Regular biography
Andrey Kormilitzin is a Research Fellow at the Mathematical Institute, University of Oxford, within the Department of Mathematics. His research interests include statistical machine learning, deep learning, bioinformatics, and applications of machine learning and deep learning to healthcare. He also engages in stochastic analysis, sequential data, signatures, particle physics, quantum field theory, and scattering amplitudes. Kormilitzin has contributed to various publications in mental health care, digital health, and biomedical research. His work includes AI-assisted triage, privacy-preserving language models, and synthetic data applications in clinical research.
Scholar-generated biography
Andrey Kormilitzin is a researcher at the University of Oxford with expertise in Machine Learning, Deep learning, Theoretical Physics, Machine learning for healthcare, and Health Informatics. His work focuses on developing machine learning techniques for healthcare applications, including natural language processing for clinical text data, early detection of sepsis from electronic health records, and explainable AI for mental health. He also explores theoretical physics, particularly in the context of scattering amplitudes in super-Yang-Mills theory. His research emphasizes the application of AI in dementia research, clinical prediction rules, and personalized treatment models for cognitive impairment.