This month, we're pleased to spotlight two of our Fellows 鈥� Genan Hamad and Donald聽Kemajou Njatang 鈥� as they share the moments that shaped their research journeys, the projects they're most proud of, and a glimpse into life beyond the data.
Meet Genan Hamad
Q: Could you take us back to a pivotal moment that shaped your research journey, and how has CAnD3 helped you reinforce your research purpose?
The COVID-19 pandemic was a pivotal moment that shaped my research journey. During that time, I witnessed the importance of data-driven decision-making in addressing complex social and public health challenges. This experience motivated me to pursue a PhD in Measurement, Evaluation, and Data Science to strengthen my quantitative research and analytical skills.
CAnD3 has played an important role in supporting this journey. Through its training opportunities and activities, I have gained valuable skills that are not typically covered in graduate coursework. For example, the sessions on research reproducibility and the Replication Game helped me better understand the importance of transparency and rigor in scientific research.
In addition, CAnD3 has helped me prepare for careers in government and industry. Training sessions and activities on data visualization, writing op-eds, and preparing briefing notes taught me how to communicate complex research findings in clear and accessible ways for policymakers and non-academic audiences. These experiences have reinforced my commitment to producing research that not only advances knowledge but also informs evidence-based policy and practice.
Q: Share a recent publication, presentation, or project you're proud of. What was the most exciting or challenging aspect of this work?
I am particularly proud of a recent project that was accepted as a poster presentation at the AI4PH Research and Implementation Symposium (July 20 & 21, 2026). The project is titled "AI Literacy as a Determinant of Health Inequalities: An Intersectional Machine Learning Analysis Using XGBoost and SHAP."
This project is especially meaningful to me for two reasons. First, I am working on this study as part of my CAnD3 applied research project. Second, it brings together several of my primary research interests: artificial intelligence, health inequality, intersectionality, and supervised machine learning (ML). The project uses advanced ML analytical techniques to examine how AI literacy varies across different social groups and how these differences may contribute to broader health inequalities.
The most challenging aspect of this interdisciplinary work has been finding collaborators across fields such as sociology, public health, and data science who share an interest in combining these research areas. I hope to build these connections through networking opportunities at conferences and symposiums, including the AI4PH event.
Q: Outside the world of research and data, what hobby or interest do you have that might surprise people?
Outside of research and data science, I enjoy fishing, strawberry picking, and gardening. I particularly enjoy planting seeds and bulbs and growing fruits, vegetables, and herbs that I can later use in my cooking.
One of my long-term dreams is to own a small farm where I can raise chickens and grow organic produce. There is something deeply rewarding about producing your own food and staying connected to nature. These activities provide a welcome balance to academic life and allow me to relax, recharge, and enjoy the outdoors.
Q: If you were to describe your research as a food, what would it be and why?
I would describe my research as my favorite ice cream. Just as ice cream brings me joy and comfort, research is a source of excitement, fulfillment, and continuous learning in my life. I genuinely enjoy the process of conducting research 鈥� exploring new questions, solving complex problems, and discovering insights through data. In fact, I often find working on research more enjoyable than many forms of entertainment because it allows me to engage my curiosity, analytical thinking, and creativity.
What I enjoy most is not only the final outcome, but the learning process itself. Every new skill, method, or discovery brings a sense of accomplishment and motivation to continue exploring. Much like enjoying a favorite dessert, research is something I look forward to and find deeply satisfying.
Meet Donald聽Kemajou Njatang
Q: Could you take us back to a pivotal moment that shaped your research journey, and explain how CAnD3 helped strengthen your research objective?
The events and Lunch & Learn sessions particularly strengthened my objective by showing me how to translate complex data analysis into actionable levers for public policy, which gives true meaning to my work as a researcher.
Q: Share a recent publication, presentation, or project you are proud of. What was the most exciting or challenging aspect of this work?
I am particularly proud of my current research project, which analyzes how the interaction between climate shocks (temperature and precipitation) and local vulnerability impacts conflict events in Africa. Within this framework, the greatest challenge was constructing a standardized 'cell-year' panel from scratch (using a fine spatial grid) by extracting, cleaning, and aggregating massive volumes of monthly raster data 鈥� such as satellite imagery and climate grids 鈥� for precipitation, temperature, localized GDP, and the Human Development Index (HDI).
Q: Outside the world of research and data, what hobby or interest do you have that might surprise people?
When I disconnect from research, you can usually find me on a football (soccer) pitch. It is a sport I play regularly.
Q: If you could put together a dream team of three fictional characters to help you with your research, who would they be and what roles would they play?
If I had to assemble my dream team to accelerate my research, I would recruit these three extraordinary scientific minds: Dr. Stone (Senku Ishigami), Dr. Vegapunk (One Piece), and Bulma (Dragon Ball). Equipped with brains capable of absorbing and storing infinite knowledge, they would design the perfect spatial infrastructure to process my global raster datasets without ever crashing the server.
