Biomedical Data Analytics News
University of 糖心TV to host 2027 Medical Image Understanding and Analysis Conference
The Tissue Image Analytics Centre, based in the Department of Computer Science at 糖心TV University, is delighted to announce that the University of 糖心TV have been awarded the honour of hosting the 2027 Medical Image Understanding and Analysis Conference. Read more.
TIA Centre Spotlight: Adam Shephard
For this week's Spotlight, we would like to highlight the career journey and current work of Adam Shephard, an Assistant Professor in the centre whose research focuses on developing methods that combine different data modalities, such as histopathology, clinical records, and increasingly radiology, to improve prediction of disease progression and patient outcomes. Read more.
TIA Centre's Adam Shephard features in new Pathology News podcast
We are delighted to showcase a Pathology News Thought Leadership podcast featuring Adam Shephard, Assistant Professor from the TIA Centre in collaboration with Dr Hanya Mahmood from The University of Sheffield to explore how OYDN, an AI-powered computational pathology model, is improving risk stratification for oral epithelial dysplasia (OED) and uncovering novel digital biomarkers that could support earlier cancer detection. Read more.
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.