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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 recognized for his contributions to data summarization
and privacy enabling data management and analysis. His work on data
streams and sketching has been widely implemented in many high tech
companies and organizations.

Thu 14 Jan 2021, 12:08 | Tags: People Highlight Research Faculty of Science Data Science

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.

Wed 16 Dec 2020, 16:38 | Tags: Grants Research Human-Centred Computing Data Science

Prof. Nasir Rajpoot awarded funding by Cancer Research UK to use machine learning to improve the early detection of oral cancer

Cancer Research UK is funding a study to examine the use of machine learning to assist pathologists and improve the early detection of oral cancer.

We are very excited to work on this project with Dr Khurram and his team at Sheffield. Early detection of cancer is a key focus area of research in our lab and this award by CRUK adds to the portfolio of research at the TIA lab on early detection of cancer.

The pilot project will pave the way towards the development of a tool that can help identify pre-malignant changes in oral dysplasia, crucial for the early detection of oral cancer. Successful completion of this project carries significant potential for saving lives and improving patient healthcare provision. -- Professor Nasir Rajpoot

The research is led by Dr Ali Khurram at the University of Sheffield with Professor Nasir Rajpoot from the University of Warwick as the co-Principal Investigator. Other co-investigators and collaborators include Professor Hisham Mehanna and Dr Paul Navkivell from the University of Birmingham and Dr Jacqueline James from Queen’s University Belfast.

Tue 03 Nov 2020, 10:12 | Tags: Grants Research Applied Computing Artificial Intelligence

WM5G funding awarded to Prof. Hakan Ferhatosmanoglu on machine learning based spatio-temporal forecasting

Warwick's Department of Computer Science has been awarded a new research grant to develop a machine learning solution for dynamic forecasting of available capacity on road networks. The developed software is planned to be integrated within the TfWM's Regional Transport Coordination Centre for adaptive route planning and traffic management mitigation against disruptions, incidents and roadworks.

The “5G Enabled Dynamic Network Capacity Manager” project is in collaboration with commercial partners, Blacc, Immense, one.network, and O2. The team has won the WM5G’s transport competition to leverage 5G networks for near real-time AI based modelling.

Prof. Hakan Ferhatosmanoglu is leading the development of the scalable ML solution to forecast residual capacities in a dynamic spatio-temporal graph. The solution is designed to benefit from high-granular and low-latency data feeds from 5G cellular and sensor data enabling congestion to be accurately monitored, modelled, and predicted.

Mon 02 Nov 2020, 11:20 | Tags: Grants Research Artificial Intelligence Data Science

Six papers accepted to the 32nd SODA conference

We are pleased to report that members of the department's Theory and Foundations research theme have had 6 papers accepted to the 32nd Annual ACM-SIAM Symposium on Discrete Algorithms. SODA is the top international conference on algorithms research. The papers are:

  • "A Structural Theorem for Local Algorithms with Applications to Coding, Testing, and Privacy" by Marcel Dall'Agnol, Tom Gur, Oded Lachish;
  • "On a combinatorial generation problem of Knuth" by Arturo Merino, Ondřej Mička, Torsten Mutze;
  • "Dynamic Set Cover: Improved Amortized and Worst-Case Update Times" by Sayan Bhattacharya, Monika Henzinger, Danupon Nanongkai, Xiaowei Wu;
  • "Online Edge Coloring Algorithms via the Nibble Method" by Sayan Bhattacharya, Fabrizio Grandoni, David Wajc;
  • "FPT Approximation for FPT Problems" by Daniel Lokshtanov, Pranabendu Misra, M. S. Ramanujan, Saket Saurabh, Meirav Zehavi.
  • "Polyhedral value iteration for discounted games and energy games" - Alexander Kozachinskiy
Fri 09 Oct 2020, 20:53 | Tags: Research Theory and Foundations

Adam Shephard joins the TIA lab

Adam Shephard

Adam Shephard has just joined the department as a Research Fellow and is currently working in the Tissue Image Analytics (TIA) Lab on the ANTICIPATE project funded by Cancer Research UK. He has recently submitted his thesis on the application of deep learning to paediatric MRI at Aston University, under the supervision of Prof. Amanda Wood and Dr. Jan Novak. His role in the ANTICIPATE project will be concerned with the development and application of deep learning techniques to digitized histology slides to aid in the more efficient grading of head and neck tumours, to ultimately provide more accurate patient prognoses.


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