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Christian EngwerView profile

Professor

• Partial Differential Equations
• Numerical Analysis
• Finite Element Methods
• +7 more

Christian Engwer is a full Professor at the University of Muenster in the Institute for Applied Mathematics, specializing in Analysis and Numerics. He leads the Engwer Group focused on Applications of Partial Differential Equations and is actively involved in the Cells in Motion initiative as a supervisor in the CiM-IMPRS Graduate Programme. His research centers on developing numerical methods for partial differential equations, particularly addressing challenges in complex geometries and multi-physics applications. He specializes in Unfitted Discontinuous Galerkin methods, which allow simulations on complex geometries without requiring domain-fitted meshes. His work spans porous media modeling, biological systems, and bioelectromagnetism applications, with significant contributions to EEG/MEG forward modeling in neuroscience. Analysis of his recent publications reveals a strong focus on model order reduction techniques, stabilized numerical schemes for cut-cell meshes, and applications in bioelectromagnetism. His work demonstrates a consistent trajectory toward developing robust, efficient numerical methods applicable to real-world problems in medical imaging and biological modeling, with increasing emphasis on high-performance computing implementations. Professor Engwer actively supervises doctoral students, with recent completions including Lukas Renelt (2025), Michael Wenske (2021), and Maria Carla Piastra (2019), among others working on topics related to numerical methods and biomedical applications. He leads several major research projects including BrainStorm: Highly Extensible Software for Advanced Electrophysiology and MEG/EEG Imaging (NIH-funded since 2019), multiple EXC 2044 Cluster of Excellence projects through 2025, and the InterKI interdisciplinary teaching program on machine learning and artificial intelligence. His group develops several important software packages including DUNE (Distributed and Unified Numerics Environment), duneuro (for bioelectromagnetism applications), and TPMC (Topology Preserving Marching Cubes). These tools support research in numerical methods and their applications to complex scientific problems.

• Hyperdimensional Computing
• Neuromorphic Hardware
• In-Memory Computing
• +3 more

Paul R. Genssler is a Dr.-Ing. researcher at the Chair of AI Processor Design (AI-Pro) within the Technical University of Munich (TUM), actively advancing hardware solutions for artificial intelligence under Prof. Hussam Amrouch. His work bridges computer engineering and emerging technologies, focusing on overcoming fundamental limitations in conventional computing architectures through brain-inspired paradigms. His research spans critical domains in next-generation computing: Hyperdimensional Computing for robust pattern recognition and bioinformatics applications Neuromorphic and In-Memory Computing architectures for energy efficiency Reliability engineering for emerging memory technologies (FeFET, etc.) Quantum computing support systems including cryogenic embedded electronics Machine learning-driven transistor aging prediction and mitigation Analysis of his 15 most recent publications (2023-2024) reveals a dominant trend toward hyperdimensional computing as a unifying framework for addressing reliability challenges in emerging technologies. His work consistently integrates in-memory computing techniques to bypass von Neumann bottlenecks while targeting real-world applications like genome matching and unsupervised learning. A significant portion focuses on error-resilient implementations for unreliable nanoscale devices, demonstrating exceptional cross-stack expertise from transistor physics to algorithm design. As a core member of TUM's AI Processor Design group affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI), Genssler collaborates extensively on projects spanning cryogenic quantum control systems, FPGA-based AI resilience, and monolithic 3D integration. The team operates at the intersection of semiconductor physics, computer architecture, and machine learning, with strong industry connections evident through publications at DATE, ASP-DAC, and ICCAD.

• Neural coding
• Spatial navigation
• Memory systems
• +4 more

Dr. Eric T. Reifenstein is a neuroscience researcher at Humboldt-Universität zu Berlin's Faculty of Life Sciences, Institute of Biology, specializing in neural mechanisms of spatial navigation and memory. As a key contributor to SFB 1315 (Entorhinal Cortex as Interface between Memory and Space), his work bridges computational modeling and human electrophysiology. His research focuses on egocentric spatial mapping and sequence learning mechanisms , with particular expertise in human single-neuron recordings during virtual navigation tasks. Reifenstein investigates how the brain encodes self-centered spatial representations and how synaptic learning rules enable temporal sequence memorization. His publication trends reveal a strong emphasis on translational neuroscience , connecting rodent studies to human cognition through innovative virtual reality paradigms. Key methodological approaches include single-neuron recordings, computational modeling of neural networks, and behavioral analysis of spatial memory. Scientific contributions include: Identification of egocentric bearing cells in human parahippocampal cortex Mathematical analysis of phase precession in sequence learning Vectorial representation models of egocentric space Reifenstein actively collaborates with leading researchers including Prof. Richard Kempter and Joshua Jacobs, contributing to major neuroscience journals like Neuron and eLife. His work has implications for understanding memory disorders and developing neural prosthetics.

