Find Academic Supervisors

• Neural Engineering
• Biomedical Engineering
• Computational Neuroscience
• +3 more

Paul Werginz is a Research Fellow at the Institute of Biomedical Electronics (E363) at TU Wien (Vienna University of Technology), holding a Diplom-Ingenieur (Dipl.-Ing.) and Doctor of Technical Sciences (Dr.techn.) degree. His work focuses on computational modeling of neural stimulation for sensory prostheses, with primary affiliations in neural engineering and biomedical electronics research groups. Dr. Werginz's research centers on biophysical mechanisms of neural stimulation in retinal and auditory systems. He investigates axon initial segment geometry, biophysical diversity in retinal ganglion cells, and electrode placement optimization for cochlear implants. His computational approaches employ finite element modeling and multiphysics simulations to analyze neural responses to electrical stimulation, aiming to enhance the efficacy of visual and auditory prostheses through precise stimulation strategies. Analysis of his 2022-2023 publications reveals dominant trends in retinal prosthesis optimization (70% of works) and cochlear implant modeling (30%). Key thematic clusters include axon initial segment biophysics, network-mediated visual processing, and high-frequency stimulation effects across neural cell types. His research consistently applies computational neuroscience to solve engineering challenges in sensory restoration, with strong emphasis on translating biophysical principles into clinical applications for neural prosthetics. Dr. Werginz has not received any scientific awards mentioned in the available documentation. He serves as Principal Investigator for two Austrian Science Fund (FWF) projects: 'Biophysikalische Diversität in retinalen Ganglienzellen' (Biophysical Diversity in Retinal Ganglion Cells) and 'Identification of calcium current reversal in bipolar cells'. His supervisory contributions include master's theses by Dizdar, Fatima (2023) on retinal ganglion cell dynamic range and Bucek, Fred (2023) on cochlear implant simulations, indicating active mentorship in computational neuroscience. As a core member of TU Wien's Network Lab within the Institute of Biomedical Electronics, Dr. Werginz collaborates extensively with Prof. Günther Zeck's research group and international partners including Dr. Shelley Fried (Harvard) and Prof. Daniel Palanker (Stanford). His team specializes in computational modeling of neural interfaces, with current work focusing on optimizing stimulation parameters for next-generation retinal and cochlear implants through detailed biophysical simulations.

• Aeroacoustics
• Computational Fluid Dynamics
• Acoustic Resonance
• +3 more

Stefan Schoder is an Associate Professor at the Institute of Fundamentals and Theory in Electrical Engineering, Graz University of Technology. His research focuses on aeroacoustics, fluid dynamics, acoustic resonance, and noise control, with applications in aerospace, automotive, and biomedical engineering. He employs advanced computational methods like Finite Element Analysis and the Discontinuous Galerkin method to model complex fluid-acoustic interactions. Schoder's work spans experimental and theoretical investigations of sound generation, turbulence, and vibroacoustic phenomena. Key projects include optimizing low-pressure axial fans, analyzing wind noise in medical devices, and developing digital twins for prosthetics. His publications emphasize predictive modeling of acoustics in industrial and environmental contexts. He has received multiple scientific awards, including the Weihnachtspreisaufgabe (Christmas Prize Competition) in 2015, 2016, 2018, and 2020. Schoder collaborates internationally, contributing to projects like bioCOMP4acoustics (recyclable sound-absorbing composites) and ECHODA (energy-efficient cooling).

• Sound Generation
• Knee Prosthesis
• Simulation Model
• +4 more

Andreas Wurzinger is a researcher at the Institute of Fundamentals and Theory in Electrical Engineering at Graz University of Technology. His work spans acoustics, biomedical engineering, and computational methods. PhD Student, Graz University of Technology (current) Research focuses on sound generation , knee prosthesis acoustics , and physics-informed neural networks . He develops digital twins for noise analysis in mechanical and medical systems, including refrigerant compressors and hydraulic prostheses. Recent publications highlight applications of computational aeroacoustics , flow-induced sound modeling , and data-driven frameworks like pyCFS-data. Collaborations span automotive and medical device industries . He actively participates in conferences like NOVEM 2025, Forum Acusticum 2025, and DAS/DAGA 2025, presenting on vibro-acoustic emissions and digital twin applications .

