Elizaveta Kopacheva

I hold a PhD in Political Science with a specialization in computational methods from Linnaeus University (Sweden). My academic background reflects a strong interdisciplinary orientation, combining social sciences, informatics, and language studies. I have master’s degrees in Informatics and International Relations from St. Petersburg State University (Russia) and in Political Science from Södertörn University (Sweden). In addition, I completed professional training in English linguistics at Peter the Great St. Petersburg Polytechnic University, earning the qualification Translator in the Field of Professional Communication. My early education at the Physics and Mathematics Lyceum No. 1580 at the Bauman Moscow State Technical University provided a foundation in mathematics, physics, and economics, which continues to inform my analytical and computational approach to research.

Teaching

My teaching approach is grounded in inclusivity, active learning, and research-informed practice. I particularly value hands-on learning through labs and project-based work, where students can apply theoretical knowledge to real-world problems and develop confidence in their own problem-solving abilities.

I am currently involved in the following courses:

• Introduction to programming (1DV501),
• Current Topics within Computer Science (2DV505),
• Selected topics in computer science (4DV504).

In these cources, I emphasize continuous feedback, conceptual understanding, and reflection as key elements of learning. My teaching integrates insights from my own research in natural language processing, machine learning, and data analysis, exposing students to current challenges and applications in areas such as communication, healthcare, and social science. My pedagogical foundation builds on formal pedagogical training (Higher Education Teacher Training) comprising three completed courses: Didactical development (4PE33U), Juridical, norm critical and ethical aspects of teaching (2PE30U), and Teaching and Learning Processes (4PE32U). My goal is to foster both competence and curiosity in students, preparing them for independent and critical engagement with data-driven technologies.

Research

I am a postdoctoral researcher working at the intersection of computational methods and interdisciplinary research across the social sciences, political science, communication, and health domains. My expertise lies in natural language processing (NLP), large language models (LLMs), and quantitative data analysis. I develop research frameworks that translate complex theoretical questions into empirically grounded, data-driven solutions. My technical proficiency includes supervised and unsupervised machine learning, network analysis, and text mining, including applications in low-resource language contexts such as Swedish.

I am currently involved in projects such as the Horizon Europe project TWIN4DEM, which develops digital twins of European political systems to investigatedemocratic backsliding, and NLMED, where NLP and LLMs are applied to extract drug-related problems from clinical texts. I also work on projects analyzing patient reviews to improve healthcare services and on studies exploring communication processes in digital media. Across these initiatives, I focus on integrating computational techniques, methodological rigor, and interdisciplinary perspectives to produce actionable, data-informed insights.