Deep Learning Indaba

Call for Nominations

Awarding African Excellence in Research and Innovation in Machine Learning and Artificial Intelligence

Deadline 30th April 2018
Deep Learning Indaba, Stellenbosch, September 2018
 
The Deep Learning Indaba is a week-long research and teaching conference which aims to strengthen African participation in machine learning and artificial intelligence, as well as promote diversity in these fields. The Indaba will be held in Stellenbosch, South Africa in September 2018, and will host 550-600 participants from across more than 25 African countries. At the Indaba, participants will delve into the theory and practical aspects of current-day machine learning methods, as well as have the opportunity to engage with industry and policymakers in debating the global impact of AI. 

As part of our broader mission to transform Africa into a driver of machine learning research, as well as creator and innovator, we have established two awards to recognise excellence in African research and innovation:
- The Thamsanqa Kambule Doctoral Dissertation Award for excellence in research and writing by doctoral candidates at African universities, in any area of computational and statistical sciences
- The Wangari Maathai Impact Award to encourage and recognise work by African innovators that show impactful application of machine learning and artificial intelligence.
 
Winners of each award will be invited to the Deep Learning Indaba in September to accept the award and will be given an opportunity to share their work via a short presentation. Each winner will also receive a cash prize of at least ZAR10 000. 
 
We therefore extend this invitation to eligible candidates and encourage them to apply for the Kambule and Maathai Awards by the 30th April 2018. Successful applicants will be notified in July 2018. 
 
Eligibility criteria for each award as well as links to submit the application form and supporting documentation can be found here.
 
We look forward to receiving your applications.
Warm wishes
Deep Learning Indaba Committee