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Graham Cormode named 2020 ACM Fellow

Prof. Graham Cormode of the Department of Computer Science has been named among the 2020 Association for Computing Machinery (ACM) Fellows, for contributions to computer science. The ACM is the world's leading learned society for computer science. Prof. Cormode is recognised for his contributions to data summarisation and privacy enabling data management and analysis. His work on data streams and sketching has been widely implemented in many high tech companies and organisations.


Warwick Postgraduate Colloquium in Computer Science 2020

This year’s Warwick Postgraduate Colloquium in Computer Science (WPCCS) was held on Monday 14th December and marked the 18th edition of this beloved event. For the first time in its history, WPCCS took place online, on the communication platform MSTeams, to allow everyone to participate safely during the ongoing COVID-19 pandemic.

A cherished occasion to present one’s research, receive valuable feedback, and create connections within the department to develop new ideas, the Colloquium saw the participation of 50 PhD students who gave presentations spread across seven major themes, showcasing the quality and diversity of the research carried out in the Computer Science Department at Warwick. 22 PhD students also submitted longer, more detailed presentations which were made available to participants and attendees on the official WPCCS MSTeam, so to receive constructive in-depth comments.

Fri 18 Dec 2020, 09:22 | Tags: Conferences Research

EPSRC funding awarded to Prof. Yulan He and Prof. Rob Procter on developing an AI solution for tackling “infodemic”

Prof. Yulan He and Prof. Rob Procter have been awarded funding from the EPSRC under the UKRI’s COVID-19 call. During the COVID-19 pandemic, national and international organisations are using social media and online platforms to communicate information about the virus to the public. However, propagation of misinformation has also become prevalent. This can strongly influence human behaviour and negatively impact public health interventions, so it is vital to detect misinformation in a timely manner. This project aims to develop machine learning algorithms for automatic collection of external evidence relating to COVID-19 and assessment of veracity of claims.

The project is in collaboration with Prof. Maria Liakata and Dr. Arkaitz Zubiaga from the Queen Mary University of London.


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