The AHEAD (Agriculture, Healthcare, Environment, Assistive Technologies in Education, and Digital Public Infrastructure) Innovation Hub is a multidisciplinary research and innovation ecosystem within the School of Computing and Engineering Sciences (SCES). It comprises five stand-alone research laboratories, supported by a central Emerging Technologies Convergence Unit. These laboratories are designed to advance applied research, digital transformation, and inclusive innovation across key sectors critical for sustainable development. The hub aims to address pressing development challenges in underserved contexts within low- and middle-income countries (LMICs) by fostering cutting-edge research, nurturing talent, and developing contextually relevant digital solutions.
To be a globally competitive African hub for transformative research and innovation, advancing Africa Agenda 2063 and the Sustainable Development Goals through context-aware digital solutions, talent development, and scalable technologies to improve quality of life.
To cultivate a vibrant, multidisciplinary ecosystem that:
· Conduct high-impact digital development research across key sectors to promote sustainable regional development.
· Develop and deploy context-responsive digital solutions using IS4D, ICT4D, Data for Design (D4D), co-design, frugal innovation, human-centered design, and AI to address pressing African challenges.
· Expand human capital through research, training, and capacity-building initiatives, equipping students, leaders, and professionals with advanced skills and deep understanding of development contexts.
· Support the full innovation lifecycle, from discovery and experimentation to prototyping, piloting, field testing, scaling, and commercialization, ensuring solutions are effective, sustainable, and impactful.
· Foster strategic partnerships with academia, industry, government, NGOs, development partners, and underserved communities to drive innovation, knowledge exchange, and real-world positive outcomes.
The Environmental Intelligence & Climate Resilience Lab utilizes climate science, ecological monitoring, and data analytics to mitigate the impacts of global environmental change. Its methodologies are aligned with international conservation technology initiatives.
Predictive Modeling: Creating sophisticated climate models to forecast environmental shifts and inform long-term planning.
Ecological Monitoring: Developing systems for air-quality tracking, biodiversity mapping, and carbon-sequestration analysis.
Renewable Energy Analytics: Applying data science to optimize the deployment and efficiency of clean energy sources.
Sustainable Strategy: Providing actionable data to help governments and urban planners design climate-resilient infrastructures.
Training & Capacity Building: Delivering structured training programs, workshops, and knowledge-sharing initiatives in climate analytics, environmental monitoring technologies, renewable energy systems, and resilience planning.
(Lab Lead: Dr. M. Ngaruiya -mngaruiya@strathmore.edu)
The Digital Public Infrastructure & Civic Technology Lab researches secure, interoperable systems modernize public administration. The focus is on creating a seamless digital interface between the state and its citizens.
Digital Identity & Trust: Developing secure authentication frameworks and digital ID solutions to facilitate access to services.
Financial Inclusion: Engineering digital payment systems and secure data exchange protocols.
Civic Design: Prioritizing citizen-centric design to ensure public technology is intuitive, inclusive, and transparent.
Cybersecurity: Researching robust defense mechanisms to protect national digital infrastructure and maintain public trust.
Training & Capacity Building: Delivering structured training programs, workshops, and professional development initiatives in digital governance, cybersecurity, digital identity systems, civic technology design, and public sector innovation.
(Lab Lead: Dr. M. Ngaruiya – (mngaruiya@strathmore.edu )
The Agriculture Innovation & AgriTech Lab serves as a cornerstone of the innovation ecosystem, dedicated to the modernization of agricultural practices through the integration of high-tech solutions and data-driven methodologies. By bridging the gap between theoretical research and field application, the lab aims to transform traditional farming into a precise, resilient, and highly productive sector. The lab’s technical agenda is centered on deploying advanced digital tools to solve complex agricultural challenges:
Precision Farming & AI: Utilizing artificial intelligence to provide decision-support systems that optimize resource use and maximize crop performance.
Remote Sensing & IoT: Integrating a network of sensors and drones to monitor crop health, soil moisture, and pest infestations in real-time.
Smart Irrigation: Developing automated systems that conserve water while ensuring plants receive optimal hydration based on localized environmental data.
Crop Genomics: Researching genetic variations to develop crop varieties that are more nutritious and better suited to changing environmental conditions.
Training & Knowledge Transfer: Delivering structured training programs, workshops, and hands-on demonstrations to build capacity in modern farming techniques, digital tools, and agritech innovation.
(Lab Lead: Dr. Vincent Mbanda
The Digital Health & AI‑Driven Healthcare Lab focuses on the creation of digital and AI-supported tools to modernize medical services. It operates at the intersection of technology and public health to strengthen system resilience.
Telemedicine & Mentorship: Developing robust platforms for remote consultation and professional telementorship to bridge the gap in specialist access.
