Deep Learning Indaba 2023
What are the Kambule and Alele-Williams Awards?
The Thamsanqa Kambule and Grace Alele-Williams Awards recognise and encourage excellence in research and writing by doctoral and master’s candidates, respectively, at African universities, in any area of computational and statistical sciences.
The Kambule Doctoral Award celebrates African research excellence: its recipients uphold Thamsanqa Kambule’s legacy as a defender of learning, a seeker of knowledge, and an activist for equality.
The Alele-William Masters Award celebrates African research excellence: its recipients uphold Alele-Williams’ legacy as a mathematician, a tireless champion of women in science, and an educationalist who influenced modern mathematics curricula across Africa.
The awards will be presented at the annual Deep Learning Indaba, Accra, Ghana in September 2023. We welcomed nominations from both students themselves, and their supervisors and mentors. Both The Kambule Doctoral and the Alele-William Masters winners will be awarded a cash prize and will travel to speak at the Deep Learning Indaba.
How were candidates nominated?
Candidates were either self-nominated or nominated by a third party. The application includes the dissertation, examiners’ reports, a summary of the dissertation’s primary contributions to its field of research, and a supporting letter from a person in a position to comment on the candidate and the candidate’s work.
How to assess a nomination
The application should be assessed based on:
- The dissertation’s technical depth
- The dissertation’s contributions/significance to its field of research (whether in theory or practice)
- Its quality of presentation – how well is the thesis communicated (clarity, succinctness, notation accuracy and consistency)
- The thesis and candidate’s role in strengthening African machine learning and artificial intelligence
- The strength of the supporting letter
The review form asks for a 1-5 rating for each of the above items, as well as a longer-length answer (150-200 words) commenting more generally on the thesis and the candidate.