Martin Garwicz is a Professor of Neurophysiology and Course Director at Lund University, serving as Centre Director of the Neuronano Research Center (NRC) and the Birgit Rausing Centre for Medical Humanities (BRCMH). His research focuses on cerebellar information processing, human evolution, and medical education. He has contributed to understanding developmental milestones like walking onset in mammals and the impact of carnivory on human evolution. His work intersects neuroscience, evolutionary biology, and healthcare education, emphasizing evidence-based practices. Key affiliations include the NRC and BRCMH, where he leads interdisciplinary projects on topics like existential resilience and healthscapes. Garwicz has organized major events like Neuroscience Day 2025 and contributed to initiatives promoting STEM education. His research spans over 65 publications, with recent work addressing medical student training in evidence-based medicine and cerebellar microcircuit dynamics. He coordinates projects such as 'Evolutionary Roots of Human Development' (2008–present) and 'ERiCi: Existential Resilience,' blending scientific and humanities perspectives. Garwicz’s activities include invited lectures on medical humanities and public talks on topics like digital immortality.
Johanna Virkki is an Associate Professor at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences, Tampere University. Her research focuses on smart textiles, wearable technologies, RFID systems, and their applications in healthcare, assistive communication, and human-computer interaction. She has pioneered projects integrating RFID into clothing and environments for control interfaces, physiological monitoring, and gamified therapies. Key research areas include: Development of e-textiles for AAC (Augmentative and Alternative Communication) RFID-based wearable and furniture interfaces for accessibility Sensor systems for healthcare monitoring and rehabilitation Smart spaces and IoT-enabled environments Her work emphasizes interdisciplinary collaboration, with notable contributions in: Passive RFID sensor platforms for moisture, strain, and physiological signals Co-design approaches involving speech therapists, engineers, and end-users Prototyping wearable devices for children with disabilities and elderly care Recent publications highlight advancements in: Smart furniture and textile-based AAC solutions AI-driven smart spaces and edge-cloud computing Bio-inspired sensors using animal hair and conductive yarns Johanna's research bridges technology and human needs, addressing challenges in healthcare, education, and accessibility through innovative textile and RFID systems.
Adam C. Puche, PhD, is a tenured Professor and Vice Chair of the Department of Anatomy and Neurobiology at the University of Maryland School of Medicine. His laboratory investigates olfactory system development, neural circuitry, and function using neuroanatomical, electrophysiological, and advanced imaging techniques. He directs the medical school course Structure and Development , covering gross anatomy, histology, and embryology. Education: Ph.D. in Anatomy and Cell Biology, University of Melbourne (Australia) Post-doctoral training at University of Maryland with Dr. Michael T. Shipley Research Focus: Dr. Puche's work examines: (1) Embryonic/postnatal olfactory system development; (2) Neurogenesis and migration of olfactory interneurons via the rostral migratory stream; (3) Synaptic processing in glomerular microcircuits; (4) In vivo neural activity mapping using calcium imaging and electrophysiology; (5) Clinical applications in trauma training and neurodegenerative diseases. Publication Trends (2019-2025): His recent articles demonstrate strong foci on olfactory bulb neural dynamics, cortical signaling pathways, innovative surgical training models (VR/cadaveric), fluorescence imaging techniques, and neuropathology of brain injury. Computational approaches like AI-based medical imaging analysis are emerging themes. Laboratory: The lab employs multidisciplinary approaches including whole-cell patch clamping, two-photon microscopy, molecular biology, and behavioral assays to study neural circuit mechanisms in rodent models.