Diagnostic Intelligence: Building advanced algorithms to assist in early disease detection and clinical decision-making.
Wearable Technology: Designing wearable devices that provide real-time health monitoring and data for proactive care.
Data Systems: Establishing secure digital frameworks for the efficient management of health data.
Clinical Collaboration: Working directly with clinicians and public health experts to ensure solutions are scientifically grounded and practically applicable.
Training & Capacity Building: Delivering targeted training programs, workshops, and continuous professional development initiatives in digital health tools, AI applications, data management, and telemedicine practices.
(Lab Lead: Dr. D Nyatuka- dnyatuka@strathmore.edu)
The Assistive Technologies & Inclusive Education Lab focuses on expanding educational access for learners with disabilities. It leverages high-tech interventions to ensure no learner is left behind.
AI Literacy & Recognition: Developing AI-enabled literacy tools and automated sign-language recognition systems.
Adaptive Learning: Designing digital platforms and tactile devices that adjust to the unique needs of the individual learner.
Advanced Neural Interfaces: Exploring the frontier of brain–computer interfaces to provide support for individuals with severe physical or cognitive disabilities.
Accessibility Frameworks: Establishing digital standards to ensure all educational content is universally accessible.
Training & Capacity Building: Delivering targeted training programs, workshops, and certification initiatives in assistive technologies, inclusive pedagogy, AI tools for accessibility, and universal design for learning.
(Lab Lead: Dr. E. Khakata- egathenya@strathmore.edu)
The Emerging Technologies & AI Convergence Unit provides specialized expertise to all other labs. Its operations mirror global AI powerhouses like DeepMind and OpenAI.
AI & Data Science: Developing core AI models and providing data analytics support across the multidisciplinary hub.
Robotics & IoT: Managing Internet of Things platforms and robotics research to automate complex industrial and agricultural tasks.
Infrastructure Management: Maintaining high-performance computing (HPC) environments and preparing for “quantum readiness”.
Ethics & Standards: Establishing the foundational standards for the responsible and ethical development of technology.
(Lab Lead: Dr. P. Macharia – pmacharia@strathmore.edu)
Applying information systems (IS) and information communication technologies to address socio economic development challenges, focusing on context, sustainability, and impact.
Designing high-value digital solutions with limited resources, emphasizing affordability, sustainability, adaptability, and simplicity to meet the needs of underserved populations.
Employing participatory design methodologies, including co-design with stakeholders, to ensure solutions are intuitive, relevant, and effectively address the needs and preferences of target users.
Harnessing AI and machine learning for data analysis, predictive modeling, automation, and intelligent decision support across the thematic areas, with a strong emphasis on ethical AI.
Peer-reviewed journal articles, conference papers, books/book chapters, technical reports, social media platforms
Educational and Training Materials, student project supervision, stakeholder workshops, and webinars
Joint research initiatives, academic exchange programs, interdisciplinary networks, and partnership frameworks formalized through Memoranda of Understanding (MOUs)
Prototypes, patents, datasets, software tools, models and simulations
Data visualizations, dashboards, metadata catalogs, statistical analysis reports, machine learning models or algorithms
Policy briefs, position papers, regulatory guidelines, consultation reports for governments or NGOs, expert testimony
Provision of strategic advisory services, digital transformation roadmaps, system design and implementation support, and evaluation of digital solutions for public and private sector stakeholders
| Project | Aim | Leads | Sponsor |
|---|---|---|---|
| The Kenyan Neonatal Mortality Risk Predictor: A User-Centered Evaluation | Evaluating usability of a LMIC ML model to screen neonatal risk in Kenya using UCD to achieve SDG 3.2 | Dr. Danny Nyatuka and Dr. Rahman Jabin | Royal Academy of Engineering |
| A Chatbot to Enhance Adolescent Mental Health Wellness in Kenya | Improving Kenyan adolescent mental health via co-designed, culturally relevant social media-based digital intervention, Dəˈskəs. | Dr. Paul Macharia and Mr. Rory Assandey | Royal Academy of Engineering |
| Project | Aim | Leads | Sponsor |
|---|---|---|---|
| Feasibility study for Solar-Powered Health Solution (Bright Health) | Feasibility study for Bright Health: energy-efficient digital tools improving healthcare in marginalized LMIC communities | Dr. Danny Nyatuka (PI) and Mr. Pazion T. Cherinet (co-PI) | Royal Academy of Engineering |
