I am Saatviga Sudhahar and this is my personal web site. I’m a Machine Learning Scientist at Healx in Cambridge currently working on Knowledge graph Inference and Reasoning using Deep Learning. Before joining Healx I worked as a Postdoctoral Research Associate at the University of Bristol on large scale news content analysis, narrative network analysis, machine translation and probabilistic inference for fact checking. I have also worked on building scalable online learning modules that learn reader preferences for different news outlets using machine learning techniques. I completed my PhD in Bristol University and my research was about ‘Automating Large scale analysis of narrative text using network analysis methods‘. Before coming to Bristol I have been a member of the academic staff at the University of Colombo School of Computing (UCSC) SriLanka.
Recent Posts
- Content Analysis of 150 years of British Periodicals
Previous studies have shown that it is possible to detect macroscopic patterns of cultural change over periods of centuries by analyzing large textual time series, specifically digitized books. This method promises to empower scholars with a quantitative and data-driven tool to study culture and society, but its power has been limited by the use of data from books and simple analytics based essentially on word counts.
This study addresses these problems by assembling a vast corpus of regional newspapers from the United Kingdom, incorporating very fine-grained geographical and temporal information that is not available for books. The corpus spans 150 years and is formed by millions of articles, representing 14% of all British regional outlets of the period. Read more..
- Gender Representation in Online News
It has long been argued that women are under-represented and marginalised in relation to men in the world’s news media. In this research we analysed over two million articles to find out how gender is represented in online news. The study, which is the largest undertaken to date, found men’s views and voices are represented more in online news than women’s.
Modern AI, which is frequently in the news, is a great tool to support research and can automate tasks that would take humans an impossible amount of person-hours to complete. It is now possible to automate the task of recognising the gender of a face with a remarkable level of accuracy, and it is also possible to detect references to people in online text, along with their gender. Read more..
Recent Publications
- Sudhahar, S., Pierleoni, A., & Roberts, I. (2019, November). Reasoning Over Paths via Knowledge Base Completion. In Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13) (pp. 164-171).
- Sudhahar S., Cristianini N. (2018) Detecting Shifts in Public Opinion: a big data study of global news content. Symposium on Intelligent Data Analysis (IDA 2018). (pp. 316-327). Springer, Cham.
- Bindris N., Sudhahar S. & Cristianini N. (2018) Fact Checking from Natural Text with Probabilistic Soft Logic. Symposium on Intelligent Data Analysis (IDA 2018).(pp. 52-61) Springer, Cham.
