Computer Science News

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.

We 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 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.

We're happy to announce that Zhenjian Lu has joined the department as a Research Fellow. He is currently funded by the project "New approaches to unconditional computational lower bounds", with support from the Royal Society.

Zhenjian Lu will soon defend a PhD thesis in computational complexity at Simon Fraser University under the supervision of Prof. Valentine Kabanets and Prof. Andrei Bulatov.

He is primarily interested in Computational Complexity, Circuit Lower Bounds, Algorithms, Pseudorandomness, Analysis of Boolean Functions, and Meta-Complexity.

Dr Theo Damoulas (Department of Computer Science) along with Dr David Armstrong (Department of Physics) and Jevgenij Gamper (Department of Mathematics) have developed probabilistic machine learning algorithms that can separate out real planets from fake ones in the large samples of thousands of candidates found by telescope missions such as NASA’s Kepler and TESS. The results of which have led to fifty new confirmed planets, the first to be not only ranked but also probabilistically validated by machine learning.

The paper "Exoplanet Validation with Machine Learning: 50 new validated Kepler planets" has been accepted to the Monthly Notice of the Royal Astronomical Society, DOI: 10.1093/mnras/staa2498

Work performed by Computer Systems Engineering student Michael Shanta for his 3rd year project, supervised by Dr. Marina Cole and Dr. Siavash Esfahani in the School of Engineering, was written up in a paper that was recently accepted for presentation at the IEEE Sensors 2020 Conference.

For his 3rd year project Michael worked on developing machine learning techniques for an Electronic Nose in order to classify odours based on the sensor responses. The system aims to detect incontinence incidents, allowing alerts to be sent to relevant personnel from an IoT network via a cloud server.

Dr Sathyawageeswar Subramanian has joined the department to work as a Research Fellow on the "Foundations of classical and quantum verifiable computing" project, which is led by Dr Tom Gur.

Sathya completed his PhD in quantum computing at the University of Cambridge under the supervision of Prof. Richard Jozsa. His primary interests are quantum algorithms and computational complexity theory.

We congratulate all A-level students on their recent achievements. The quality of our intake in recent years has been outstanding and we are delighted to report that we will be welcoming another exceptional cohort of first year students. We look forward to getting to know you all in the coming term, and hope you will enjoy taking your next steps in your development as Computer Scientists.

Due to this year's special circumstances, this cohort will be by far the largest in the history of the department. While there will be challenges for students and staff alike, we will work hard, together with our students, to ensure that everybody can fully realize their considerable potential. We are excited and are looking forward to meeting this new talented group of students