Who we are
Guided by humanity, driven by compassion
At our core, we are driven by a simple but powerful belief: technology should serve people, not the other way around. Our organization brings together expertise in health sciences, artificial intelligence, data analytics, and public health research to address some of the most urgent healthcare challenges of our time.
We work at the intersection of health, data, policy, and innovation. This allows us to ensure that insights generated from advanced analytics are not only scientifically rigorous, but also ethical, context-aware, and responsive to real human needs. Every project we undertake is grounded in compassion, guided by evidence, and designed to deliver measurable impact.
Our approach emphasizes translation. We do not stop at discovery or analysis. We focus on ensuring that research findings move beyond academic spaces and inform policies, programs, and interventions that improve lives.
The challenge in healthcare
Despite unprecedented growth in health research and digital health systems, critical gaps persist that limit the effectiveness of healthcare delivery worldwide.
Underutilized Health Data
Healthcare providers and decision-makers lack timely, research-backed evidence, slowing effective responses and policy decisions.
Limited Access to Evidence
Limited access to timely, research-backed evidence hinders rapid health responses and sound policy decisions.
Health Inequities in Underserved Communities
Limited access to data and technology drives unequal disease burdens and weakens health systems.
Slow Translation of Research into Practice
Delays in translating research into practice limit impact and leave communities waiting for existing solutions.
Our core focus areas
Our core focus areas define how we apply data, NLP, and research to address critical health challenges.
Biomedical & Public Health Research
We conduct interdisciplinary research that combines data science, epidemiology, and health systems research to inform evidence-based interventions and policies.
AI for Health Equity
We design and deploy ethical AI solutions that address health disparities and support equitable access to healthcare insights and services.
Capacity Building & Training
We empower individuals and institutions with skills in bioinformatics, NLP, and health data science through structured training and open educational resources
Health NLP Systems
We develop and apply natural language processing techniques to analyze unstructured health data such as clinical notes, medical literature, health surveys, and patient feedback, unlocking insights that traditional methods often miss.
Health Data Analytics
We transform complex health datasets into actionable intelligence for researchers, healthcare providers, policymakers, and organizations through advanced analytics and visualization.
Our impact in action
Using NLP, data science, and health research, we turn complex data into actionable, real-world insights.
Health Data Insight Platform
We built a data analytics framework that supports population health monitoring and evidence-based decision-making.
NLP for Medical Literature
By applying advanced NLP to biomedical literature, we enable faster evidence synthesis and access to critical insights.
Community Health Research
Our data-driven research addresses public health challenges in underserved communities, prioritizing ethical, locally relevant and practical solutions.
Publications & Research
We advance knowledge at the intersection of health, data science, and language technologies through publications, reports, and policy analyses for scientific and public audiences.
AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages
In recent years, multilingual pre-trained language models have gained prominence due to their remarkable performance on numerous downstream Natural Language Processing tasks (NLP).
AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages
Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measuring this progress remains challenging.
Pharmacogenomic Profiling for Optimizing Drug Therapy in Congenital Heart Disease Patients
Pharmacogenomic profiling is being recognized as a paradigm shift in cardiovascular precision medicine to personalize drug treatment for patients diagnosed with congenital heart disease.
CIRAL: A Test Collection for CLIR Evaluations in African Languages
Cross-lingual information retrieval (CLIR) continues to be an actively studied topic in information retrieval (IR), and there have been consistent efforts in curating test collections to support its research.
Computer-aided identification of Neisseria gonorrhoeae's Bacteriophage-Q-beta inhibitors from selected anti-gonorrheal plants
The emergence of multidrug-resistant Neisseria gonorrhoeae has intensified the need for innovative therapeutic strategies.
ARTIFICIAL INTELLIGENCE GOVERNANCE: LEGAL AND PUBLIC POLICY IMPLICATIONS FOR DATA PRIVACY AND ALGORITHMIC ACCOUNTABILITY
Artificial Intelligence (AI) is an explanatory force in modern government and presents fundamental legal and public policy issues concerning data protection and algorithmic accountability.
Artificial Intelligence in Transfusion Medicine: Current Applications, Opportunities, and Challenges
Artificial intelligence (AI) is increasingly shaping modern healthcare by enabling data-driven decision-making, improving diagnostic accuracy, and optimizing resource use. In transfusion medicine, AI offers substantial opportunities to enhance donor management
Countermeasures for Adversarial AI Attacks in Cybersecurity: Open Challenges and Future Research Directions
Artificial intelligence (AI), the science of enabling machines to mimic human behavior and intelligence, has found application in every aspect of our lives from healthcare to manufacturing to education to communication networks, among others.
Outreach Programs
Our outreach programs build capacity and empower communities, addressing gaps in data literacy, research use, and evidence-based decision-making.
December 10th, 2025
Ethical and Responsible Artificial Intelligence
The session was designed to help community members and students better understand health information in today's digital world and make safer, more informed choices.
September 16th, 2025
Introduction to Machine Learning & Language Technologies
The session focused on helping participants especially students and community members—build simple, practical skills for understanding information they encounter every day, both online and offline.
June 23rd, 2025
Using Machine Learning Challenges to Improve Disease Treatment
The session introduced participants to how data, research, and language technologies are shaping modern healthcare and improving decision-making at individual, community, and policy levels.
