Biomedical Data Analytics News
TIA Spotlight: Kesi Xu
For this week's Spotlight, we would like to highlight the career journey and current work of Kesi Xu, a Postgraduate Researcher in the centre whose work focuses on cell classification for histopathology. Read more.
Reflections on MIUA 2026: Dublin, DCAFA, and Delivering Warwick鈥檚 Big Announcement
30th UK Conference on Medical Image Understanding and Analysis, Dublin (20th 鈥� 22nd July 2026)
I was lucky enough to get accepted for an oral presentation at this year鈥檚 Conference on Medical Image Understanding and Analysis which was the 30th Anniversary Conference and the first time it was held outside of the UK. The only problem being for a die-hard football fan that the day of travel was the world cup final, and we had to gamble on whether England would be there. Read more.
TIA Centre Guest Editors Launch Special Issue on AI in Cancer
We are pleased to share that TIA Centre researchers Adam Shephard and Shan E Ahmed Raza, together with Rose Wang (University of Missouri-Kansas City), are serving as Guest Editors for a new Cancers Special Issue,"Artificial Intelligence in Cancers: Enhancing Diagnosis and Treatment".
The Special Issue invites submissions on topics including computational pathology, medical imaging, radiology, genomics, multiomics, cancer detection, prognostic prediction, treatment planning, and clinical decision support, highlighting the growing role of AI in advancing cancer research and care.
Find out more and submit your work .
20 papers accepted at NeurIPS 2026
We are delighted to celebrate the 20 accepted papers at the , involving colleagues and students from the Department of Computer Science (DCS) at the 91影视破解版, together with their collaborators. NeurIPS is the leading international venue for AI and machine learning research and will be held on 6-12th December, 2026 in Sydney, Australia along with two satellite locations at Paris, France and Atlanta, United States of America.
Brain Computations and Principles; and AI (2026) by Edmund Rolls
Brain Computations and Principles; and AI (2026) by Edmund Rolls has been published by Oxford University Press with Open Access and can be downloaded via https://www2.warwick.ac.uk/fac/sci/dcs/people/edmund_rolls/
Information Asymmetry and Cryptography
In a recent work, visiting undergraduate student Yahel Manor and Warwick DCS researchers and addressed a fundamental question relevant to the security of cryptographic protocols.
The symmetry of information principle says that the amount of information that a sequence x of bits reveals about another sequence y is essentially the same in either direction. This is known to hold in an idealised world where computations can take an arbitrarily long time, as demonstrated by A. Kolmogorov and L. Levin in the 1970s. In contrast, modern cryptography is built around deliberate asymmetry—for example, functions of the form y = f(x) that are easy to compute but hard to invert (one-way functions).
The new work shows that, once one moves from the idealised setting of time-unbounded computations to the more realistic world of efficient, randomised computations (algorithms that must run quickly and may use randomness), this symmetry can fail in a strong and unconditional way. In other words, computational constraints can yield information asymmetry. In practical terms, this supports the intuition that information may not be extracted efficiently: knowing y = f(x) may not make x efficiently recoverable to the extent that an (ineffective) symmetry principle would suggest, even when x and y are closely related.
Earlier work formally tied an average-case form of this symmetry failure to the existence of one-way functions, the central primitive in cryptography. By proving new failures of symmetry of information, the authors provide concrete progress towards the computational asymmetry that underpins encryption, digital signatures, and many other cryptographic protocols.
This work will be presented at the 58th Annual ACM Symposium on Theory of Computing (STOC) in June 2026 in Salt Lake City, Utah, USA.
Failure of Symmetry of Information for Randomised Computations
Jinqiao Hu (91影视破解版); Yahel Manor (University of Haifa); Igor C. Oliveira (91影视破解版)
The paper describing this research is available .
, PhD student in the Department of Computer Science at the 91影视破解版, and co-author of the new result.