A motivated MSc graduate in Computer Science with a strong focus on applied machine learning and research-driven solutions. I have hands-on experience designing, training, and evaluating supervised and deep learning models, and I enjoy building end-to-end ML pipelines that translate research into practical impact. My work combines solid technical skills with a passion for ethical, scalable AI and clear communication, developed through teaching roles and collaborations with diverse teams.
I thrive in collaborative environments where data quality, uncertainty, and fairness matter. My research explores uncertainty in missing data imputation, and I have presented and published work on data quality, missingness patterns. I am eager to apply ML research to real-world problems and to continue growing as a data scientist, developer, and educator.
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