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You are here: Home / Event / Open Call: Deep Learning Indaba Workshop (Africa)

Open Call: Deep Learning Indaba Workshop (Africa)

Deadline: 24 February 2025

Entries are now open for the Deep Learning Indaba Workshop to strengthen and celebrate African AI.

In 2025, the DLI will be held in Kigali, Rwanda at the University of Rwanda from 17 to 22 August 2025. The event will include keynotes, tutorials, workshops, panels, and paper presentations. They invite proposals for workshops to be held on 21 and 22 August 2025. Workshops serve as focused forums to discuss emerging research, share novel ideas, and encourage active engagement across the African AI community.

Focus Areas

  • They welcome all areas of machine learning and AI.
  • Topics of particular interest include:
    • Foundation models for African languages
    • Trustworthy AI (robustness, explainability, privacy, fairness)
    • Generative models
    • Learning in low-resource settings (edge ML, tiny ML)
    • NLP and multi-modal learning
    • Computer vision
    • Reinforcement learning
    • Real-world applications (agriculture, healthcare, finance, education, etc.)

Benefits

  • Each accepted workshop receives:
    • 2 free registration tickets for organisers
    • 4 free registration tickets for speakers

Workshop Format

  • Workshops can be structured as either:
    • Full-day (5 hours, excluding breaks) to be held on 21 August
      • Tentatively 9 a.m. to 4 p.m. with a 30 min tea break at 11:30 a.m. and a 1.5 hour lunch break at 1 p.m.
    • Half-day (3.5 hours, excluding breaks) to be held on 22 August
      • Tentatively 9 a.m. to 1 p.m. with a 30 min tea break at 11:30 a.m.
  • Please note that they may request a change from Full-day to Half-day (or vice-versa).
  • Possible session types include, but are not limited to:
    • Invited talks / keynote speakers
    • Contributed paper presentations
    • Tutorials
    • Panel discussions
    • Poster sessions
  • They encourage creative, participatory formats that spark dialogue and collaboration.

Selection Criteria

  • The Workshop Program Committee will review proposals based on:
    • Clarity & completeness of the proposal
    • Relevance to the African AI community
    • Uniqueness / novelty (note: merging may be requested for overlapping topics)
    • Organiser expertise and diversity
    • Potential for impact and active participant engagement
    • Confirmed speakers (with flight and accommodation funding details)

Application Requirements

  • Please structure your proposal as follows:
    • Title & Abstract:
      • A concise summary (one paragraph) of your workshop’s focus and scope.
    • Goals & Objectives:
      • How the workshop will contribute to African AI and broader ML/AI research.
      • Expected outcomes or success metrics.
    • Organising Team:
      • Names, affiliations, and roles (highlight the primary contact).
      • Brief statement on relevant expertise and how the team ensures diversity (e.g., geographic, gender, career stage).
    • Tentative Agenda / Schedule:
      • Indicate full-day or half-day.
      • Outline sessions (talks, panels, breaks) with approximate duration.
    • Speakers:
      • Confirmed vs. tentative speakers.
      • For confirmed speakers, please specify how their flights and accommodation in Kigali will be covered. —Please also include a short email confirmation from confirmed speakers.
    • Rationale for each speaker’s relevance.
      • Remote participation plan, if applicable. Note that remote participation is discouraged where possible due to potential internet issues.
    • Sponsorship & Funding:
      • Whether you intend to sponsor speaker travel/lodging.
      • Potential industry or institutional sponsors.
    • Promotion & Advertising:
      • Methods to attract participants (email lists, social media, flyers, etc.)
    • Diversity & Inclusion:
      • Ensure representation (topic scope, speaker lineup, etc.)
    • Additional Information:
      • Any special requirements or extra details (expected audience size, A/V needs, etc.)

For more information, visit Deep Learning Indaba.

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