• Cognitive Rehabilitation
• Prosthetics and Assistive Technology
• Neurological Rehabilitation
• +3 more

Helen Lindner is a Senior Lecturer in Occupational Therapy at Örebro University (Sweden), with academic qualifications including BSc Pharmacology (University College London), MSc Medical Informatics (University of London), BSc Occupational Therapy (Örebro University), and a PhD in Medical Sciences (Örebro University). She specializes in cognitive rehabilitation for patients with mild-to-severe cognitive impairments and conducts clinical work at Region Örebro County's Adult Habilitation Centre, focusing on autism spectrum disorders. Her primary research areas involve cognitive function analysis in individuals with multiple disabilities and the learning processes associated with multifunctional prosthetic hands. She employs eye-tracking technology and motion analysis to study attention, visuospatial skills, and cognitive load. Key collaborations include projects with Kobe Gakuin University (Japan), Harvard Medical School (USA), and the University of Cambridge (UK). Notable research contributions include studies on prosthetic hand usability, the ACMC assessment tool, and the integration of eye-tracking into clinical practice. Her work has been presented at global conferences such as the World Congress of Occupational Therapists (Paris, 2022) and the International Conference on Music Perception and Cognition (2021). Lindner coordinates a BSc course on occupational therapy for patients with cognitive/psychiatric/neurodevelopmental disorders and teaches pharmacology's role in occupational therapy interventions. She is affiliated with the WellCET research group focused on wellbeing promotion through care environments and technologies.

Daniel SieberView profile

Lecturer

• Medical Technology
• Health Technologies
• Surgical Simulation
• +6 more

Dr. Daniel Sieber serves as Head of the Department and Study Programs in Medical, Health, and Sports Technologies at MCI | The Entrepreneurial School®. He holds a Dr. rer. biol. hum. (Summa Cum Laude) from Hannover Medical School and a Dipl.-Ing. in Mechanical Engineering (Biomedical Engineering) from the University of Stuttgart. His academic roles include full-time lecturer and researcher with a clinical-medical focus. Research Interests: Dr. Sieber specializes in medical technologies, particularly focusing on surgical simulation using virtual reality (VR), cochlear implant innovation, minimally invasive surgery techniques, and 3D printing applications in healthcare. His work bridges engineering and medicine, emphasizing translational research and interdisciplinary education. Teaching & Leadership: He leads courses in Medical Technologies, Product Development, and Implantable Devices at MCI. Recent activities include visiting professorships in Shenzhen, China, and supervising over 20 bachelor's and master's theses in medical device engineering and surgical training technologies. Key Awards: 2023 MCI Teaching Award Patents: Includes designs for cochlear implant electrodes and surgical tools Networks: Member of Tyrol's Life Sciences Cluster Advisory Board Grants & Labs: His research has driven partnerships with institutions like Hannover Medical School and MED-EL GmbH. Active in developing VR surgical training platforms and digital twins for healthcare systems.

• Prosthesis Engineering
• Orthosis
• Additive Manufacturing
• +5 more

Sophie Bauernfeind is a researcher at the University of Applied Sciences Hagenberg, affiliated with the Research Center Hagenberg and AIST Center of Excellence Medical Engineering/TIMed Center. Her work bridges information and communications technology with medical engineering, focusing on orthopedic solutions through digital innovation. Her research interests center on prosthetic and orthotic engineering , leveraging additive manufacturing and adaptive modeling to create patient-specific medical devices. She specializes in applying automated processes to orthopedic aids, with particular emphasis on shoe insoles and foot biomechanics , integrating clinical knowledge with digital workflows for enhanced patient outcomes. Recent publications reveal a strong trend toward AI-driven orthopedic solutions , with 80% of her 2023-2025 work focusing on digital customization of orthotic devices. Key themes include patient-specific 3D printing applications (Industry 4.0), clinical knowledge extraction from medical records, and AI-powered diagnostic systems for orthopedics, reflecting a strategic shift toward data-driven medical device development. As Co-Investigator for the MOVE project (Modeling Orthoses for Vitality Enhancement, 2023-2024), she contributed to research advancing orthosis customization through additive manufacturing. Her collaborations span clinical partners and engineering teams, focusing on translating research into practical orthopedic solutions. She actively participates in conferences like ICECCME 2023, demonstrating engagement with the international biomedical engineering community. Her laboratory work centers on the AIST Center of Excellence Medical Engineering/TIMed Center, where she utilizes advanced prototyping facilities for orthopedic device development. Current activities involve integrating clinical data systems with manufacturing pipelines to streamline production of personalized orthotics, with future work likely expanding into real-time biomechanical monitoring systems.