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ICResG

Intelligent Computing Research Group

From Ideas to Impact

A collaborative research community advancing Artificial Intelligence, Machine Learning, Data Science and intelligent computing — carrying promising ideas beyond the dissertation, into publications, software, datasets and real-world innovation.

Illustration of intelligent computing research: a neural core connected to data nodes
28
Members
3
Active Projects
2
Completed Projects
13
Publications
6
Conference Papers
13
Partner Institutions
16
Countries Represented

Overview

At a Glance

The Intelligent Computing Research Group (ICResG) is a collaborative research community that brings together students, graduates, academics, researchers and industry professionals to advance Artificial Intelligence, Machine Learning, Data Science and intelligent computing and to carry promising ideas beyond the dissertation, into publications, software, datasets and real-world innovation.

Open membership irrespective of institution or location. Contribution-based authorship — recognition is earned, never automatic.

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Mission Snapshot

Our Commitment

  • Promoting collaborative and ethical research in Computer Science and intelligent computing.
  • Transforming innovative ideas into high-quality publications, software solutions, datasets and technological innovations.
  • Developing research capacity among students, graduates and early-career researchers through mentorship, peer learning and practical research experience.
  • Encouraging interdisciplinary collaboration among academia, industry, government and other stakeholders.
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Research Output

Featured Publications

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Conference
Proceedings of the DEMO International Conference on Applied Machine Learning · 2026
Conference
Proceedings of the DEMO Symposium on Intelligent Transportation · 2025
Journal
DEMO Journal of Intelligent Health Systems · 2025

Active Research

Current Projects

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Low-Resource NLP for African Languages (DEMO)

Building corpora, baselines and transfer-learning methods for text classification in low-resource African languages.

30% · Lead: Chijiuka Akuma

Privacy-Preserving Federated Health Analytics (DEMO)

A federated learning framework enabling hospitals to train shared diagnostic models without exchanging patient records.

40% · Lead: Amina Bello

Crop Disease Detection from Leaf Imagery (DEMO)

A deep learning pipeline for early detection of crop diseases from smartphone leaf images, targeting smallholder farmers.

55% · Lead: Daniel Mensah

Recently Completed

Watch & Learn

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Turn your ideas into impact.

Open membership irrespective of institution or location. Collaborate on real research, earn authorship through genuine contribution, and help transform promising ideas into publications, software and datasets.

A collaborative research community advancing intelligent computing

Our Partners & Affiliations