About
A Lifelong Student, Researcher, Data Scientist.

Introduction
Hello there, my name is Emmanuella Budu. I am a doctoral student at the Centre for Applied Intelligent Systems Research (CAISR) at Halmstad University in Sweden, specialising in generating synthetic Electronic Health Records (EHRs) using generative models. My research interests lie in applying machine learning to drive advancements in disease diagnosis, improve treatment outcomes, and optimize service delivery in healthcare settings. I am most interested in developing AI-based solutions that can be implemented in real-world clinical environments. I have hands-on experience in building machine learning models, data analysis, software engineering, and network technologies.
I consider myself a lifelong learner. I sometimes share my work on my Github and Medium accounts. I am also a Computer science-focused writer at Baeldung, where I write articles and tutorials on various topics in Computer Science.
I also did some volunteer works as a Research Analyst with Abeyie Innovation Studios.
Words I live by: Do unto others as you would have them do unto you!.
Last Updated: 30/04/2025
Skills
Soft skills and technical skills
TOOLS
PowerBI, Tableau, Tensorflow, Pytorch
Data Science
Machine Learning, Data analysis, Data pre-processing
Programming Languages
Python, Java, SQL, HTML and a little bit of R
Research
Data Collection, Problem Identification, Evaluation
Other
Web Development, Software Engineering
Quote
“Data is the new oil” - Clive Humby
Publications
Scientific Papers published in Conference Proceedings and Journals.
Evaluation of synthetic electronic health records: A systematic review and experimental assessment
E Budu, A Soliman, K Etminani, T Rögnvaldsson
Neurocomputing
Evaluating Temporal Fidelity in Synthetic Time-series Electronic Health Records
E Budu, A Soliman, T Rögnvaldsson, F Etminani
2024 IEEE Conference on Artificial Intelligence (CAI)
- See my Google Scholar page for more