We are a collocation of collaborators working on a diverse range of topics in computational linguistics, natural language processing and machine learning.
Credits to Afra for the lab logo and to Tim for the logo idea.
*Alumna is the nominative plural of alumnum, which means student in Latin. This a gender neutral (or, better said, gender neuter) version of the gendered words alumni and alumnae.
ETH Zürich Fall 2025 This course presents topics in natural language processing with an emphasis on modern techniques, primarily focusing on statistical and deep learning approaches. The course provides an overview of the primary areas of research in language processing as well as a detailed exploration of the models and techniques used both in research and in commercial natural language systems.
ETH Zürich Fall 2025 This Bachelor’s seminar investigates the computational foundations of modern machine learning. We examine how model complexity, data availability, and algorithmic design interact to determine what learning systems can and cannot achieve, highlighting classic results from computational learning theory.
ETH Zürich Spring 2025 This course explores the connection between automata and formal logic. More precisely, it covers the algebraic characterization of the regular languages definable in many different logical theories, the complexity theory of boolean circuits, and the connection between the two.
ETH Zürich Spring 2025 This graduate class, partly taught like a seminar, is designed to help you understand the philosophical underpinnings of modern work in natural language processing (NLP), most of which is centered around statistical machine learning applied to natural language data.
ETH Zürich Spring 2025 In the first part of the seminar, we study some of the most popular parsing algorithms, which are a fundamental tool both in natural language processing and in programming languages. Each week, a student will present a paper on parsing, including the papers that first described celebrated parsing algorithms like Earley’s and CKY. We will also put a lot of focus on weighted parsing, which is fundamental in applications to language modeling. In the second part, we’ll examine advanced NLP topics through analysis of pivotal (and often controversial) papers that are shaping the field’s future direction.
If you are a BSc or MSc student at ETH Zurich interested in writing your thesis with us, we would be delighted to hear from you! Unfortunately, we do not have the capacity to consider students from outside ETH for thesis projects. To obtain a better understanding of what currently interests us, we invite you to check our most recent publications. However, feel free to express interest in any topic you think our group might be well suited to advise you on.
Specifically for Bachelor theses or semester projects, we typically assign you one of our published papers to replicate, so it would be ideal if you indicate 3-4 of our publications that you are interested in.
Please send in your inquiry using this form. It helps us a lot with finding a matching project if you are able to state more concrete topics that you would like to work on. We are looking forward to receiving your inquiry!
Thank you very much for your interest in joining our group – unfortunately, we are not accepting PhD students anymore!
If you are interested in working with us as a Master’s student, please see here. Ryan has previously co-advised Master’s students on NLP topics with Mrinmaya Sachan and others, if co-advising is an option you would like to pursue.
