معرفی
Dr. Henrietta Tomán serves as an Assistant Professor in the Department of Data Science and Visualization at the University of Debrecen's Faculty of Informatics, where she bridges advanced mathematical theory with practical medical imaging applications. Her work integrates abstract algebraic structures with cutting-edge AI systems to solve critical healthcare challenges.
Her research portfolio spans three interconnected domains:
- Medical image processing (particularly ensemble-based segmentation and quality assessment for ophthalmic diagnostics)
- Geometric structures (quasigroups, loops, and differentiable manifolds)
- Stochastic optimization for resource-constrained AI systems
Analysis of her publication trajectory reveals evolving expertise: early work (2010-2014) established foundations in geometric loop theory applied to image processing, while recent research (2020-2024) pioneers stochastic fusion techniques for medical image ensembles under computational constraints. Her most significant contributions involve translating mathematical abstractions into robust clinical decision-support tools, particularly in diabetic retinopathy detection and epidemic modeling. Current work demonstrates increasing focus on real-time AI systems that maintain accuracy under hardware limitations, reflecting urgent needs in telemedicine and mobile health applications.
Dr. Tomán maintains active collaboration within the Doctoral School of Informatics and contributes to Hungary's national research initiatives in medical AI, with consistent publication output in top-tier venues spanning computer vision, medical imaging, and mathematical computing.