Matthias KrauledatView profile

Professor

• Machine Learning
• Brain-Computer Interface
• Signal Processing
• +3 more

Prof. Dr. Matthias Krauledat is a faculty member at Hochschule Rhein-Waal , specifically within the Faculty of Technology and Bionics . His academic career spans both theoretical research and industrial application, with a focus on Machine Learning and Brain-Computer Interfaces . After completing his PhD in Electrical Engineering/Computer Science at Technische Universität Berlin , he has contributed significantly to the advancement of EEG-based communication systems and neural signal processing methodologies. Born in Essen, Germany Studied Mathematics with a minor in Computer Science at University of Münster/Oxford Doctoral research at TU Berlin on Brain-Computer Interfaces Industrial experience at Henkel AG & DMT GmbH Research Interests focus on Machine Learning applications in Neuroscience and Biomedical Engineering , specifically Brain-Computer Interfaces , EEG Signal Processing , and Adaptive Classification Systems . His work explores how algorithms can be developed to enable self-learning computers to solve complex tasks involving neural data interpretation and prediction for previously unseen data in clinical and technological contexts. Publications demonstrate a consistent contribution to Neuroscience and Machine Learning fields, with particular emphasis on Brain-Computer Interface systems from 2004 through 2009. His research has focused on reducing training requirements, improving signal processing accuracy, and developing novel interaction paradigms like the Hex-o-Spell mental typewriter while addressing statistical challenges like covariate shift in neural data analysis. Professional Experience includes academic research at TU Berlin's Intelligent Data Analysis group, industrial software development roles at Henkel AG's Scientific Computing department, and TÜV Nord Group's Optical Metrology and Machine Diagnostics divisions. He maintains active research connections through collaborative publications with leading experts in the field.

• Pediatric Oncology
• Cancer-Related Fatigue
• Cognitive Impairments
• +3 more

Dr. Anna-Maria Platschek is an academic staff member at the Institute of Movement and Neurosciences (German Sport University Cologne). Her research focuses on cancer-related fatigue , cognitive impairments , and exercise interventions for pediatric oncology patients. She collaborates extensively with institutions like the Institute of Cardiology and Sports Medicine and researchers including Thomas Abel , Saskia Henckert , and Hans-Georg Predel . Awards : Outstanding Trainee Research Award (MASCC Fatigue Study Group, 2019) Multiple Reisestipendium awards (2013–2022) Projects : ExerBrain Study (2024–2027) MORE! Move & Relax! (2020–2023) ChiMove (2016–2020) Her work bridges neuroscience and sports medicine , aiming to improve quality of life for children undergoing cancer therapy through tailored physical interventions.

• Nanotechnology
• Materials Science
• Memristive Systems
• +3 more

Dr.-Ing Alexander Vahl is a Researcher at the Technical Faculty of Kiel University, leading the subgroup Nanoparticles for Nanocomposites . He specializes in advanced materials science, focusing on nanoparticle synthesis, functional thin films, and neuromorphic engineering. His research bridges nanotechnology with applications in memristive systems and plasmonics, emphasizing strain-invariant conductors and photocatalytic growth mechanisms. Key projects include developing self-assembled nano-object networks for brain-inspired computing and optimizing gas aggregation cluster sources for novel material fabrication. His work spans disciplines such as memristive switching, plasmonic metasurfaces, and bio-inspired electronics. Notable contributions include studies on silver/polymer nanofluids, ITO-TiO₂ heterojunctions, and multicomponent nanoparticle synthesis. Vahl collaborates with the Chair for Functional Nanotechnology, leveraging interdisciplinary expertise to advance materials innovation. His articles highlight advancements in neuromorphic systems, photocatalytic deposition, and thin-film technologies. The research emphasizes scalability and real-world applications, such as energy-efficient sensors and hybrid zinc batteries. Vahl’s subgroup webpage and extensive publications reflect a commitment to pushing boundaries in nanomaterials engineering.

