Under the Jasmine Tree

by siobhan | Jul 9, 2025 | Sauti Yetu

تحت الياسمينة

This month’s newsletter was written by two community members. Amal Nammouchi, originally from Tunisia 🇹🇳, is a co-founder of AfriClimate AI, a Pan-African non-profit using AI to tackle climate challenges across Africa. She is a PhD candidate affiliated with SOLVE and Karlstad University, Sweden, and is a long time organiser for the Deep Learning Indaba, including her role as the Chair of the Applications and Selection Committee for the 2024 Deep Learning Indaba. From Algeria 🇩🇿, Sabrina Amrouche relocated to Switzerland to pursue a PhD in physics and AI CERN. She has moved to industry after her PhD and is now leading the data science department at ZYTLYN. She is a co-founder of AfriClimate AI and leads the AfriNet project.

🇹🇳 Growing up in Tunisia, the northernmost African city, I spent countless hours beneath Jasmine trees, enjoying the cold breeze of “El 9ayla”, the Tunisian term for midday hot hours, and the soft echoes of “Ta7t el Yassmina Under the Jasmine Tree” song filled my soul. I grew up in El Alia, a quiet farming town, where summer days meant joining neighbors to pick tout and hendi fruits, playing under the wide open sky, climbing trees with sticky fingers, and resting under fig branches while the land was filled with life. Those rhythms once felt eternal. But with each passing year, they began to shift. What we once called seasons started losing their meaning: extreme heat waves hitting more often, more harshly reaching 50°C temperature in my little coastal town, carrying a different weight, one of risk, even death for some, rain arriving too late or not at all, fruit ripening too early, the soil too dry.

🇩🇿  It’s been ten years since I left Algeria. Before that, the idea of water consistently coming out of a tap was foreign. The very first time I immersed myself in a bath tub was when I was 27. The notion would be completely outrageous back home. People get regularly shamed for washing their cars… Water means food, peace, or chaos. More than 85% of my country’s agricultural land depends on rain. Rain makes and breaks farmers and millions of livelihoods.  On dry spring days, there would be massive prayers (“Salat el istiskaa” in Arabic) organised to humbly plead for rain. It is the last resort for people when they, helplessly, see their crops die. Most farmers in my country sold their land and moved to the city. My parents came from a family of farmers. When their land completely dried, a decade ago, I remember my mother, shovel in hand, filling up large bags of the old tired soil that once fed her. That soil travelled hundreds kilometres and now sits in a balcony nourishing colourful roses. And so, there was once a Jasmine tree that scented my early childhood memories. I get to see what remains of it on my mother’s balcony every time I visit.

🇹🇳 🇩🇿 Climate change has never been a scientific, abstract concept. For many of us, it arrived slowly, quietly—like a neighbour who overstayed their welcome, reshaping the contours of daily life without asking. It revealed itself in the wells running dry, in the timing of harvests going unpredictable, in the exhaustion on the faces of farmers who can no longer rely on the sky. And yet, despite the heaviness, we have found something else: connection. Through communities such as the Deep Learning Indaba and AfriClimate AI, we’ve learned that while the signs of crisis may differ across our landscapes, our stories echo each other. From Cape Town to Cape Angela, From El Alia to Milliana, we are united by the urgency to protect what we love, to unite in pushing the frontiers of climate research, adapt and mitigate together.

AfriClimate AI was born from this shared vision. A grassroots community of AI and Climate researchers, professionals, policy makers and changemakers, dedicated to harnessing the power of AI for a sustainable and climate-resilient Africa. Our work is deeply rooted in Wangari Maathai’s powerful assertion: “You cannot protect the environment unless you empower people, you inform them, and you help them understand that these resources are their own, that they must protect them.” Guided by this vision, we have set ambitious goals to tackle the pressing challenges at the intersection of climate science and AI across the continent. From capacity building through our workshops and seminars, to knowledge sharing through AfriWiki, to concrete on-the-ground impact with AfriNet—where we deploy community weather stations—and research initiatives such as our weather benchmarking project, we strive to bridge gaps and cultivate resilience.

Whatever your vision, there is a place for you to plant a seed, to empower, to volunteer, and to grow alongside us. We invite you to join in reimagining and rebuilding a future where communities thrive in harmony with their environment.

Cheikh Anta Diop Award

The Cheikh Anta Diop Award recognises, encourages, and celebrates excellence in research, teaching, and community service by early- to mid-career academics and researchers at African universities in any area of artificial intelligence, as well as computational and statistical sciences. Its recipients are those who uphold Cheikh Anta Diop’s legacy as a multidisciplinary scientist and visionary intellectual.

