CGIAR marks the International Day of Women and Girls in Science
CGIAR celebrates the voices and achievements of women whose work, leadership, and lived experience will inspire the next generation of scientists.
Visible role models are key to crushing stereotypes and biases, and closing the gender gap in science. For IDWGS 2026, CGIAR celebrates the voices and achievements of women whose work, leadership, and lived experience will inspire the next generation of scientists.
Graduate Fellow Juliet Masiga won the ILRI CapDev Grand Challenge 2025 for her presentation showcasing groundbreaking research on improving vaccine quality control for livestock.
What motivates this early-career scientist? “Translating what we do in the lab into something that the common person, the farmer back home can understand, apply to their daily life and improve the health of their animals. This leads to better economies, more money for the farmer and overall, a better life for everyone.”
For Masiga, scientific work isn’t destined purely for publication in journals and Petri dishes in the laboratory – it needs to be accessible and deliver practical impact in the field.
At IITA, Africa Food Prize Laureate Mercy Diebiru‑Ojo is helping advance a new approach to rapid crop multiplication with Semi‑Autotrophic Hydroponics (SAH), taking SAH from scientific innovation to practical, scalable system for farmers and seed producers across sub‑Saharan Africa.
The method speeds up the generation of clean, healthy planting materials, allowing improved cassava and yam varieties to reach communities more quickly and reliably. “It’s a way of producing planting materials that is very different from the traditional way, which involves a lot of drudgery,” she explains.
SAH is also accessible: “This does not involve serious laborious work,” she notes. “Women and youth can do it very conveniently.”
The newly-launched CGIAR Hub in Abu Dhabi has a number of promising products in the pipeline, including Agri LLM. “Before, farmers had to use ChatGPT to get incorrect or imprecise information,” explains Lina Yassin, Data Product Director, CGIAR Digital Transformation Accelerator. “Soon they will be able to ask questions to Agri LLM, a large language model that speaks agricultural language simplified to the farmer’s language.” They’ll receive a customized response based on CGIAR’s extensive, robust, cutting-edge agricultural research.
Representation matters! It's our duty to mentor the girls and women scientists who want to be the next AI creators and AI innovators.
- Lina Yassin
Asked about the potential for AI to unlock opportunities for women and girls in science, Yassin says, “AI is simply a technology. Those who know how to utilize it will excel; those who are afraid of it will lag behind.”
While acknowledging that today AI is biased and not inclusive, she believes the current moment offers an opportunity for women and girls. “They can be warriors who make AI work to their advantage. Armed with AI, data analysis and decision-making skills, girls and women can absolutely excel in STEM.”
WorldFish scientist Chan Chin Yee is working on a project to integrate an AI chat bot with sophisticated foresight models. The models her team builds project future aquatic food production, consumption, trade, and prices— and usually require specialized software to run complex equations, as well as expert interpretation.
In its first phase, the open-access, user-friendly AI‑enabled tool will support policymakers and local governments developing national fisheries and aquaculture plans. The next phase will incorporate more localized data to generate real-time short‑ and long‑term fish price forecasts. For small-scale fishers, excluded from policy decisions and facing volatile prices, limited market access and increasing climate risk, such real-time supply‑and‑demand information can strengthen their negotiating power and boost income. Chan’s work with AI and foresight economic models directly benefits marginalized groups like small-scale fishers and coastal communities, while providing vital information to guide policy development.
From my experience, the gender gap is not uniform across different science disciplines. I work on foresight economic modeling. Female modelers have low representation on the CGIAR foresight team, roughly around 10 to 15% on average. I feel honored to work with these experts from different Centers, but I hope more female economics modelers join the team to improve the dynamics.
I think it's important to have more gender-balanced science teams horizontally as well as vertically, to capture diverse perspectives. Diversity will not only improve equity, but also research quality.
- Chan Chin Yee