🎓 I'm a data science master's student who loves diving into the world of numbers and patterns. Passionate about NLP, system architectures, large-scale computing, and statistics, I enjoy exploring the fascinating intersections between them.
JOBSKAPE: A Framework for Generating Synthetic Job Postings to Enhance Skill Matching
We introduce JobSkape, a framework to generate synthetic data that tackles these limitations, specifically designed to enhance skill-to-taxonomy matching. Within this framework, we create SkillSkape, a comprehensive open-source synthetic dataset of job postings tailored for skill-matching tasks. We introduce several offline metrics that show that our dataset resembles real-world data. Additionally, we present a multi-step pipeline for skill extraction and matching tasks using large language models (LLMs), benchmarking against known supervised methodologies. We outline that the downstream evaluation results on real-world data can beat baselines, underscoring its efficacy and adaptability.
Studying Lobby Influence in the European Parliament
We present a method based on natural language processing (NLP), for studying the influence of interest groups (lobbies) in the law-making process in the European Parliament (EP).
Social Mobile App created in the context of LauzHack against Covid-19, a 72 hours Hackathon in a team of 8. It provides entertainment to people during lockdown by enabling to share challenges and activities ideas