• Computational Neuroscience
• Visual System
• Sensory Coding
• +7 more

Thomas Wachtler-Kulla is a Professor in the Department of Biology II at Ludwig-Maximilians-University Munich, where he leads the Computational Neuroscience research group. He is a GSN full member and serves as the GSN Ombudsperson, offering neutral and confidential counseling for students. He is also the Group Leader and Scientific Director at the German Neuroinformatics Node (G-Node), contributing significantly to neuroscience data infrastructure. His research focuses on how the brain processes sensory signals, particularly in the visual system, aiming to understand neural coding, perceptual stability, and color vision under natural conditions. He employs neurophysiology, psychophysics, and computational modeling to investigate sensory processing, eye movement compensation, and efficient coding mechanisms. At G-Node, he develops software and hardware tools for organizing, storing, analyzing, and sharing neurophysiological data, promoting reproducible research. His recent work spans Bayesian models of hue perception, data management frameworks like DataLad and odML, and studies on honeybee neuroethology. He actively supervises graduate students and contributes to major initiatives such as NFDI-Neuro and the International Neuroinformatics Coordinating Facility, advancing standards for open and FAIR neuroscience. Scientific Contributions and Leadership: Scientific Director, German Neuroinformatics Node (G-Node) GSN Ombudsperson for student conflict resolution Key contributor to NFDI-Neuro and INCF Developer of tools for metadata management and data sharing He advises several current and former graduate students and is deeply involved in shaping data policies and infrastructure for the neuroscience community, ensuring scientific rigor and accessibility.

Surjo R. SoekadarView profile

Professor

• Clinical Neurotechnology
• Brain-Computer Interfaces (BCI)
• Neuromodulation
• +8 more

Surjo R. Soekadar is the Einstein Professor of Clinical Neurotechnology at Charité – University Medicine Berlin. He leads the Clinical Neurotechnology Laboratory , which focuses on developing noninvasive neurotechnologies for treating neurological and psychiatric disorders through closed-loop brain stimulation and advanced brain-machine interfaces (BCI/BMI). His work integrates real-time EEG/MEG monitoring with electromagnetic stimulation to modulate pathological brain oscillations and enhance neuroplasticity in conditions like stroke, spinal cord injury, and psychiatric disorders. Education : Studied medicine in Mainz, Heidelberg, and Baltimore Clinical Training : Residency in Psychiatry and Psychotherapy at University of Tübingen Academic Journey : 2008-2011 Research Fellow at NINDS (USA); 2017 Venia Legendi at University of Tübingen; 2018 First Professor of Clinical Neurotechnology in Germany His research interests span: • Closed-loop neurostimulation combining real-time brain state monitoring with targeted intervention • Next-generation BCI using optically pumped magnetometers (OPM) for mobile MEG recordings • Neurorehabilitation through exoskeleton control and sensory feedback • Neurophysiological modeling of entropy measures and phase flows Recent publications highlight: • Adaptive deep brain stimulation protocols • Real-time phase-sensitive tACS applications • OPM-based BCI innovations • Stroke recovery mechanisms through corticospinal tract analysis Scientific recognition includes: International BCI Research Award BIOMAG Award NARSAD Young Investigator Award Funded by the European Research Council (ERC) , his lab trains doctoral students like David Haslacher (EEG/MEG integration), Khaled Nasr (multicoil TMS optimization), and Annalisa Colucci (entropy-driven BCI development). The team also explores quantum AI applications in clinical decision-making and bidirectional BCI systems using OPM and tES.

