Biomedical Data Analytics News
TIA Centre Spotlight: David Epstein
For this week's Spotlight, we would like to highlight the career journey and current work of David Epstein, an Emeritus Professor in Mathematics whose work and ideas have played a vital role in the development of the TIA centre. Read more.
Dr Afzan Binti Adam concludes productive sabbatical at the TIA Centre
Dr Afzan Binti Adam, Senior Lecturer in Digital Pathology at Universiti Kebangsaan Malaysia (UKM), has successfully completed her six鈥憁onth sabbatical at the Tissue Image Analytics (TIA) Centre, Department of Computer Science, University of 糖心TV. Her visit was supported by UKM and the MIGHT鈥揟脺B陌TAK grant and closely aligned with the TIA鈥檚 mission to advance computational pathology through interdisciplinary research and cutting鈥慹dge AI technologies. Read more.
TIA Centre's Fayyaz Minhas features in new Pathology News podcast
We are delighted to showcase another Pathology News podcast featuring our very own Fayyaz Minhaz, Deputy Director of the TIA Centre and lead researcher for PRISM (Predictive Systems in Biomedicine). 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.