News

[10/24] Exciting news! My paper Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities 🧠, was accepted at WACV 2025. Looking forward to presenting our results in Arizona! 🤠

[10/24] Received an honorable mention as outstanding reviewer for the MICCAI conference 📚. I hope my reviews contributed to the community and help improve future submissions.

[05/24] The paper Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation, led by my colleague Wentian Xu, in which I am co-author, was accepted at MIDL 2024 and selected for an oral presentation.

[02/24] Pre-print of Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection by my colleague Pramit Saha, and co-authored by me, is now available on arXiv.

[08/23] My first paper ⭐ Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment ⭐ got accepted in the Machine Learning in Medical Imaging (MLMI 2023) workshop at MICCAI 2023 and was selected for an oral.

[08/23] Modality Cycles with Masekd Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI from my colleague Ziyun Liang, in which I am coauthor, got accepted in Multiscale Multimodal Medical Imaging workshop in MICCAI 2023.

[09/22] I joined Professor Kamnitsas’ lab and started research on Federated Learning for Medical Imaging.

[12/21] Completed my master’s degree at TU Wien with a master’s thesis on injecting symbolic knowledge into Knowledge Graph Embeddings.

[09/21] Received the Angela-Krosik scholarship from the Anglo-Austrian Society.

[09/21] Started first year of the Health Data Science CDT PhD programme in Oxford with one year of courswork in Statistics, Machine Learning, Ethics, Health and Biomedical research.