The DLI 2026 Cheikh Anta Diop Award is awarded to:

Winner: Prof Omneya Attallah 

Country: Egypt

Affiliation: Arab Academy for Science, Technology and Maritime Transport (AASTMT)

Essence of the Award: Prof. Omneya Attallah says that this award reminds her that every late night, sacrifice, and challenge she has faced as a working mother and African researcher has been worthwhile. It proves that perseverance truly pays off.

Professor Omneya Attallah is recognised for a career that integrates research excellence, teaching, and community service into a single mission. At AASTMT, she has built a research programme spanning breast cancer detection, paediatric epilepsy diagnosis, wearable biosensing, explainable AI, and CanSense, a breathomics AI system for non-invasive breast cancer screening developed on locally collected Egyptian clinical data in partnership with Egyptian clinicians. As a teacher she designed the curriculum for a new undergraduate Biomedical Engineering programme. She has supervised 13 postgraduate researchers to completion, the majority of them women. Through HERBioLab, WeBios, and her IEEE and editorial activities, she has built laboratories, curricula, training pathways, and partnerships that are shaping the next generation of African biomedical AI researchers

Wangari Maathai Impact Award

The Wangari Maathai Impact Award recognises and celebrates work by African innovators, thinkers, and advocates who demonstrate impactful work, including, but not limited to, technical, societal, environmental, and economic domains, around machine learning and artificial intelligence. This award reinforces the legacy of Wangari Maathai by acknowledging the capacity of individuals to be a positive force for change: by recognising ideas and initiatives that demonstrate that each of us, no matter how small, can make a difference.

The DLI 2026 Wangari Maathai Impact Award is awarded to:

Winner: Dr Hellina Hailu Nigatu

Country: Ethiopia

Affiliation: Artificial Intelligence Accountability Lab (AIAL) at Trinity College Dublin

Essence of the Award: Dr Hellina Hailu Nigatu says that having read Wangari Maathai's autobiography, Unbowed, it is a personal privilege to be recognized with an award in her name. She wants to give gratitude to her mentees on the project who carried the majority of the work. This recognition is as much, if not more, a fruit of their effort and hard work. She hopes this will also inspire more grassroots ventures in the African AI landscape that foster meaningful community engagement and participation.

Dr Hellina Hailu Nigatu is recognised for her work addressing gender bias in machine translation across three Ethiopian languages: Amharic, Afan Oromo, and Tigrinya. Rather than adapting English benchmarks, she built evaluation frameworks and datasets directly within African languages, preserving cultural nuances that translation from English cannot capture. Key to this work is the Yeswa Stories dataset, centered on African women's narratives and lived experiences. Seven Ethiopian female students participated as paid researchers, benefiting from funding, compute access, and substantive mentorship throughout. The project produced open-release benchmark datasets now available to the broader African NLP community. Her mentorship has been described by those she supervised as transformative, not nominal.

The DLI 2026 Wangari Maathai Impact Award runner-up is: 

Runner-up: Abdel-aziz Harane Abounounou 

Country: Chad

Affiliation: Chad AI Network

Essence of the Award: Abdel-aziz Harane says that he is deeply honored by this award. This recognition reflects his constant obsession: solving Chad's real problems through AI and software engineering. It renews his commitment to the Chad AI Network's mission of sustainable, locally driven transformation.

Abdel-aziz Harane Abounounou is recognised for his work building the first natural language processing tools for Chad's indigenous languages, a country with 123 languages yet only two represented in existing digital tools. Rather than waiting for a foreign lab to take interest, he set out to build the entire pipeline himself, working directly with the communities who speak these languages. The Kalam-na project anchors this work, collecting audio and text data across 16 dialects of the Sara language family. Native speakers contribute their own voices through Kalam-na Voice, a platform built to remove technical barriers to participation. The project has gathered over 68,000 transcribed audio clips and 72,000 aligned texts, laying the groundwork for open ASR, TTS, and MT models. He also founded the Chad AI Network, now over 200 members strong, and ran two editions of IndabaX Chad. This work reaches an estimated 4 million speakers of Chadian languages currently shut out of the digital world.

Thamsanqa Kambule Doctoral Award

The Thamsanqa Kambule Doctoral Award recognises, encourages, and celebrates excellence in research and writing by doctoral candidates at African universities in any area of computational and statistical sciences. Its recipients are those who uphold Thamsanqa Kambule’s legacy as a defender of learning, a seeker of knowledge, and an activist for equality.

