Dr. Sarah Williams
Associate Professor of Computer Science
s.williams@university.edu
+81 90-1234-5678
linkedin.com/in/sarahwilliamscs
github.com/swilliams-cs
DOB: 1990/03/15
Nationality: Australian
Status: Unmarried
Visa: Engineer/Specialist in Humanities Visa
Dependents: 0
Research Summary
Associate Professor of Computer Science with 12+ years in academia, specialising in machine learning and natural language processing. Published 35+ peer-reviewed papers (h-index 22) and secured over $2.4M in competitive research funding. Passionate about bridging industry and academia through applied research and mentoring the next generation of researchers.
Education
University of Tokyo
Kyoto University
Osaka University
Publications
- Williams, S., Chen, L., & Park, J. (2023). 'Explainable Transformers for Biomedical Text Classification.' NeurIPS 2023.
- Williams, S. & Rodriguez, A. (2022). 'Cross-Lingual Transfer Learning for Low-Resource NLP.' ACL 2022, pp. 1234–1245.
- Park, J., Williams, S., et al. (2021). 'Attention-Based Models for Clinical Note Summarisation.' EMNLP 2021.
- Williams, S. (2020). 'A Survey of Pre-trained Language Models for Domain-Specific Applications.' Journal of Machine Learning Research, 21(1), pp. 1–42.
Research Experience
- Lead the NLP & Applied ML research group (8 PhD students, 3 postdocs)
- Secured $1.8M ARC Discovery Grant for explainable AI research programme
- Published 12 papers in top-tier venues (NeurIPS, ACL, EMNLP) since 2020
- Redesigned postgraduate ML curriculum adopted by 3 partner universities
- Supervised 6 PhD completions with 100% employment placement rate
- Taught undergraduate and postgraduate courses (200+ students/semester)
- Co-authored textbook 'Applied Machine Learning' adopted by 15+ institutions
- Established industry partnership programme with 4 tech companies
- Received Faculty Teaching Excellence Award (2018)
- Conducted research in deep learning for biomedical text mining
- Published 8 papers with 1,200+ citations
- Collaborated with Stanford NLP Group on open-source toolkit development
Teaching Experience
University of Queensland
University of Queensland
University of Melbourne
Grants & Funding
- ARC Discovery Grant — Explainable AI for Healthcare — $1,800,000 — 2021
- Google Research Scholar Award — NLP for Accessibility — $80,000 — 2022
- University Strategic Research Fund — Cross-Lingual NLP — $520,000 — 2019
Conferences & Presentations
- Keynote Speaker — Australasian Language Technology Workshop (ALTA) — 2023
- Invited Talk — Google Research Sydney — 'Explainability in NLP' — 2022
- Oral Presentation — NeurIPS 2023, New Orleans, USA
Skills
Research: Machine Learning, NLP, Deep Learning, Statistical Analysis
Technical: Python, PyTorch, TensorFlow, R, LaTeX
Academic: Grant Writing, Curriculum Design, PhD Supervision, Peer Review