About Daniel Sogbey
Software engineer building toward machine learning engineering.
I am a software engineer with a background in physics, mathematics. I currently build mobile product systems used in real-world settings, and I am moving deeply into artificial intelligence and machine learning.
My goal is to become a strong machine learning engineer. I want to understand machine learning from the ground up, from mathematics and algorithms to the practical work of training, evaluating and deploying models.
My previous research in AI-guided learning systems, electric circuit reasoning and IoT-based energy monitoring remains part of my background. It shows the kind of work I care about: systems that are practical, measurable and useful to people.
Current Focus
AI and Machine Learning Direction
- Machine learning models. Building models from clear foundations, not only using high-level tools.
- Model evaluation. Testing model behavior, studying errors and understanding where systems fail.
- ML infrastructure. Learning the practical systems that support data, experiments, training and deployment.
- Applied AI systems. Turning models and research ideas into usable systems for real problems.
Background
Research and Product Experience
- Built mobile product systems as a Mobile Product Engineer.
- Designed and evaluated AI-guided learning systems with real students.
- Worked on applied machine learning projects including malaria parasite image classification and fake-news classification.
- Studied IoT-based energy monitoring and adaptive load control.