The DLI 2026 Thamsanqa Kambule Doctoral Award is awarded to:

Winner: Dr Everlyn Chimoto 

Country: Kenya

Affiliation: Lelapa AI & Riara University

Essence of the Award: “Receiving this award is deeply meaningful because it recognises not only the years of work invested in this thesis, but also the support of my supervisor, collaborators, family, and the African NLP community that has continually inspired and challenged me. To me, it also recognises the importance of pursuing research motivated by the needs of underrepresented language communities. I believe this work demonstrates that data-centric approaches can make meaningful progress in low-resource settings while remaining relevant to many other machine learning problems. I am encouraged to continue pursuing research that advances knowledge while creating opportunities for more languages and more people to participate in language technology,” says Dr Everlyn Chimoto.

Dr Everlyn Chimoto is recognised for a doctoral thesis on sentence alignment for the Marama dialect of Luhya, CAT data pruning which achieves 92% of full-data performance at 50% of the data with no additional compute cost, GrammaMT which delivers over 12 BLEU point improvements for endangered languages from as few as 21 grammatical examples, and COMET-QE active learning for efficient data selection. Together these form a framework immediately usable by African NLP practitioners working under real compute and data constraints. Her work is centred on improving model performance to make AI systems more inclusive for African language communities.

The DLI 2026 Thamsanqa Kambule Doctoral Award runner-up is:

Runner-up: Dr Devon Jarvis 

Country: South Africa

Affiliation: University of the Witwatersrand

Essence of the Award: “I started learning ML while volunteering at the Indaba in 2017. To be recognised nine years later is gratifying and reflects the impact this community has had on my career,” says Dr Devon Jarvis.

Dr Devon Jarvis is recognised for his doctoral work developing a theoretical framework for controlled semantic cognition using deep and nonlinear neural networks to explain how the human brain flexibly applies learned semantic concepts to new contexts. Rather than treating machine learning purely as an engineering tool, he built tractable theoretical models that shed light on the principles of human cognition itself. His dissertation extends deep linear network theory to explain systematic generalisation, introduces a novel framework (the Rectified Linear Network) to model ReLU network training dynamics, and shows that these networks can capture all six classical properties of controlled semantic cognition while still falling short of systematic generalisation. He then proposes a meta-learning model, the Meta-GDLN, as a path toward closing that gap. He has since remained on the continent to establish the CAandL Lab, one of Africa's first computational neuroscience labs.

Grace Alele-Williams Masters Award

The Grace Alele-Williams Masters Award recognises and celebrates excellence in research and writing by master's candidates at African universities in any area of computational and statistical sciences. Its recipients are those who uphold Grace Alele-Williams’ legacy as a defender of learning, champion of academic excellence, and activist for access to education.

The DLI 2026 Grace Alele-Williams Masters Award is awarded to:

Winner: Akinbobola Adegboyega

Country: Nigeria

Affiliation: Olabisi Onabanjo University

Essence of the Award: According to Akinbobola Adegboyega, “The Alele-Williams Award is a reminder that hard work, curiosity, and dedication matter, and it inspires me to keep making meaningful contributions for societal benefit.”

Akinbobola Adegboyega is recognised for a Master's thesis that introduces affective fidelity as a new evaluation lens for machine translation in low-resource tonal languages, reframing emotion as a core measure of translation faithfulness rather than a secondary concern. His work targets Yorùbá, a language representing just 0.008% of Common Crawl training data. He produced a culturally validated bilingual emotion dataset of over 200 annotated paragraph pairs verified by native speakers, created a reproducible benchmarking framework evaluating four major language models, and identified six distinct failure modes specific to tonal low-resource language translation. The dataset has been released openly, contributing usable infrastructure to the African NLP community.

The DLI 2026 Grace Alele-Williams Masters Award runner-up is:

Runner-up: Imen Habibi 

Country: Tunisia

Affiliation: LARIA, ENSI, University of Manouba, Tunisia

Essence of the Award: “This recognition is the reward for five years of dedication and perseverance. It honors my supervisors' support and inspires me to continue pursuing research with confidence,” says Imen Habibi.

Imen Habibi is recognised for her master's thesis designing a drone-based inspection system that integrates optimized UAV path planning with AI-powered imaging for industrial applications. She developed spiral and zigzag trajectory strategies for nuclear facility inspection (validated through 2D and 3D simulations) alongside a CNN-based anomaly detection pipeline for PV solar panels achieving 91% accuracy. Her work bridges trajectory optimization and intelligent image analysis into a unified system applied to real industrial use cases, improving inspection reliability, precision, and efficiency.