Lonneke van der Plas
https://usi.to/bkks
Biografia
Since October 2024, I am associate professor at USI at the Institute of Argumentation, Linguistics and Semiotics, and since February 2021, I am leading the Computation, Cognition & Language group at Idiap in Martigny, to which I am still affiliated. I was associate professor at the University of Malta from 2014-2020. Before that, I was junior professor at the Institute for Natural Language Processing (IMS), University of Stuttgart, where I lead a research group (see below) in the framework of the SFB 732, a collaborative research centre that brings computational linguists and linguists together. I did a post-doc (maître-assistante) at the University of Geneva working in the field of cross-lingual transfer of semantic role labelling as part of the CLASSiC project. I earned my PhD from the University of Groningen (Department of Humanities Computing), where I worked on vector-based word representations for medical question answering within the Alfa-Informatica group. Before that, I did the M.Phil Computer Speech and Language Processing at the University of Cambridge. The M.Phil has now been renamed into Computer Speech, Text and Internet Technology.
I have been working on the following subjects: computational linguistics, cross-lingual natural language processing (nlp), distributional semantics, vector-based word representations, text mining, (medical) terminology extraction, computational creativity, (medical) question answering, semantic role labelling, low-resource languages.
Visiting fellowships:
I was a DSI fellow at the University of Zurich from October 2019-January 2020.
I was a Erasmus Mundus LCT visiting scholar at the Shanghai Jiao Tong University (SJTU) and at the School of Computing and Information Systems of the University of Melbourne in June, July 2016.
I was a visiting academic at the Division of Information and Communication Sciences of Macquarie University, Sydney from January till March 2007.
More information on my personal website (see also link on the right-hand side).
Ricerca
SNSF (2024-2028, principle investigator)
The Swiss National Centre of Competence in Research (NCCR) Evolving Language is a nationwide interdisciplinary research consortium bringing together research groups from the humanities, from language and computer science, the social sciences, and the natural sciences at an unprecedented level. Together, we aim at solving one of humanity’s great mysteries: What is language? How did our species develop the capacity for linguistic expression, for processing language in the brain, and for consistently passing down new variations to the next generation? How will our capacity for language change in the face of digital communication and neuroengineering?
Within this framework the task Lexical Innovation will investigate how new terms are formed and how they spread in different contexts, thereby comparing Western societies with hunter-gatherer societies. This task is led by Prof. Lonneke van der Plas , together with Lena Jäger and Andrea Migliano from the University of Zurich.
PhD student: To be filled. More information and link to upload your application here (see 'APPLY).
FactCheck
Hasler Foundation (2024, co-PI)
In this project we plan to build a dataset and implement methods for multi-modal fact checking
Postdoc: Michiel van der Meer
C-LING
SNSF 2022-2026 (PI)
This project aims to create computational models of language as a tool for creative thinking. We will extract statistical patterns from large text corpora to inform these models as well as structured knowledge bases. We aim to generate new concepts by means of comparing statistical patterns in large text corpora from different cultures and domains, just like a person may get new ideas from travelling and collaborating with people from different backgrounds. At the same time, we want to go one step further by looking at more complex constructs such as new ideas, for example scientific discoveries. For such complex constructs statistical patterns alone will not suffice and structural knowledge will be added to our models.
PhD students:
Molly Petersen
Mete Ismayilzada
SEM24
Innosuisse 2023-2025 (PI)
SEM24 focuses on skill extraction in multiple languages from resumes and job ads that incorporates insights from the fields of HRM and NLP. We work with real-world data in collaboration with the EHL business school and ARCA24. The semantic engine will identify a wider range of important skills, including soft skills, improving the matching quality, mitigating bias and significantly reducing manual labor.
Post-doc:
Laura Vasquez
Developer:
Samuel Michel
Transfer manager:
Alexandre Nanchen
PREVIOUS PROJECTS:
LT-BRIDGE
H2020-WIDESPREAD (2021–2024, main applicant/coordinator > external collaborator)
Bridging the technology gap: Integrating Malta into European Research and Innovation efforts for AI-based language technologies.
UPSKILLS (UPgrading the SKIlls of Linguistics and Language Students)
EU Erasmus+ (2021-2023, main applicant/coordinator > external collaborator)
The central goal of this project is to tackle the identified skills gaps and mismatches in linguistics and language students through supporting the development of innovative materials that better meet the learning outcomes needed in the current job market, and this in collaboration with language technology companies.
MUFINS (NLP-Driven, MUltilingual FInancial News and content Search)
Malta Enterprise Research grant (2020-2022, co-applicant)
This project aims to investigate transfer learning techniques to resolve a variety of NLP tasks in multiple languages, within the financial and news domains. This project is led in collaboration with CityFalcon Trading Ltd.
Postdoc:
Marc Tanti
MASRI (Maltese Automatic Speech Recognition)
UM Research Fund (2018-2020, co-applicant)
This project aims to build a automatic speech recogniser for Maltese, a low-resource language, using various bootstrapping approaches.
SFB 732 project D11: A crosslingual approach to the analysis of compound nouns
DFG (2014-2018, main applicant)
This project tries to bridge the gap between computational linguistics and theoretical linguistics by using linguistically-informed models and explicitly testing hypotheses stemming from Linguistics literature. It proposes a compositional approach to noun-noun (N-N) compound analysis with an interdependent three-level model that comprises compound splitting, capturing the meaning of the components and the covert relation that holds between them. We used multi-lingual data throughout the project, in analysis and evaluation, and followed a language-independent approach, using automatic, knowledge-lean, data-driven methods.
PhD students:
Stefan Müller
Patrick Ziering
Collaborations with Gianina Iordachioaia (Institute for English Linguistics)