Dr. Alemseged Abdissa is Deputy Director General of the Armauer Hansen Research Institute (AHRI) in Ethiopia, a position he has led since 2018. He also an Associate Professor of Microbiology at Jimma University.He has authored more than 124 scientific articles and currently serves as Executive Director of the South and Eastern Africa TB Programs Network, as well as Director of the Pan-African Bioethics Initiative (PABIN).Dr. Abdissa is deeply committed to strengthening research and innovation capacity in Africa. He led the development of a practical guide for institutionalizing research mentorship in low- and middle-income countries (LMICs), in collaboration with WHO/TDR and other partners, and is currently spearheading the creation of a practical guide on AI ethics for innovators in LMICs. He also serves as Vice-Chair of the Governing Board of the European & Developing Countries Clinical Trials Partnership (EDCTP).

Minyahil Tadesse Boltena is Lead of the Artificial Intelligence Innovation Lab at the Armauer Hansen Research Institute (AHRI), where he drives the development of ethical, practical, and scalable AI solutions to improve healthcare outcomes in Ethiopia. He is a member of Ethiopia’s National Artificial Intelligence in Healthcare Programs Technical Working Group and an expert member of the Coalition for Health AI Innovation and Ethics (CHOICE), an Africa CDC initiative led by AHRI. He leads initiatives from innovation to real-world integration of AI solutions in low-resource clinics, including AI-PRESCRIBER, SUSTAIN-AI ECG, AI-HEALS AMR, and AI4GMP, enabling early cardiovascular disease detection, evidence-based antibiotic prescription, and broader clinical decision support. He also serves as Director of Cochrane Ethiopia, overseeing evidence synthesis, guideline development, and multi-stakeholder capacity-building to support evidence-informed decision-making. He has also contributed as a digital health equity consultant, clinical and statistical peer reviewer for The Lancet Regional Health – Western Pacific, and mentor for evidence synthesis programs across Ethiopian universities. Through his leadership, he enabled to develop replicable, context-aware artificial intelligence and machine learning models that strengthen healthcare delivery, reduce inequalities, and save lives across Ethiopia and beyond

Khondaker A. Mamun, PhD is a scientist, AI innovator, and entrepreneur advancing transformative AI solutions for healthcare, education, and human–computer interaction. With a PhD in Biomedical Engineering from the University of Southampton and postdoctoral training at the University of Toronto, he combines deep technical expertise in Brain–Computer Interfaces, neurofeedback, and AI-driven diagnostics with a proven track record of real-world impact. As founder of CMED Health, Mindwave Analytics, TinyTracker, and other AI ventures, and Director of the Institute of Research, Innovation, Incubation and Commercialization (IRIIC) at United International University, he drives research commercialization, inclusive technology, and AI4GOOD initiatives translating innovation into scalable, equitable solutions.

Dr. Paul Springer Dr. Paul Springer is Co-Founder and Managing Director of MI4People gGmbH, a nonprofit advancing Machine Intelligence for social impact, and Head of AI at vtmw AG, leading data science and AI strategy for enterprise applications. He holds a PhD in Theoretical Particle Physics and has extensive experience in technology consulting and applied AI research. Dr. Springer leads the SUSTAIN-AI ECG project in Ethiopia, applying AI-assisted electrocardiography to improve early detection of cardiovascular diseases in resource-limited settings, and the HOPE project in Germany, using AI to personalize addiction treatment and improve therapy access and outcomes. His work bridges cutting-edge AI research with real-world applications that save lives, strengthen healthcare systems, and reduce inequalities. He is passionate about ethical, open-source AI solutions that empower underserved communities and improve societal well-being. Through his initiatives, Dr. Springer advances responsible AI that delivers measurable impact in health, social care, and beyond.

Dr. Maraki Fikre Merid is an Ethiopian‑Canadian healthcare strategist, entrepreneur, and senior consultant with over 18 years of international experience spanning Africa, the Middle East, and North America. She holds a PhD in Health Policy, Management, and Evaluation from the University of Toronto, an MSc in Epidemiology, and a BSc in Biochemistry from McGill University. Dr. Merid is the Managing Partner of CHS Advisory, where she leads strategic consulting, healthcare financing models, and private‑sector engagement to expand affordable, quality care in underserved settings. She has worked with public, private, and donor partners across more than ten African countries, advising on sustainable business models, market diagnostics, and health system strengthening. Based in Addis Ababa, she also co‑founded Youth Education Services to empower Ethiopian youth with practical skills and industry exposure. Dr. Merid is bilingual in English and French and has published research in leading health journals while regularly speaking at global health forums.

Dr. Tsegaye Hailu is a Data Science Division Head at Armauer Hansen Research Institute(AHRI).He has been working in delivering research methodology training, analysis varies project and he has authored and co-authored in the publication of more than 30 cutting –edge research articles on highly reputable peer-reviewed journals.

