of mass. Quasars can be brighter than the galaxy that hosts them and can be detected beyond a redshift of 7. Detecting quasars at high redshift probes the Universe at an early age. Quasars can be used to study reionization cosmological structure growth and the formation of supermassive black holes. Finding more high redshift quasars is therefore important to understand the early Universe and how it evolves.
QSO’s are unresolved due to their small size and long-distance. Therefore, they are point sources and cannot be distinguished from stars by their shape. The ultimate way to disentangle quasars from stars is through spectroscopy, which can only be taken for a limited set of sources. The colour properties of quasars and stars are very different and can therefore be used to perform a rough selection to prepare a sample for follow-up spectroscopic observations.

On that side, I developed a data model that accommodates external data and provides the necessary processing, comparison and checking with these external data. I was then able to discover the first high-red shift quasars high redshift quasars at redshift >6.5.
This is the Artificial intelligence process, which involves building instruments calibrating models, and image analysis. I also developed a class-based object versioning framework that supports dynamic changes to pipelines while managing dependencies. The framework addresses the management of arbitrary changes made to scripts during a data row and the association of these changes to data created. This is mainly very important to research and/or scientist as they do, they experiment, most often, they have several results without knowledge of which modification in the scripts produced the results or artefact.