Vasileios (aka Bill) Lampos
Associate Professor
Ωmega Research Group
Centre for Artificial Intelligence
Department of Computer Science
University College London
Join us!
Twitter: @lampos
UCL profile
Email: v.lampos (at) ucl.ac.uk
Research news
- *** Join my research group! Opportunities are listed here. ***
- 01/11/2025 — For more up-to-date material and announcements, please check the Ωmega research group website. I will maintain this space, but updates will be more sparse.
- 01/04/2025 — Our paper titled "DeformTime: capturing variable dependencies with deformable attention for time series forecasting" is now published in the Transactions on Machine Learning Research (TMLR).
- 28/08/2023 — Our paper titled "Neural network models for influenza forecasting with associated uncertainty using Web search activity trends" is now published in PLOS Computational Biology.
- 01/09/2021 — Our paper titled "An artificial intelligence approach for selecting effective teacher communication strategies in autism education" is now published in Nature (npj) Science of Learning.
- 08/02/2021 — Our paper titled "Tracking COVID-19 using online search" is now published in Nature (npj) Digital Medicine. You can find more about our work in this press release.
- 10/09/2020 — A Google.org initiative is supporting our research on COVID-19.
- 18/09/2019 — Our research on transfer learning for disease surveillance models from online search activity was covered by Nature as part of an outlook article about real-time flu tracking.
- 21/01/2019 — 2 papers have been accepted by the Web Conference 2019. The first one proposes a transfer learning method for estimating flu rates using web search activity in locations that do not have an established health surveillance system, and the second proposes a privacy-preserving framework for collecting web search activity data for health-related research.
- 24/05/2018 — The 2017/18 annual flu report by Public Health England incorporates internet-based flu rate estimates, powered by web search activity and our machine learning models.
- 22/12/2017 — Our paper on multi-task learning models for syndromic surveillance from Google search data has been accepted by WWW 2018.
- 01/01/2017 — Our paper proposing a better feature selection method for syndromic surveillance models from web search activity was accepted by WWW 2017.
- 24/10/2016 — Our paper on predicting judicial decisions of the European Court of Human Rights using statistical NLP was published in PeerJ Computer Science; this research has been covered by mainstream media outlets (e.g. VICE, BBC, The Guardian) as well as a UCL press release.