Announcing the Deep Learning Indaba Award Winners

by siobhan | Aug 23, 2023 | Annual Indaba, Awards, Blog

Kambule Doctoral Award

The Kambule Doctoral Award, held in honour of one of South Africa’s greatest mathematician and teacher, Dr Thamsanqu W. Kambule, recognises  excellence in research and writing by doctoral candidates at African universities, in any area of computational and statistical sciences, and whose work demonstrates excellence through technical rigour, significance of contribution, and a strong role in strengthening African machine learning.  Its recipients are those that uphold Thamsanqa Kambule’s legacy as a defender of learning, a seeker of knowledge, and activist for equality.

The 2023 Kambule Doctoral Award has been given to Dr Arnu Pretorius, from Stellenbosch University, South Africa. 

Dr Pretorius received the Kambule Doctoral Award for his thesis titled ‘On noise regularised neural networks: initialisation, learning and inference’. When a neural learns from data, it can sometimes focus on irrelevant details that do not capture general aspects important for solving a particular task. This is referred to as “overfitting”. A powerful approach to address overfitting is to introduce noise into the training process. In this way, the network is forced to learn only from the more general signal that remains salient in the presence of noise, if it is to perform well. Arnu’s thesis focused on the mathematical underpinnings of how neural networks behave using this approach at the start (initialisation), middle (learning) and end of training (inference). The thesis provides a new theoretical understanding of the learning dynamics of training in this setting and uses the developed theory to derive novel ways of initialising neural networks trained with noise that improves performance during inference.

Dr Arnu Pretorius is a senior research scientist at InstaDeep, with a PhD in Computer Science from Stellenbosch University. Based in Cape Town, South Africa, Arnu is actively involved in cutting-edge research and development efforts related to multi-agent reinforcement learning, combinatorial optimisation, AI-driven drug discovery and AI for social impact and collaborates closely with applied teams to tackle real-world challenges at scale.  

Dr Arnu Pretorius with his team at InstaDeep, Cape Town, South Africa.

Runner Up Kambule Doctoral Award

This years’  Runner Up for the Kambule Doctoral Award went to Dr Oumaima Hourrane from Hassan II University of Casablanca, Morocco, for her thesis titled “Semantic Textual Similarity based on Deep Learning: Towards the Automatic Paraphrastic Detection of Monolingual and Cross-Lingual Plagiarism”. Dr Hourrane’s PhD thesis advances research on plagiarism detection across various aspects. The thesis introduced a range of methods to detect several plagiarism types, generating high-quality outcomes with focus on paraphrastic, translation, and idea-based plagiarism, and not literal plagiarism forms like copy-pasting. The focus is directed towards analyzing documents at the level of content, including citations and sentences. Her thesis significantly enhanced multiple plagiarism detection types such as extrinsic, intrinsic, and cross-lingual.

Dr. Oumaima Hourrane, an NLP researcher and lecturer, holds a PhD in Computer Science from Hassan II University of Casablanca and a Master's degree in Computer Science from Cadi Ayyad University. Her research expertise lies in deep learning, focusing on advanced model design and implementation for various NLP tasks. Areas of specialisation include Multilingual Modelling, Semantic Textual Similarity, Representation Learning, GNNs for text, and Low-Resourced NLP. Alongside her academic pursuits, she actively engages in event organisation and volunteering, showcasing her commitment to knowledge advancement and community involvement.

Alele-Williams Masters Award

The Alele-Williams Masters Award, held in honour of Prof. Grace A. Alele-Williams, one of Nigeria’s most influential mathematicians and educators,  recognises excellence in research and writing by Masters candidates at African universities, in any area of computational and statistical sciences. This Award celebrates  those whose work demonstrates excellence through technical rigour, significance of contribution, and a strong role in strengthening African machine learning. Its recipients are those that uphold Grace Alele-Williams’ legacy as a defender of learning, a seeker of knowledge, and activist for equality.

Boago Okgetheng from the University of Botswana, Botswana, is this years’ Alele-Williams Masters Award recipient.

Boago received  the Alele-Williams Masters Award for his MSc thesis titled  “Tagging: Setswana Complex Qualificatives & Adverbs”, which advances Natural Language Processing (NLP) for Setswana. Setswana, a Bantu language spoken in several African countries presents a unique disjunctive writing style challenges of tagging complex parts of speech, particularly qualificatives, and adverbs formed by multiple words. Boago’s thesis addresses these challenges of tagging complex qualificatives and adverbs for Setswana.