Julia MierauView profile

Researcher

• Electroencephalography
• Cognitive Performance
• Exercise Psychology
• +7 more

Dr. Julia Mierau is a researcher at the Institute of Movement and Neuroscience, German Sport University Cologne. She is actively involved in projects related to digitalization in sports teacher education, cognitive performance, and exercise neuroscience. Her work bridges pedagogy and neuroscience, with a strong focus on EEG, motor performance, and digital learning tools. Institution: German Sport University Cologne Department: Institute of Movement and Neuroscience Email: j.mierau@dshs-koeln.de Phone: +49 221 4982-8613 Her research interests include electroencephalography, cognitive performance, exercise psychology, sports pedagogy, and digital media in education. She investigates how physical activity influences brain function and learning, particularly in educational contexts. The recent publications reflect a strong trend in digital innovation in sports education, EEG-based monitoring of exercise effects, and cognitive performance in athletes and children. Her work combines experimental neuroscience with practical pedagogical applications. Scientific Awards: ECSS Young Investigators Award (2011) Fellowship for Digital Higher Education Innovation (2019) Graduiertenstipendium (2007) Reisestipendium (2011, 2014) Dr. Mierau has been principal or co-investigator in multiple externally funded projects, including ComeSport, ComeIn, and S.P.O.R.T.S., focusing on digital competence development in teacher training. She also served as co-editor of the Journal for Study and Teaching in Sports Science in 2021 and 2022, demonstrating academic leadership. She collaborates extensively with researchers such as Jens Kleinert, Heiko Strüder, and Andreas Mierau, contributing to a robust network in sports neuroscience and pedagogy.

Kai EssigView profile

Professor

• Human Factors
• Interactive Systems
• Eye Tracking
• +15 more

Prof. Dr. Kai Essig is a Professor of Human Factors and Interactive Systems at the Faculty of Communication and Environment, Rhine-Waal University of Applied Sciences, Kamp-Lintfort, Germany. He has a strong interdisciplinary background combining computer science, cognitive science, and human-computer interaction, with a focus on eye tracking, visual perception, and assistive technologies. Master of Science in Computer Science and Chemistry, Bielefeld University (1998) Ph.D. in Computer Science, Bielefeld University (2007) His research centers on eye tracking, human-computer interaction, usability engineering, visual attention, and cognitive interaction technology . He investigates how movement expertise influences visual perception and how multimodal software can support real-time human actions. His work integrates computer vision, machine learning, and neuroscience to develop intelligent systems that adapt to user behavior. The 15 most recent publications reflect a consistent trend in eye movement analysis, mental representations, brain-machine interfaces, and assistive technologies . These works span domains such as sports psychology, robotics, augmented reality, and cognitive neuroscience, demonstrating a strong interdisciplinary approach. Key themes include gaze-based interaction, automated annotation of visual behavior, and the implementation of smart systems for daily living assistance. Scientific recognition includes: Landmark in the Land of Ideas (2018) – for the ADAMAAS project, awarded by 'Land of Ideas', a joint initiative of the German government and the Federation of German Industries Prof. Essig has been actively involved in research projects such as ADAMAAS (Adaptive and Mobile Action Assistance in Daily Living Activities), which received national recognition. He has collaborated extensively with the Neurocognition and Action-Biomechanics Research Group at Bielefeld University and the Excellence Cluster CITEC. While no formal advising of students is listed, his publications suggest mentorship and collaboration with junior researchers. His lab work is centered on eye-tracking systems, multimodal interaction, and cognitive modeling , particularly within applied environments like smart glasses and assistive technologies.

Matthias SchlesewskyView profile

Professor

• Neurobiology of Language
• Cognitive Neuroscience
• Language Processing
• +3 more

Prof. Matthias Schlesewsky is a Professor of Psychology at the University of South Australia. Previously, he held positions as Professor of General Linguistics at the University of Mainz and as a Junior Professor at the University of Marburg. With a unique background in chemistry and a PhD in linguistics, he specializes in interdisciplinary research at the intersection of science and humanities. His research focuses on the neurobiological foundations of language and how language processing evolves across the lifespan. Key interests include sentence comprehension mechanisms, cross-linguistic neurocognitive models, and the interplay between auditory processing and language evolution. Prof. Schlesewsky’s work integrates experimental methods like EEG and eye-tracking to explore real-time language processing. His contributions have advanced understanding of linguistic universals and neural mechanisms underlying language.

