Recognition

Honors & awards

Competitive recognition across research, competitions, and professional achievement. Each represents rigorous peer review or public validation.

COMPETITIVE SCHOLARSHIP

Google DeepMind Scholarship

AIMS / Stellenbosch University · 2025–2026

Full scholarship covering tuition, accommodation and living costs. One of Africa's most competitive awards for AI research talent — fewer than 15 awarded annually across the entire continent to exceptional candidates.

This is one of the world's most selective AI research scholarships, awarded only to graduates who demonstrate both exceptional research promise and commitment to trustworthy AI.

WORLDWIDE COMPETITION

5th place, Hausa track — SemEval-2026 Task 9

Polarization manifestation identification (low-resource NLP) · 2026

Ranked 5th globally on the Hausa track (out of 50+ teams), 14th on English. Research published in Proceedings of SemEval-2026 (ACL), pp. 1632–1640, San Diego, USA.

ACL (Association for Computational Linguistics) is the top peer-reviewed venue for natural language processing. SemEval is the premier shared task competition for evaluating semantic and lexical systems on benchmark datasets.

REGIONAL HACKATHON

Finalist, IndabaX Cameroon Hackathon

Deep Learning Indaba Network · 2025

Data visualization innovation track. Selected from 80+ teams across Cameroon. Organized by the Deep Learning Indaba, Africa's largest AI research community and conference.

Deep Learning Indaba is the premier AI conference in Africa, bringing together researchers and practitioners from across the continent. IndabaX events provide a forum for demonstrating applied AI skills under competitive conditions.

INSTITUTIONAL RECOGNITION

2nd Prize, Data Visualization Competition

ISSEA-CEMAC · 2024

Best data storytelling on employment statistics and economic trends in Africa. Recognized for clarity of insight and decision-oriented narrative design.

ISSEA (Sub-Regional Institute of Statistics and Applied Economics) is Africa's flagship institution for training statisticians and economists in data science at scale.