Ahmed Aman Ibrahim
Experienced in computer vision, NLP, and deep learning with 4+ years in applied AI and research roles. Published author with a strong academic foundation (MSc, BSc with Distinction) and a track record of delivering ML solutions for healthcare, insurance, and environmental monitoring. Skilled in designing and deploying end-to-end ML pipelines using PyTorch, TensorFlow, Scikit-Learn, and AWS. Passionate about using AI to solve real-world problems.
Experience
Research Assistant in Applied AI
- Built and deployed regression models and graph neural networks (GNNs) using Scikit-Learn, PyTorch Geometric, Flask, and Azure to predict soil organic carbon content.
- Designed and implemented Bayesian Networks and knowledge graphs (Neo4j) to model and analyze causal relationships affecting soil carbon levels. Create visualisations using networkx, matplotlib and plotly.
Machine Learning Researcher (part-time)
- Researched and developed deep learning models for facial beauty prediction, creating novel loss functions and achieving state-of-the-art results presented at IEEE SKIMA conference in 2023.
- Built and optimized person re-identification (ReID) and Single Shot Detector (SSD) models for image-to-image search in large forensic datasets.
- Trained and deployed gait recognition, face verification, and face pose estimation models for forensic applications in collaboration with Dubai Police.
- Train and deploy transformer embedding models for low resource languages (Sinhala and Dhivehi) to be used in RAG applications.
Artificial Intelligence Consultant (contract)
- Built a personalised recommendation engine that has 95%+ accuracy using customer purchase histories and demographic data using collaborative filtering. Make visualisations using Power BI.
- Designed and deployed a statistical anomaly detection pipeline to identify potential insurance fraud cases which analyse customer behaviour and relationships.
- Developed a custom chatbot using LlamaIndex, Claude, and OpenAI APIs, integrating internal knowledge bases, agents and internal APIs to automate customer support.
- Developed and deployed an OCR automation framework using AWS Textract, reducing manual claims processing workload by 70%.
Machine Learning Engineer
- Fine-tuned LLaMA 2 and MiniLM models to analyze speech and text data for automated mental health screening, achieving 80% accuracy (state-of-the-art).
- Developed multimodal ML pipelines combining vision (Facial Action Units) and NLP, enhancing depression and anxiety detection models.
Machine Learning Engineer Intern
- Trained and deployed convolutional neural networks (CNNs) for automated vehicle damage detection from motor accident images.
- Designed a sentiment analysis dashboard for LiveChat customer data, enabling data-driven insights into customer experience trends.
Publications
For a complete list of my publications, please see my Google Scholar profile.
Education
MSc Machine Learning in Science (Distinction)
B.S. Computer Science, Artificial Intelligence (Distinction)
Volunteering & Leadership
The Circle by Ugail Foundation
Lead a team of 4 tutors and organise online AI and coding classes for school children.
University of Malaya
Organised Python programming workshops for over a 100 students in University of Malaya.
Women In Tech MV (NGO)
Teach web design, HTML and programming in workshops targeted for early career females.