Markus KnauffView profile

Professor

• High-level cognition
• Reasoning
• Decision-making
• +7 more

Markus Knauff is a Professor at the Justus Liebig University Giessen in the Department of Experimental Psychology and Cognitive Science. His research focuses on high-level cognition, including reasoning, decision-making, and rationality, as well as spatial cognition and mental imagery in cognitive processes. Dipl.-Psych., University of Bochum, 1991 Dr. phil., University of Freiburg, 1996 Habilitation, University of Freiburg, 2002 His work integrates cognitive science, psychology, and artificial intelligence, emphasizing mental models and belief revision. He explores how counterexamples, probabilities, and spatial reasoning influence human cognition, with applications in navigation and decision-making. While his publications span deductive reasoning, belief dynamics, and spatial mental models, his recent studies highlight probabilistic reasoning in the brain and rationality frameworks. Markus leads the Giessen virtual environment laboratory, focusing on human wayfinding and landmark salience. He contributes to interdisciplinary projects like the SPP1516 "New Frameworks of Rationality" and has mentored researchers in cognitive systems, though specific student names are not listed in the provided texts.

Sandra Diaz PierView profile

Researcher

• Computational Neuroscience
• High Performance Computing
• Machine Learning
• +3 more

Dr. Sandra Diaz Pier is a Scientific Lead at the Jülich Supercomputing Centre (JSC) within the Jülich Research Centre , Germany. Specializing in computational neuroscience , high performance computing (HPC) , and machine learning , she bridges neuroscience and advanced computational methods through her research. Education: B.Sc. in Electronic Systems Engineering, Mexico M.Sc. in Computer Science (focus: machine learning, quantum computing), Mexico Second M.Sc. in Electrical Engineering, Ontario, Canada Ph.D. in Computer Science, Germany (2021) Her research focuses on modeling and simulating brain dynamics and plasticity at multiple scales, leveraging HPC to accelerate large-scale neural network simulations. She actively contributes to EU projects like the Human Brain Project (HBP) , Virtual Brain Cloud , and EBRAINS 2.0 , emphasizing infrastructure development and educational training. Her work includes open-source tools such as the NEST simulator , The Virtual Brain , and L2L , enabling efficient parameter exploration and multiscale co-simulation frameworks. The 15 most recent publications highlight her interdisciplinary approach, spanning topics from quantum computing in biomolecular simulations to neural plasticity algorithms and cloud-based brain modeling . These articles reflect her expertise in integrating machine learning , multi-scale simulation , and HPC infrastructure for neuroscience challenges, including seizure propagation, Parkinson’s disease progression, and swarm intelligence in spiking networks. She leads technical coordination in projects like EBRAINS and serves as a task leader in the HBP infrastructure work package , while also organizing workshops and hackathons for open-source tools. Her role involves supporting domain scientists through methodological research and workflow optimization for brain simulations.

Gordon ChengView profile

Professor

• Neuroengineering
• Robotics
• NeuroRobotics
• +1 more

Professor Gordon Cheng is a faculty member at the Technical University of Munich (TUM), affiliated with the School of Computation, Information and Technology (CIT). He serves as the Director of the Chair of Cognitive Systems at the Institute for Cognitive Systems (ICS), where he focuses on advancing cognitive systems, robotics, and their intersections. His research addresses fundamental challenges in creating intelligent systems capable of understanding and interacting with complex environments. Research Interests: His work spans Neuroengineering , Robotics , and Cognitive Systems , emphasizing the integration of biological principles into artificial systems. Key projects include robot skin development , EEG-based prosthetic control , and human-robot co-adaptation . Selected Publications: Recent articles highlight advancements in real-time tactile sensing , neuroprosthetics , and BCI-driven rehabilitation , reflecting his interdisciplinary approach bridging robotics and neuroscience. Supervision: He supervises PhD students from the Graduate School of Neuroscience (GSN), including Jasmin Kajopoulos and Nikolas Berberich. Contact: Email: gordon@tum.de | Website

• Neuroscience
• Cognitive Neuroscience
• Neural Oscillations
• +3 more

Ole Jensen is a Professor at the School of Psychology, University of Birmingham, affiliated with the Department of Psychology since September 2016. His research spans neuroscience, cognitive science, and theoretical models of consciousness. Research Interests: Dr. Jensen focuses on neural oscillations, brain-computer interfaces, and the neural mechanisms underlying language processing and consciousness. His work employs neuroimaging techniques like MEG and explores theories such as Global Neuronal Workspace (GNW) and Integrated Information Theory (IIT). Recent Publications: His recent projects include the OPM FLUX TOOLKIT (2025), preregistration files for the Cogitate project (2022), and adversarial collaborations testing models of consciousness (2019–2021). These studies emphasize computational neuroscience, reproducibility, and theoretical frameworks.