In executing our mission to Strengthen African Machine Learning and Artificial Intelligence, this year, instead of hosting our usual activities (the annual Indaba, IndabaX, or the Maathai and Kambule awards), we are experimenting with several new programs, one of these being the IndabaX-AI4D Innovation Grants, which aim to fund 6-month projects that support AI research communities and the work they do, especially now during the COVID pandemic. They gave overviews of their work at our #IndabaSession live stream on the 1st September – a fun and inspiring session – and you can watch the session here (second half).
After a rigorous review process, 11 projects out of a total of 109 were selected. In this post, we are excited to share the selected projects, as well as summarize the selection process to inform those that will apply in future. This grant programme has only been possible through deep partnership, and has been funded through a collaboration between the International Development Research Centre (IDRC), the Swedish International Development Cooperation Agency (SIDA), the Knowledge 4 All Foundation (K4A), and the International Research Centre on Artificial Intelligence under the auspices of UNESCO. Masakhane – We Build Together!
11 IndabaX-AI4D Projects
Characterizing Health Misinformation on Social Media
- Quick summary: The objective of this project is to study the dynamics of the spread of factual and false information in online social networks in Nigeria during the pandemic.
- Country: Nigeria 🇳🇬
- Team: Ofure Ebhomielen, Ezinne Nwankwo and Daniel Nkemelu
AI for Coral Reef Conservation
- Quick summary: The goal of this project is to develop a computer-vision based non-intrusive automatic data collection mechanism to collect images and give insights about coral reefs in the Vamizi Island and allow biologists to analyze data in real-time and infer on animals’ life story, behaviour, population, and survivorship in Mozambican waters.
- Country: Moçambique 🇲🇿
- Team: Erwan Sola and Luís Pina
Development Of Machine Learning Dataset For Poultry Diseases Diagnostics
- Quick summary: The expected outcome of this work is to establish an annotated dataset for poultry diseases diagnostics for small to medium scale poultry farmers.
- Country: Tanzania 🇹🇿
- Team: Hope Emmanuel Mbelwa, Ezinne Nwankwo, Dr. Dina Machuve, Dr. Neema Mduma and Dr. Evarest Maguo
Visual Question Answering in the Medical Domain
- Quick summary: This system takes as input a medical image and a clinical relevant question and outputs the answer based on the visual content.
- Country: Cameroon 🇨🇲
- Team: Volviane Saphir MFOGO, Dr. Georgia Gkioxari, Dr. Xinlei Chen and Jeremiah Fadugba,
Locally run Web-based App for Interpretable Breast Cancer Diagnosis from Histology Images
- Quick summary: Wee will be building a Locally run web-based app for interpretable breast cancer diagnosis.
- Country: Ghana 🇬🇭
- Team: Jeremiah Fadugba and Moshood Olawale
AI System for MNC (Maternal, Neonatal and Child Health)
- Quick summary: We will be building an AI system for predictors of early detection of maternal, neonatal and child health risks and their timely management.
- Country: Tanzania 🇹🇿
- Team: Gladness G. Mwanga, Timothy Y. Wikedzi and Scott Businge
Improving Online Learning Experience using Accent Transfer
- Quick summary: This work will focus on making online educational content accessible through the reformulation of content in local accents.
- Country: Nigeria 🇳🇬
- Team: Tejumade Afonja, Munachiso Nwadike, Olumide Okubadejo, Lawrence Francis, Clinton Mbataku, Femi Azeez and Wale Akinfaderin.
An African Short Story Language Corpus
- Quick summary: is intended to develop openly licensed free to use African language corpora.
- Country: Kenya 🇰🇪
- Team: Prof. Audrey Mbogho, Dr. Lilian Wanzare, Dr. Benson Muite, Prof. Constantine Yuka and Mr. Juan Steyn,
Keyword Spotting with African Languages
- Quick summary: The motivation of this work is to extend a speech commands dataset to include African languages, particularly focusing on 6 Senegalese languages: Wolof, Poular, Sérère, Mandingue, Diola, Soninké.
- Country: Senegal 🇸🇳
- Team: Jean Michel Ahmath Sarr, Daouda Tandiang Djiba, Thierno Diop, Derguene Mbaye, Elias waly Ba, Ousseynou Mbaye and Dr Mamour Dramé.
ChexNet Model Compression for Pneumonia Detection Using Low Powered Edge Devices
- Quick summary: The goal of this work is to build a model compression algorithm for ChexNet. The ChexNet network is chosen as the base model because it is the current state of the art technique in detecting Pneumonia on chest x-ray and as such, a reasonable choice.
- Country: Rwanda 🇷🇼
- Team: Rukayat Sadiq, Brume Love, Jeremiah Fadugba, Olalekan Olapeju, Oluwafemi Azeez, Pelumi Oladokun and Tella Hambal.
Computationally Accelerating Protein-Ligand Matching for Neglected Tropical Diseases
- Quick summary: We will be working on a solution for the Indaba Grand Challenge: Curing Leishmaniasis.
- Country: Ivory Coast 🇨🇮 and United States 🇺🇸
- Team: Kane Mohamed Hassan, Nkwate Ebenezer and Loic Kwate Dassi
Call for Proposals and Selection
The call targeted individuals, grassroots organizations, initiatives, academic, and civil society institutions to apply for funding for mini-projects; new or existing projects at various stages, from early-stage projects that create and analyse new data sets around a research hypothesis, to later stage projects that require a “final push”. With £60,000 set aside for this exercise, we were looking to identify and fund several projects involving work conducted in Africa that has a strong machine learning, artificial intelligence or data science component, in any discipline of science and that supports progress towards the Sustainable Development Goals (SDGs).
The call was open from 12th June to 13th July and a total of 109 submissions were received. Every submission received at least two reviews, which focused on both the technical merit and the social implications of the research. It was a very challenging process to evaluate the submissions, shortlist and finally allocate funding. While there were 30 projects on our short-list, each equally deserving of funding, we selected 11.
Beyond making the cut-off in terms of points, we considered the diversity of team compositions, the amount of funding requested by each proposal and the countries of project implementation.
The recipients of these grants will soon receive the first tranch of financial support, and then be paired with mentors to support them over the next few months. They will be asked to checkin with their mentors half way, and early next year complete their proposed outcomes. We’ll host another #IndabaSessions Live Stream event so you can hear all about their work; watch their intro session here (send half).
Congratulations to all the grant recipients! We look to them as role models of the research capacity across our African continent and look forward to seeing what their efforts will produce.