Dr Nitsa Herzog is an esteemed researcher with an extensive academic and industry background. She is actively engaged in research at both Northumbria University (NU) and Birkbeck College, demonstrating her commitment to advancing knowledge and contributing to the academic community.

In her early career, Dr Herzog gained valuable experience as a Matlab and SAS programmer, utilising her technical skills to develop innovative solutions. Additionally, she worked as a Business Consultant specialising in Cloud Computing, where she applied her expertise to assist organisations in optimising their technological infrastructure and operations.

With a medical background, Dr Herzog brings a unique perspective to her work. She has valuable experience working in both the Ward and A&E departments of Adolescent Psychiatry, where she provided crucial medical support and care to patients. Furthermore, she actively participated in Clinical Trials as a dedicated researcher, contributing to advancing medical knowledge and developing new treatments and interventions.

• Herzog, N.J., Magoulas, G.D.: Brain Asymmetry Detection and Machine Learning Classification for Diagnosis of Early Dementia. Sensors, 21(3), p.778 (2021).
• Herzog, N.J. and Magoulas, G.D., 2021, June. Deep Learning of Brain   Asymmetry Images and Transfer Learning for Early Diagnosis of Dementia. In International Conference on Engineering Applications of Neural Networks (pp. 57-70). Springer, Cham.
• Herzog, N.J. and Magoulas, G.D., 2022. Machine Learning-Supported MRI Analysis of Brain Asymmetry for Early Diagnosis of Dementia. In Medical Informatics and Bioimaging Using Artificial Intelligence (pp. 29-52). Springer, Cham.
• Herzog, N.J. and Magoulas, G.D., 2022. Convolutional Neural Networks-Based Framework for Early Identification of Dementia Using MRI of Brain Asymmetry. International Journal of Neural Systems, pp.2250053-2250053.
• Herzog, N.J. and Magoulas, G.D., 2022. Transfer Learning and Magnetic Resonance Imaging Techniques for the Deep Neural Network-Based Diagnosis of Early Cognitive Decline and Dementia. In International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (pp. 53-66). Springer, Cham.

Qualifications

• PhD in Computer Vision & Machine Learning, Birkbeck College University of London, London, UK (2023)
• Master of Science, Technologies and Health, Université Paris-Est Créteil (UPEC), Paris, France (2017)
• BSc (Honors), Information Technologies and Business Information Systems, Middlesex University London, UK (2011)
• Doctor of Medicine (MD), Belarusian State Medical University, Minsk, Belarus (1994)

Professional certification and membership

• Fellowship of the Higher Education Academy (FHEA), (2022)
• SAS Certified Clinical Trials Programmer Using SAS 9, SAS Institution (2012)
• Oracle 10g, Administration Part I Certificate, Oracle (2008)
• MCTS Certificate for Microsoft SQL Server 2005, Microsoft (2008)
• Cisco Certified Network Associate (CCNA), Cisco (2010)