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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.


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.


EPSRC funding success for Dr. Ramanujan Sridharan

RamanujanWe are delighted to report that Dr Ramanujan Sridharan from the Theory and Foundations (FoCS) research theme at the Computer Science Department has received a prestigious EPSRC New Investigator Award. The approximately £264K project titled "New frontiers in Parameterizing Away From Triviality” aims to develop novel notions of graph edit distance and investigate their connections to efficient solvability of computationally hard problems.
The reviewers commented:
the proposal identifies research questions that are novel, has the potential to have a broader impact both within and outside academia and it is an exciting project that will break new ground.
Mon 21 Sep 2020, 20:38 | Tags: People Grants Highlight Theory and Foundations

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