teaching

I have had diverse teaching experiences that span foundational, advanced, and interdisciplinary topics, particularly in natural language processing (NLP) and machine learning (ML). During my PhD, I taught the graduate-level course Introduction to Natural Language Processing (7.5 ECTS) twice at the University of Copenhagen. The second time, I was the head teaching assistant, where I took on greater responsibilities, including managing other teaching assistants. I was involved in adapting the curriculum and teaching materials to reflect the latest advancements in NLP, such as shifting the focus from constituent and dependency parsing to including the topics of multilinguality, interpretability, and bias detection. As a course lecturer, I co-designed and delivered the graduate course Fair and Transparent Machine Learning Methods (7.5 ECTS), which explored the topics of fairness and interpretability in ML. I was involved in developing the curriculum, creating learning materials, designing assignments, and giving lectures. In particular, I took responsibility for the sessions on statistical notions of fairness and bias, and model interpretability.

One of my most rewarding teaching experiences was teaching the class Digital Humanities: Studies in Computational History at the Advanced School for Computational History at the Federico Santa María Technical University (UTFSM), where I designed and taught a highly interdisciplinary course for historians new to digital humanities. Teaching this audience required a balance between introducing technical concepts and practical applications tailored to their historical research. I introduced computational methods and tools through hands-on examples, followed by a workshop where students brainstormed how these tools could address their research questions, resulting in lively discussions on how computational techniques could support historical studies. Many students successfully integrated techniques such as web-scraping into their projects, and the course received overwhelmingly positive feedback, with plans for future iterations.

As such, I have experience with teaching students from different backgrounds. At the University of Copenhagen, those included students enrolled in BSc Computer Science, MSc Computer Science, PhD Computer Science, MSc Social Sciences, and MSc Social Data Science. At UTFSM, I taught BSc and MSc History students. The biggest classroom size I have taught is 150 students.