Scholar
Chen Cecilia Liu
Google Scholar ID: eNFB3fgAAAAJ
Technische Universität Darmstadt
Citations & Impact
Citations
259
H-index
6
i10-index
6
Publications
17
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- July 2025: Guest lecture at TUDa on cultural NLP; May 2025: 1 paper accepted at ACL; Apr 2025: New preprint available on cultural NLP; Mar 2025: 1 paper accepted at TACL; Feb 2025: Guest lecture at MBZUAI on cultural NLP; Jun 2024: A workshop version of our paper on early period of training and OOD generalization is accepted at HiLD@ICML; Jun 2024: New preprint available on culturally aware NLP; Mar 2024: New preprint available on early period of training and OOD generalization; Mar 2024: 2 papers accepted at NAACL-HLT 2024; Jan 2024: Visiting LTL at the University of Cambridge for the next 6 months! Sep 2023: New preprint available on culture and LLMs; May 2023: Paper accepted at RepL4NLP Workshop, ACL 2023; Jan 2023: Paper accepted at EACL 2023; Oct 2022: Paper accepted at EMNLP 2022.
Research Experience
- Worked in the NLP industry for nearly a decade before returning to academia. Worked at Canadian startups such as Meta (acquired by CZI), Wattpad (acquired by NAVER WEBTOON), and ElementAI (acquired by ServiceNow).
Education
- ELLIS PhD student at Technische Universität Darmstadt (UKP Lab), Germany and the University of Cambridge, UK. Supervised by Prof. Iryna Gurevych and Prof. Anna Korhonen. Previously, obtained both undergraduate and master’s degrees from the University of Toronto, with master’s research under the supervision of Prof. Brendan Frey (PSI Lab, Toronto ML).
Background
- Research interests include cultural adaptation and alignment, efficient and low-resource methods for multilingual NLP, methods and analyses of models inspired by developmental psychology, neuroscience, or social psychology, and applications in education, healthcare, psychotherapy, and the creative industries, emphasizing multilinguality and cultural adaptation.
Miscellany
- Appreciates pure deep learning methods but is equally drawn to ideas for NLP grounded in theories and insights from other disciplines, such as sociology, anthropology, etc.
Co-authors