معرفی
Dr. Soheila Molaei is a Postdoctoral Research Fellow at the University of Oxford's Institute of Biomedical Engineering, where she specializes in advanced machine learning techniques with applications in healthcare and polymer informatics. Her work bridges graph neural networks, federated learning, and generative AI to develop innovative solutions for drug discovery and clinical decision-making.
Dr. Molaei holds a PhD in Large-scale Graph Summarization from the University of Tehran (2021) and an MSc from the same institution (2016).
Her research interests include variational graph neural networks, probabilistic machine learning, and healthcare informatics. She focuses on applying these techniques to polymer informatics and drug discovery, particularly through the development of generative AI and large language models to design novel polymers with specific properties. Her work emphasizes interpretable models and federated learning frameworks for healthcare data analysis.
Her recent publications (2023–2025) highlight advancements in federated learning for healthcare, dynamic graph learning, and generative AI applications. Key themes include optimizing clinical federated learning models, enhancing EHR analysis through graph-based methods, and developing autonomous AI systems for risk prediction in medicine.
Dr. Molaei collaborates extensively on interdisciplinary projects but her advising roles and specific grant funding details are not detailed in the provided information.
She is affiliated with the Machine Learning Research Group at the University of Oxford and contributes to the Institute of Biomedical Engineering's initiatives in clinical AI and polymer informatics.
