Data Science News
Suzanne Candanedo wins UKESF and UltraSoC Automotive Electronics Competition 2020
Suzanne Candanedo, who recently graduated from Computer Systems Engineering at the University of Warwick, has won the UKESF and UltraSoC Automotive Electronics Competition 2020.
The competition requires entrants to produce a 'think piece' about the future of cyber security for connected and autonomous vehicles, written along the lines of a blog post in style rather than a formal essay. You can read Suzy's winning entry here.
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
Adam Shephard joins the TIA lab

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.