| Student | Project Title | Supervisor |
|---|---|---|
| Faith Siva | Cross-Sectoral Leadership in Digital Transformation: A Social Protection Intelligence Framework for Maternal Health and Nutrition in Kenyan Underserved Settings | Dr. Nyatuka |
| James Gikera | A Unified Framework for AI Evaluation in Low-Resource Healthcare Settings: A TEHAI and BS 30440 Synthesis | Dr. Macharia |
| Jevans Omonge | Enhancing Diagnostics of Cervical Cancer Screening Using an Interpretable Joint Deep Learning Model: Integrating Colposcopy Images and Multimodal Data | Dr. Khakata |
| Student | Project Title | Supervisor |
|---|---|---|
| Teresa Ngunjiri | Designing frugal, voice-based mobile reminder system for low-literate pregnant women within Nairobi slums | Dr. Nyatuka |
| Newton Ng'eno | Design and Evaluation of a Data-Driven Scoring Model for Enhancing Investment Readiness among Low-Income Earners in Emerging Economies | Dr. Nyatuka |
| Julius Yogo | A Secure HL7-Enabled API Framework for Interoperability Between DHIS2 and Private Health Information Systems in Kenya | Dr. Nyatuka |
| Edwike Nyauncho | Building a predictive model for drought prediction in Elgeyo Marakwet County | Dr. Macharia |
| Josphine Nyokabi | Developing a predictive model for child speech delay | Dr. Macharia |
| Geofrey Mariara | Developing a risk prediction model at construction sites | Dr. Macharia |
| Janice Gichuhi | A Smart Water Management System for Detecting Household Water Wastage | Dr. Khakata |
| Jackline Chebet | Predicting Tea Crop Outturn Using Random Forest Regression | Dr. Khakata |
| Julia Rutendo | A Predictive Framework for Healthcare Access and Referral Planning | Dr. Khakata |
| Nasra Gedi | Knowledge Retention Model for Enhancing Institutional Memory in Public Institutions: Case of Teachers Service Commission | Dr. Khakata |
| Ntumwa Bulonza | An XGBoost-Driven Risk Prediction Model for Tailored Education on Hypertensive Disorders of Pregnancy Awareness | Dr. Khakata |
| Hub Member | ORCID | Google Scholar / ResearchGate |
|---|---|---|
| Dr. D. Nyatuka | 0000-0001-6251-7695 | Google Scholar |
| Dr. P. Macharia | 0000-0002-3564-8873 | Google Scholar |
| Dr. E. Khakata | 0000-0003-3145-6193 | Google Scholar |
| Dr. M. Ngaruiya | 0000-0001-6442-4951 | Google Scholar |
| Dr. V. Mbandu | 0000-0003-4878-3764 | Google Scholar |
| Ms. F. Siva | 0000-0003-0608-0892 | ResearchGate |
Co-Founder & Lab Lead, Digital Health & HealthTech Lab
A distinguished scholar in Information Systems, ICT4D, and digital health, Dr. Nyatuka holds a PhD in ICT from Cape Peninsula University of Technology. His research leverages frugal digital innovations and people-centered design to address healthcare challenges in resource-constrained African settings. He has led projects funded by the Royal Academy of Engineering, WHO, and the AKTO Academy of Frugal Innovation.
dnyatuka@strathmore.eduCo-Founder & Lab Lead, Emerging Technologies & AI Convergence Unit
A distinguished Computer Scientist and Human-Centered Design researcher, Dr. Macharia spearheaded the establishment of the AHEAD Innovation Hub. His expertise lies in Large Language Models (LLMs) and Edge AI in resource-limited settings. He collaborates internationally with Yale University, Stanford University, University of Washington, and the University of Bradford.
pmacharia@strathmore.eduLab Lead, Innovation & AgriTech Lab | Environmental Intelligence & Climate Resilience Lab
An ICT4D faculty lecturer and consultant with a PhD in Information Systems from the University of Nairobi, Dr. Ngaruiya crafts user-centered, community-led technological solutions across health, agriculture, and financial inclusion. She serves as Chair of the IEEE Women in Engineering – Kenya Section and is a strong advocate for AI and gender equality in technology.
mngaruiya@strathmore.eduLab Lead, Assistive Technologies & Inclusive Education Lab
A technologist with a PhD in Information Technology from Strathmore University, Dr. Khakata is passionate about assistive and inclusive digital solutions for persons with disabilities. She served as Visiting Assistant Professor at the University of Cincinnati in 2023 and is an active voice on Responsible and Ethical AI in Africa.
View Full ProfileLab Lead, Innovation & AgriTech Lab
A distinguished scholar in Artificial Intelligence, Deep Learning, and AgriTech, Dr. Vincent Mbandu Ochango holds a PhD in Information Technology. His research focuses on hybrid deep learning models, computer vision, and decision support systems for crop disease and pest management to enhance sustainable agriculture and food security. He has contributed to curriculum development, AI-driven agricultural innovation, and research in intelligent systems that support farmers and agricultural stakeholders.
vochango@strathmore.edu