Masirouna – Our Destiny

by siobhan | Jan 20, 2024 | Sauti Yetu

وما نيل المطالب بالتمني  *** و لكن تؤخذ الدنيا غلابا

وما استعصى على قوم منال  *** إذا الإقدام كان لهم ركابا

The desired goals are not attained through mere wishes 

But rather the world is conquered through endeavour

No achievement is beyond the reach of those

Who take on the road with determination

أحمد شوقي - Ahmed Chawki

Since I joined the Indaba organisation in 2019, I started hearing about the amazing Indaba wave of positive energy that can fuel us for months. The global pandemic meant that I had to wait for three years to experience it for myself, and those accounts were by no means exaggerated.

The moment the Indaba participants start arriving at the venue brings an indescribable joy, and it only keeps growing over the week. Thinking about the reason for this special energy, I find myself often linking this to our amazing diversity and strong unity. We come to the Indaba with wonderfully different cultures, backgrounds, environments, challenges and aspirations, but with a common passion, thirst for knowledge, and generosity of acts and spirit. We come to learn together, share our knowledge with extreme kindness and openness of mind and to grow scientifically and humanly, as individuals and as a group. Our community is a wonderful illustration of how diversity is a strength, when we transcend our differences to focus on what brings us together. Our evolving network and the growing number of success stories that started with an Indaba conversation are testament of this strength.

While organising the Indaba, we are often reminded how hard it is to categorise it. It is more than a conference or a summer school, more than one event per year. The categorization that I like the most is "grassroots movement". It conveys two ideas that are central to what we do. The first is that people, you, are at the core of everything we do. Our annual gathering and our many other activities are organised by you, with you and for you. The second is the idea of constant change. Looking at the history of the Indabas, it seems that no two gatherings have been the same. Each year brings new experiments, visions and goals. Each year, we become more inclusive and kinder to each other, while we take the next step in our learning journey.

This year is a special one for our community. This month has witnessed the very first major International Conference for Machine Learning in our continent (ICLR). Many members of our Indaba family took part in the event, from organising to showcasing their research to participating and engaging with researchers from all over the world. It has been an occasion for the global community to better understand the opportunities and challenges related to machine learning and AI in our continent. This will be followed later in the year by the largest Indaba ever, taking us again to a new region, the West of the continent. It will be another opportunity for us to learn more about each other, strengthen our connections, and grow this wonderful diversity and binding unity. Our voices are more than ever loud and present, but there is still a lot to do. So as you read this newsletter, I would like to invite you to think with us about how we can grow our movement, so that together we can own and take our place in building this transformative technology and with it, shape our future and destiny.

-Amal Rannen-Triki, General Chair and Member of the Executive Board. May 2023.

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.