Press Release DLI 2025

by rimallouche | Jul 25, 2025 | Uncategorized

Deep Learning Indaba 2025: Africa's biggest AI Community Gathers 1000 participants in Kigali, Rwanda to Shape the Future

KIGALI, RWANDA –July 14th, 2025– The Deep Learning Indaba (DLI), Africa's premier machine learning and artificial intelligence (AI) event, proudly announces its 7th edition, set to take place in Kigali, Rwanda, under the powerful theme “Urunana – Hand in Hand for AI in Africa”. This edition will build on the success of the previous editions in South Africa, Kenya, Tunisia, Ghana, and Sénégal.

The University of Rwanda's Kigali Campus will host over 1,000 participants, including researchers, students, industry professionals, startups, and policymakers from Africa and beyond from August 17th to 22nd. This event aims to create a collaborative and inspiring environment for the continent's dynamic AI community.

The Deep Learning Indaba is more than just an annual event; it's a grassroots movement dedicated to empowering Africans to become active contributors and leaders in the advancement of AI, rather than just consumers. 

The edition remains committed to inclusivity and diversity, actively ensuring representation from across the African continent and beyond through travel and accommodation sponsorships, mentorship programs, and community engagement initiatives.

"By prioritising education, collaboration, and inclusivity, the Deep Learning Indaba has become a beacon of hope for Africa’s technological renaissance," stated Bruno Ssekiwere, Tejumade Afonja, and Pierrette Mahoro Mastel, the 2025 Indaba General Chairs. "Hosting the Deep Learning Indaba 2025 in Kigali perfectly aligns with Rwanda’s vision to become Africa’s hub for inclusive, responsible, and homegrown AI innovation. As our community grows and evolves, we will continue to work together, to unlock new opportunities, inspire innovation, and solidify Africa’s place in the global AI landscape".

Professor Kayihura Muganga Didas, Vice Chancellor, University of Rwanda expressed his enthusiasm: "Hosting the 2025 Deep Learning Indaba is both an honor and a testament to the University of Rwanda's commitment to championing research, innovation, and collaboration across the continent. We are proud to welcome Africa's AI community to our campus, and we look forward to working alongside the Deep Learning Indaba to inspire the next generation of scientists, technologists, and changemakers who will shape Africa's digital future".

Highlights of the 2025 Deep Learning Indaba will include:

  • Distinguished Keynote Speakers: The event will feature leading voices in AI, including Verena Rieser (Senior Staff Research Scientist at Google DeepMind), Max Welling (Research Chair in Machine Learning at the University of Amsterdam and Distinguished Scientist at MSR), Dina Machuve (Co-Founder and CTO of DevData Analytics), and Sanmi Koyejo (Assistant Professor at Stanford University and co-founder of Virtue AI).
    • Verena Rieser shared her anticipation: "The promise of AI's transformative power demands a collective vision. For AI to truly serve all of humanity, its alignment must be forged not just by a few, but by the rich tapestry of human experience and wisdom. I'm thrilled to be at the Deep Learning Indaba in Rwanda, where we have the unparalleled opportunity to collaborate and ensure AI's benefits reach everyone, everywhere. I look forward to connecting with the community".
    • Sanmi Koyejo added: "I'm excited to join the Deep Learning Indaba community to discuss how we can transform AI evaluation from ad-hoc benchmarking into a rigorous measurement science. I look forward to exploring with fellow researchers how real-world applications and modern computational techniques can help us build the evaluation frameworks that the field truly needs".
  • A Flagship “AI Policy in Africa” Panel: Featuring experts like Jane Munga (Carnegie Endowment for International Peace), Vukosi Marivate (University of Pretoria), Rayid Ghani (Carnegie Mellon University), and Virginia Dignum (Umea University).
  • Engaging conversations: Panel discussions will revolve around critical areas such as Ethical AI, AI in Healthcare, Climate-Resilient AI Solutions, AI for Business and Finance in Africa, and Centring Data in African AI.
  • Engaging Workshops: In-depth sessions for collaboration and community building across a wide range of topics, including Trustworthy AI, Responsible AI, Robotics, Quantum ML, Data for African AI, Neuroscience, Natural Language Processing, and Compute.
  • A Comprehensive Program: The event will also include tutorials, a two-day African Research Symposium, mentorship sessions, paper presentations and more. You can find the full program here.

Building on the remarkable success of the Indaba 2024 in Dakar, Senegal, this year's edition in Kigali is set to be even more impactful.  The 2024 event brought together over 700 participants, showcasing 150+ posters and 62 papers, and featured 90+ startups. It hosted 40+ speakers and guests, including Samy Bengio from Apple, and was supported by 30+ sponsors such such as Google DeepMind, InstaDeep, JPMorgan Chase & Co, Meta, Microsoft AI for Good Lab, and OpenAI. 

For a deeper understanding of past achievements, the full Deep Learning Indaba 2024 Impact Report is available here.

As a registered charity with over 100 dedicated organisers, DLI has been building a sustainable pan-African community of AI expertise since its inception in 2017. Through its annual event, the distributed IndabaX local chapters in 47 African countries, and its Excellence in Research and Community Awards, DLI aims to strengthen Africa's AI ecosystem, foster learning, collaboration, and innovation, and recognise local leadership.

About the Deep Learning Indaba:

The Deep Learning Indaba is a grassroots movement, a culmination of the collective efforts of people across the continent working towards a common goal: to strengthen and empower the African AI community, ensuring Africans are contributors, shapers, and owners of the coming advances in machine learning. Founded in 2017 by a group of friends and collaborators, it has grown into a registered charity powered by volunteers who organise events, coordinate activities, and foster a community of passionate researchers and practitioners. DLI works in collaboration with other pan-African communities and is strengthened through international partnerships, continually fostering new research collaborations, incubating innovation projects, and opening career opportunities.

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French Version

Press Contact: comms@deeplearningindaba.com

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.