Boago Okgetheng, born in Lotlhakane West, Botswana, embarked on an academic journey ignited by a profound fascination with language and technology. Following his undergraduate studies at the University of Botswana, he volunteered as a research assistant from 2016 to 2022 at the same university where he got introduced to the realm of NLP and registered to pursue an MSc in Computer Science in 2018 and graduated in 2020. Boago is now considering registering for a Ph.D. with a topic on NLP and machine learning, ultimately pushing the boundaries of linguistic technology.

Boago Okgetheng with his colleagues at the University of Botswana, Botswana.

Runner Up Alele-Williams Award

The Runner Up for the 2023 Alele-Williams  Award is  Masechaba Sydil Kupa from Rhodes University, South Africa, for her thesis titled “Semantic segmentation of Astronomical Radio Images: A Computer Vision Approach''. New types of radio telescopes, such as MeerKAT and ASKAP are generating data at a petabyte scale. Handling this massive volume of data using conventional methods has become a challenging task. In Sydil's thesis, a novel approach was employed, leveraging deep learning techniques to detect and segment astronomical objects. This holds particular significance for the MeerKAT telescope and our  pursuit toward understanding the origins of our Universe.

Sydil Kupa hails from the northern region of South Africa, specifically a small locality named Lebowakgomo. Sydil holds a BSc in Actuarial Sciences from the University of Pretoria, South Africa, and a BSc Honours in Statistics from the University of the Western Cape, South Africa. In 2019, she embarked on her journey with the South African Radio Astronomy Observatory (SARAO) as a Graduate-in-Training. During this time, she worked as a Junior Software Engineer while simultaneously pursuing an MSc in Astrophysics at Rhodes University, South Africa. The latter endeavour was made possible through funding from SARAO. She successfully graduated with her MSc in March 2023. Presently, Sydil serves as a Software Engineer at SARAO, contributing to the development of software for the MeerKAT telescope.

Sydil Kupa with colleagues at the South African Radio Astronomy Observatory, Cape Town, South Africa.

Maathai Impact Award

The Maathai Impact Award is held in honour of Prof. Wangari Muta Maathai, Africa’s first female Nobel Laureate, globally for her contribution to democracy, peace, and sustainable development in Kenya as well as across the great African region. This Award recognises work by African innovators that shows impactful application of machine learning and artificial intelligence to positively impact Africa and her communities. This award reinforces the legacy of Wangari Maathai in acknowledging contributions – both intellectual as well as activism – at the intersection of technology and issues such as ecology, development, gender, and African cultures.  

This years’ Maathai Impact Award co-recipients are Zindi and VoteBot.  

Zindi hosts the largest community of African data scientists, working to solve the world’s most pressing challenges using machine learning and AI. Zindi  connects data scientists with organisations, and provide a place to learn, connect, and find a job. Zindi aims to transform the African continent and showcase African data science talent to the world.

Zindi was founded in 2018 with the goal of making AI more accessible to all. Over the last 5 years, Zindi has become a home for more than 65 000 data enthusiasts, students, engineers, analysts, and researchers who are looking to learn, connect and grow their skills in data science, AI and machine learning. As a data science competition platform, Zindi has given out more than $500 000 in prizes to users across 52 African countries and 185 countries worldwide. Zindi's talented and passionate community has built cutting-edge machine learning models for companies and organisations like Google Deepmind, Fossil, Absa, Rand Merchant Bank, Uber, Lacuna Fund, CGIAR, and many many more. Zindi aims  to help every one of their community members find their dream job in data and AI, by connecting their community with the global demand for talent.

Picture of one of Zindi ambassadors and a group of Zindians at a local event in Tanzania.

VoteBot, co-recipient of the  2023 Maathai Impact Award, is an initiative by Justice Code Foundation, a CivicTech organization based in Zimbabwe. Justice Code Foundation's mission is to leverage the power of technology for civic good. VoteBot is one of its initiatives. VoteBot is accessible on WhatsApp. WhatsApp accounts for more that 44% of internet usage in Zimbabwe, making VoteBot easily  accessible  in rural areas. A user wishing to use VoteBot just sends a "Hi" to a given number and starts interacting with the platform. VoteBot then provides  options to access a range of information such as voter registration centres across the country, a free ride (for young people) to go and register to vote, a link to view their voter registration status, and what the Constitution of Zimbabwe says about elections. Users can also use the platform to report any electoral malpractices in their local community and as well upload any evidence of electoral malpractices. 

VoteBot began in January 2022 ahead of the 2023 elections in Zimbabwe to enhance voter information and citizen observation of elections using Artificial Intelligence, targeting young people and women. VoteBot has worked with the African Union CivicTech Fund which saw user growth to +15 000 in 9 months. VoteBot has also partnered with Accountability Lab Zimbabwe to enhance electoral accountability in the 2023 elections.

Team members of Justice Code Foundation implementing the VoteBot project in Marange, a rural area in  Zimbabwe. 

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.