The Tensions of Pursuing African Excellence in Innovation

by siobhan | Jul 3, 2026 | Sauti Yetu

Victoria Natsai Chasi is a South African and Zimbabwean Master of Public Administration graduate from Cornell University, with a Bachelor of Laws and Bachelor of Social Sciences both from the University of Cape Town. As a tech founder with a background in the United Nations working on economic affairs, policy research, and partnerships within the United Nations system, her work as the founder of ARCHV bridges technology, international development, and social policy and spans AI infrastructure in low-resource contexts, development partnerships, and inclusive digital innovation. Her main interest is exploring scalable, context-appropriate solutions in developing countries with limited public resources. This includes artificial intelligence infrastructure, policy, and data partnerships for low resourced languages.

As a Zimbabwean raised in South Africa, who now finds herself in* the polarised United States**, amidst growing*** anti-immigrant sentiment in South Africa, the United States or any other place – the reality of navigating constraint and opportunity is (unfortunately) intimately familiar to me. 

I know for a fact, that those of you coming to Nigeria for this year’s Deep Learning Indaba (DLI) face varying degrees of hope and complexity in arriving at the Indaba – largely influenced by your passports and resource availability. 

I also know that all who want to build together, are welcome in this community. 

The Deep Learning Indaba’s efforts in equalising inequalities faced by those coming to the places where the Indaba itself is hosted have my utmost respect, and I trust it will further strive to leave the places it visits better than it found it.

Use your unique understanding

Knowing that no single African experience is the same, we nevertheless share a common understanding of our own values, abilities, lands, peoples and cultures. 

Looking back through the annals of history, I think of the work of Kenyan filmmaker, founder and producer at Filmset Africa – Valerie Keter, who highlights the engineering feats that resulted in early underground water systems dating back centuries on the African continent. Examples of these include the North African fogarra system dating back to 500 BC - 600 AD, found in places such as  modern day Libya  as well the fogarra systems from the the 9th to 12th centuries still used in the Algerian Sahara. Looking to East Africa, the work of Valerie Keter has highlighted how the water harvesting and sanitation system in 15th century Gedi  (which is in modern day Kenya) continues to survive to this day.

This is an ancient reminder of systems that serve people I see echoed in the present through momentous efforts such as the work of Masakhane and Lanfrica. The former, who works on collectively building African language capacity in research, data collection and public-good tools; and the latter, who coalesces our collective efforts by data sharing for the continent.

We know our own necessities and I cannot think of more worthy people than those in the DLI’s community to flex their inventive creativity in meeting needs we ourselves experience and see. 

We say in Shona: “chirema chine mazano”, which means something along the lines of “A person with a disability  always finds a resourceful way to make the best out of their situation.” Whether we call it “grit” or “resource-constrained innovation,” because “necessity is the mother of invention,” we as Africans, have ALL the constraints and conditions necessary to solve any challenge we face counter-intuitively.

I think of the work of businesses such as Cassava Technologies, Dataspires, Datawise Africa and Yamify – to name a few. These ventures have seen the limitation of access to compute as the foundation to open up our creative capacities in deep learning. Recognising the capacity opened up for excellence by providing local-currency compute, and AI infrastructure they are working towards facilitating the expression of our bigger, bolder and better dreams in a reality that improves our collectively lived experiences.

Our constraints present an opportunity to innovate towards the discovery of an even more fundamental problem, and an even more curated solution.

All this to say: there is a way to innovate with the far-reaching future in mind and to do so in a way that genuinely improves quality of life for the people served by our innovations. 

Who is served when Africans choose the path of least resistance

I observe a need in our community – and in my own start-up endeavours – in becoming adept in forming a business-case, and doing this as precisely as possible. 

I reference the words of Boris Cherny, Head of Anthropic’s Claude Code, who initially built Claude Code for internal use, emphasises that when building solutions: you can never get people to do something they do not yet do". When testing whether your market needs your work, it is advisable to understand what people regularly do, and how your solution makes this better. If we cannot impact our community with our innovations, others will step into the gap. Are we content to let that happen (again)?

Our community has rightfully raised many questions about  “our data” and “sovereignty.” We need to be clear what we mean by this, and whether we have the infrastructure and the ethics and accountability structures to not be found wanting. If we say we want to protect our data, but use non-commercial (CC-BY NC) open source models with fixed weights and “add a few layers” then make the licence more open for our community – we shouldn’t be surprised if the Big Tech companies who trained the original models come for our data in response to licensing breaches. 

Maintaining excellence requires trial and error as well as continual pursuit. We will fail, and that is natural. Consider this permission to shoot your best shot. But when we stumble, and when we fail, I trust we will be a community that calls each other to the best of our potential, and not slingers of suspicion, shame or harbingers of doom. There is more, and there is better.  We can want it, and create structures to make it ours.

The challenge I leave with you (and myself) is seeking excellence under constraint and not being satisfied with constraint as a reason to limit our aims or our ethics. Our histories both commend us and invite us.

Together in constraint, complexity innovation, and intent,

Victoria Chasi

Founder,

ARCHV


* Brookings Institution, host, How American Visa Bans and Migration Policies Are Shaping US-Africa Relations, Foresight Africa, March 25, 2026, 26 min, https://www.brookings.edu/articles/how-american-visa-bans-and-migration-policies-are-shaping-us-africa-relations/.

** E.J. Dionne, Jr., “How 2026’s Divisive Immigration Politics Could Lead to a Solution down the Road,” Brookings Institution, April 7, 2026, https://www.brookings.edu/articles/how-2026s-divisive-immigration-politics-could-lead-to-a-solution-down-the-road/.

*** Enos Denhere, “Why Are Anti-Migrant Attacks Increasing in South Africa?,” Aljazeera (Johannesburg, South Africa), May 23, 2026, https://www.aljazeera.com/news/2026/5/23/why-are-anti-migrant-attacks-increasing-in-south-africa.

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.