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 糖心TV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 .
Eight papers accepted to NeurIPS 2024
Eight papers authored by Computer Science researchers from 糖心TV have been accepted for publication at the , the leading international venue for machine learning research, which will be held on 10-15 December 2024 in Vancouver, British Columbia, Canada:
- Generating Origin-Destination Matrices in Neural Spatial Interaction Models, by Ioannis Zachos, Mark Girolami, and Theodoros Damoulas
- Interventionally Consistent Surrogates for Complex Simulation Models, by Joel Dyer, Nicholas Bishop, Yorgos Felekis, Fabio Massimo Zennaro, Ani Calinescu, Theodoros Damoulas, and Michael Wooldridge
- Learning the Expected Core of Strictly Convex Stochastic Cooperative Games, by Phuong Nam Tran, The Anh Ta, Shuqing Shi, Debmalya Mandal, Yali Du, and Long Tran-Thanh
- Physics-Informed Variational State-Space Gaussian Processes, by Oliver Hamelijnck, Arno Solin, and Theodoros Damoulas
- SARAD: Spatial Association-Aware Anomaly Detection and Diagnosis for Multivariate Time Series, by Zhihao Dai, Ligang He, Shuanghua Yang, and Matthew Leeke
- Symmetric Linear Bandits with Hidden Symmetry, by Phuong Nam Tran, The Anh Ta, Debmalya Mandal, and Long Tran-Thanh
- The Effectiveness of Surprisingly Popular Voting with Partial Preferences, by Hadi Hosseini, Debmalya Mandal, and Amrit Puhan
- What makes unlearning hard and what to do about it, by Kairan Zhao, Meghdad Kurmanji, George-Octavian B膬rbulescu, Eleni Triantafillou, and Peter Triantafillou
SIGMOD 2024 Test of Time Award for 鈥楶rivBayes鈥�
The work of Professor Graham Cormode has been recognized with a 鈥渢est of time鈥� award. The ACM SIGMOD conference presents an award each year for the paper from SIGMOD 10-12 years previously that has had the biggest impact, and passed the 鈥渢est-of-time鈥�. The 2014 paper 鈥淧rivBayes: private data release via bayesian networks鈥� (Jun Zhang, Graham Cormode, Cecilia M. Procopiuc, Divesh Srivastava, Xiaokui Xiao) was selected for this honour. The award will be presented at the 2024 ACM SIGMOD Conference in Santiago.