Dr. Rose Nakasi is a Ugandan AI researcher, lecturer in Computer Science at Makerere University, and Head of the Makerere Artificial Intelligence Health Lab, where she leads groundbreaking work applying AI and data science to healthcare challenges in resource‑limited settings. She holds a PhD in Computer Science from Makerere University with specialization in AI, machine learning, computational mathematics, modeling, and health informatics. Dr. Nakasi is principal investigator of projects like the Google‑funded Ocular mobile microscopy initiative for automated diagnosis of malaria, tuberculosis, and cervical cancer and the NIH‑supported DS‑I Malaria project for AI‑enabled disease surveillance. She chairs the ITU/WHO/WIPO Topic Group on AI‑based Malaria Detection under the Global Initiative AI for Health, contributing to ethical, policy, and international data science governance. Her research emphasizes low‑cost, context‑specific AI tools that improve diagnostic accuracy, strengthen local capacity, and advance inclusive health innovation. Dr. Nakasi is committed to training the next generation of AI scientists and translating research into practical solutions that enhance healthcare delivery across Africa.

Wondwossen Amanuel Hailemariam is a strategic IT executive, cybersecurity expert, and Creator & Lead Developer of the STG Platform Development Team, with over 12 years driving digital transformation, hybrid cloud architectures (Azure, AWS, GCP), and secure innovation in public health. He architects scalable, resilient platforms integrating AI tools, Python/PowerShell automation, Docker containers, and Microsoft Defender Suite for threat hunting, Zero Trust security, and advanced data governance—aligning with Africa CDC’s Digital Transformation Strategy and the AU Continental AI Strategy to enhance epidemic intelligence, predictive analytics, and interoperable health systems. Key achievements include pioneering DHIS2-based vaccine tracking boosting accuracy by 40%, maturing Secure Software Development Lifecycle (SSDLC) for Laboratory NIMS rollout across 7 member states in 12 months, leading zero-downtime Azure/Entra ID migrations, and establishing modern hybrid data centers with cutting-edge security. Holding CISSP, ITIL v4, an MBA, and completing an M.Sc. in Computer Science with Cybersecurity (Abertay University, 2025), he champions innovative, sovereign African digital health solutions—leveraging emerging AI for faster outbreak response, health data sovereignty, and equitable continental impact amid evolving threats.

Simachew Tenagneis Simachew Tenagne is a system administrator and data science professional with strong expertise in information technology, cloud platforms, and research computing. He serves at the Armauer Hansen Research Institute (AHRI), where he administers Oracle Cloud Infrastructure (OCI) and Oracle Fusion ERP, managing enterprise systems, cloud security, and institutional IT operations. His work actively supports the digitalization of organizational and research systems, enhancing operational efficiency, system reliability, and data-driven workflows.He has completed a Master of Science (MSc) in Data Science. His graduate research focused on analyzing large-scale public health datasets, particularly HIV patient data, to predict outcomes and generate insights that inform evidence-based decision-making and research. He has hands-on experience in developing, evaluating, and interpreting machine learning models using real-world data.Simachew is actively engaged in digital health initiatives, integrating data science methodologies with modern IT infrastructure to strengthen health information systems and support data-driven healthcare solutions.

Martha Muluneh is a public health researcher and Master’s student in Data Science at Addis Ababa University, with applied experience in artificial intelligence and machine learning for health analytics and clinical decision support. She has worked as a research consultant on multi regional public health projects in Ethiopia, contributing to data collection, field coordination, data quality assurance, stakeholder engagement, and analytical reporting. Her work combines quantitative and qualitative research methodologies with applied machine learning, including developing and evaluating predictive models using real world health datasets and conducting statistical analysis to support evidence-based decision making. On the AI-POWERED PRESCRIBER project, Martha will contribute to large scale clinical data annotation and standardization, strengthen data quality processes, and support algorithm retraining based on patient outcomes and antimicrobial resistance trends. She will also participate in clinical evaluation of the model and support the integration of explainability features, ethical safeguards, and continuous model monitoring. Her Master’s thesis will be conducted under the project and will focus on evaluating the model’s performance and real-world applicability in Ethiopian healthcare settings.

Solomon Tilahun Kahsay is a Public Health professional and Public Health Data Science trainee with over seven years of experience across clinical care, public health emergency management, and health program leadership in Ethiopia. He is currently completing a Master of Science in Public Health Data Science at Addis Ababa University, where he has developed strong competencies in statistical modeling, machine learning, health data management, and digital health systems. His academic and professional work focuses on disease surveillance, and clinical practice. He has applied machine learning methods to real-world health datasets, including malaria outbreak prediction and disease classification modeling. Through the AI-HEALS AMR project, Solomon aims to work on real-world evaluation, data standardization, and ethical AI deployment for antimicrobial resistance surveillance. His work will emphasize One Health integration, explainable AI, and evidence-based decision support aligned with Ethiopia’s National Action Plan on AMR. He is committed to developing scalable, responsible AI solutions that strengthen clinical decision-making and improve population health outcomes in resource-limited settings.

Matyas Demesew Mengesha is a versatile physician and public health leader with over eight years of experience in clinical medicine, health program management, and technical advisory across Ethiopian Health System. Matyas has a proven record of managing complex health initiatives, having served as a Technical Advisor for regional health bureaus and Mistry of health. His work has spanned across critical domains including Infectious disease, NCDs, MNCH and Disease Surveillance. He is currently advancing his expertise as an MSc candidate in Public Health Data Science at Addis Ababa University, School of information science bridges the gap between clinical practice and AI-driven healthcare solutions combining domain expertise with ML skills. With a deep technical foundation in clinical medicine (MD) and public health (MPH), Matyas is now specializing in the application of Machine Learning, and AI to strengthen African health systems.