جست‌وجوی استاد و پژوهشگر

• Medical Imaging
• Radiotherapy
• Virtual Reality
• +۵ مورد دیگر

Michael Rauter serves as a Research Associate at the University of Applied Sciences Wiener Neustadt (FHWN) within the Faculty of Health and the Competence Center for Preclinical Imaging and Medical Technology. His work bridges computer science and medical applications, focusing on advanced imaging techniques for radiotherapy and assisted living technologies. Dr. Rauter's research interests include: Medical imaging for precision radiotherapy GPU-accelerated image processing Virtual and mixed reality applications in healthcare Computer vision for medical diagnostics Assisted living technologies and home care systems His recent publications show a clear evolution from computer vision applications in security systems toward medical applications. The 2024 paper on accelerating transfer function updates for volume rendering represents the current focus on optimizing medical visualization techniques, while earlier works from 2013 demonstrate foundational expertise in GPU-accelerated computer vision. Dr. Rauter is actively involved in multiple research projects funded by organizations including FFG (Austrian Research Promotion Agency) through the Active Assisted Living Programme. His current projects include PAIR (2022-2026) and Applied Molecular Imaging (2021-2026), with previous contributions to Care about Care (2021-2023) and CARU Cares (2019-2022). As a member of the Competence Center for Preclinical Imaging and Medical Technology, Dr. Rauter contributes to research that integrates advanced imaging modalities with radiotherapy, aiming to improve cancer treatment through personalized precision approaches. His work combines technical expertise in computer vision and GPU programming with medical applications to advance healthcare technologies.

• Computer Vision
• Explainable Machine Learning
• Statistical Models in AI
• +۳ مورد دیگر

Siavash Arjomand Bigdeli serves as an Associate Professor of Computer Vision at the Technical University of Denmark, following prior employment as a scientist at the Swiss Center for Electronics and Microtechnologies (CSEM). His research focuses on: Ante-/Post-Hoc explainability of machine learning models Integration of statistical models in learning/inference processes Philosophical methodologies in artificial intelligence development Advanced computer vision techniques for visual understanding Recent publications reveal consistent specialization in image restoration and stereo vision, employing deep learning architectures and probabilistic graphical models to solve core challenges in visual data reconstruction and temporal coherence. His work demonstrates strong interdisciplinary connections between theoretical machine learning, practical computer vision applications, and epistemological considerations in AI systems.