Jibrin Jaafaru | Loughborough University

[Last updated: 16-04-2024]

About Me

I currently work as the Principal Machine Learning Engineer at Greysoft Technologies in Nigeria, where I lead a small team of ML Engineers at the GreyAI Lab. Our primary focus is on cross-lingual translation, particularly for low-resource languages like Hausa. Additionally, I hold the position of CEO and Co-founder of 5Minutes (Beta version available on Google Play Store) at Greysoft Technologies. 5Minutes is a mentor-mentee platform emphasizing brevity in content (videos, texts) without compromising depth.

My educational background includes an MSc. degree in Artificial Intelligence and Data Analytics from the Institute for Digital Technologies at Loughborough University London (awarded a fully-funded merit-based scholarship),where I was advised by Dr Xiaolan Liu. I also earned a BSc. degree in Computer Science from the University of Jos, Nigeria, with Dr. Nentawe Gurumdimma as my advisor during my undergraduate project. This project focused on the automatic screening of precancerous cervical lesions from pap smear images using transfer learning. My dedication to research led to a research assistantship position in an NIH-funded project (Vaginal Microbiome in Cervical Intra-Epithelial Neoplasia and Cancer, NIH grant, K43 project: K43TW011416-02) with Prof. Musa Jonah as the Principal Investigator. This project aimed at increasing cervical cancer screening uptake and reducing mortality in Nigeria.

I am an active member of ACM Special Interest Group (SIGecom) since 2020, as well as being affiliated with Black in AI and Data Scientists Network formerly known as Data Science Nigeria.

In my free time I take pleasure in both watching and playing football. My unwavering allegiance to Arsenal FC is rooted in my childhood admiration for Thierry Henry, (My boyhood idol!) whom I consider Gunner’s Greatest of all Times.

Two quotes that resonate with me are, “If you do not strive for excellence in your endeavours, you have lost your purpose.” by Dr. Manzo Maigari, and “Sincerity is a better ‘persuasion tactic’ than any trick you can learn,” by Michael.

I appreciate your interest in reading this snippet. Feel free to say hello or ask me anything here before you leave. or book an appointment for futher discussion.

Research Interests

I am a budding researcher and an effective altruist with interests revolving around: AI for social good, Self-supervised learning, Geometric Deep learning and Image/signal analysis, Uncertainty Quantification in Vision-Language Models, Multi-agent Reinforcement Learning, Tech Startups and Innovation.

Publications and Projects

EC'20

Towards increasing cervical cancer screening uptake and reducing mortality rates in Nigeria.

Jibrin Jaafaru *, Nentawe Gurumdimma, Innocent Emmanuel, Nyam Chuwang (*Main author)

The Twenty-First ACM Conference on Economics and Computation (EC'20), 2020.

Conference Poster [Accepted]

21LLP008

Collaborative project with WeAreTheNews startup

As the unit team lead for the collaborative project between Loughborough university London and WeAreTheNews startup, I championed ideas on 1. The integration of blockchain in news to revolutionise transparency, ownership, and monetization. 2. Enhancing news article credibility by ensuring the immutability of news articles. 3. Smart contracts to automate fair revenue distribution 4. Proposed the WATN coin to enable micropayments for precise content consumption. 5. Developed measures to ensure GDPR compliance.

Collaborative Project

21LLP131

Deep Q network for optimal irrigation scheduling in Northern Nigeria

Deep reinforcement learning holds significant promise for optimizing irrigation scheduling in diverse cropping systems. By adapting water amounts based on multiple measurements, the framework aims to uncover an intelligent decision rule, demonstrated effectively through a case study in Nigeria wheat farming, maximizing profits. The versatile model, tested in Kaduna, applies to various cropping systems, addressing realistic optimization challenges.

Reinforcement Learning coursework

21LLP501

Robust identification of fall army worm infestation on maize fields of small African farmholders.

This study focuses on the robust identification of fall army worm infestation in maize fields owned by small African farmholders. The research aims to develop effective methods for accurately and reliably detecting the presence of fall army worm infestations, addressing a significant threat to the agricultural productivity of small-scale farmers in Africa. The findings of this study are crucial for implementing timely and targeted interventions to mitigate the impact of fall army worm infestations on maize crops, thereby contributing to the resilience and sustainability of smallholder farming in the region.

MSc Dissertation

21LLP133

Semi-supervised fabric defect detection based on image reconstruction and density estimation.

Textile industries suffer profit declines due to defective products, emphasizing the need for automated inspection systems. This paper introduces a hybrid semi-supervised method for fabric defect detection using variational autoencoder and Gaussian mixture model. Validated on AITEX and DAGM 2007 databases, the method excels in automated detection, outperforming selected alternatives in overall performance.

Advance Big Data Analytics coursework

MTH308

Mathematical Modelling of Anti-Malaria Drug resistance.

I focused on developing a comprehensive model for anti-malaria drug resistance. This involved a thorough examination of parasite population dynamics, drug treatment impacts, host immune responses, and various epidemiological factors. My findings contributed to the formulation of effective strategies for combating drug-resistant malaria.

Mathematical Modelling coursework

About Me

Research Interests

Recent News

Publications and Projects