Professor Jim Harkin serves as Head of the School of Computing, Engineering and Intelligent Systems at Ulster University's Magee Campus in Derry~Londonderry. He is a prominent member of the Computational Neuroscience and Neuromorphic Engineering team within the Intelligent Systems Research Centre (ISRC), where he leads cutting-edge research bridging biological neural processes with hardware implementations. Harkin's research focuses on developing intelligent embedded systems capable of self-repair under error conditions, drawing inspiration from neural network models. His work explores how computer models of neural networks can be mapped to hardware to build highly efficient and reliable embedded computers. Key innovations include Networks-on-Chip strategies and hardware implementation of self-repairing Spiking Neural Networks. His research spans multiple domains including fault tolerance, neuromorphic computing, and AI hardware acceleration, with applications in healthcare, structural monitoring, and energy systems. Analysis of his recent publications reveals a strong trend toward practical applications of neuromorphic computing, particularly in healthcare monitoring systems, structural health assessment, and energy-efficient computing. His work shows increasing integration of spiking neural networks with real-world hardware implementations, demonstrating a clear trajectory from theoretical models to deployable systems with commercial applications. Harkin has received numerous scientific accolades including the Life and Health Startup Company of the Year 2019 from InventNI Ulster Distinguished Learning Support Fellowship Multiple awards for innovative routing strategies in neural network hardware implementations Professor Harkin has secured significant research funding exceeding £3.5 million from diverse sources including EPSRC, MRC, Innovate UK, HSC R&D, InvestNI, and DEL. His grant portfolio demonstrates strong industry and healthcare sector engagement, particularly through his co-founded startup Respiratory Analytics which focuses on medical analytics. He has supervised numerous research students and has been instrumental in Ulster University's Computer Science submissions to major research assessment exercises including RAE 2008, REF2014, and REF2021. As Head of School and leader within the Intelligent Systems Research Centre, Harkin oversees multiple research teams focusing on computational neuroscience, neuromorphic engineering, and intelligent embedded systems. His lab has developed specialized FPGA-based platforms for simulating and implementing self-repairing neural networks, including the AstroByte multi-FPGA architecture for accelerated simulations of fault-tolerant spiking astrocyte-neuron networks.
Florent Haiss is a researcher at the Institut Pasteur in Paris, France, where he leads a research group within the Neural Circuit Dynamics and Decision Making team under the Physics of Biological Function unit. His work is centered on understanding how cortical microcircuits process sensory information and contribute to perception, learning, and decision-making in behaving animals. His research interests lie at the intersection of systems neuroscience, neurophysiology, and behavioral neuroscience, with a strong emphasis on sensory systems—particularly the somatosensory and visual systems. He investigates how neuronal networks interact during cognitive tasks, using advanced methods such as two- and three-photon imaging, optogenetics, intracellular patch-clamp recordings, multi-electrode arrays, and psychophysics in rodent models. The trends in his recent publications indicate a focus on neural coding in the barrel cortex, including how state, choice, and sensory inputs are co-represented. His work also explores autonomic correlates of cognition (e.g., pupillary responses), neural adaptation, and the development of novel neuroimaging tools and neural interfaces. His methodological innovations support long-term, in vivo investigations of neural dynamics. Functional and Structural Properties of Highly Responsive Somatosensory Neurons in Mouse Barrel Cortex Coexistence of state, choice, and sensory integration coding in barrel cortex LII/III Pupillary dilations reflect task engagement and confidence in mice Design of ultra-flexible two-photon microscopes for in vivo use Reorganization of cortical activity during sensory deprivation Florent Haiss mentors early-career researchers, including PhD students and postdoctoral fellows such as Ervan Achirou, indicating an active and productive research group. He has not received any explicitly mentioned scientific awards in the provided texts. His research is supported by institutional affiliations and collaborative networks at the Institut Pasteur, particularly within transversal programs involving quantitative biology and artificial intelligence in biomedical research. He is involved in the development of advanced technologies for neuroscience, including flexible microscopes and large-scale electrode arrays for retinal stimulation, reflecting a strong engineering and translational component in his work. His team collaborates across disciplines, integrating computational modeling with experimental neuroscience.
Mark J. Schnitzer is the Anne T. and Robert M. Bass Professor at Stanford University, with primary faculty appointments in the Departments of Biology, Applied Physics, and Neurosurgery within the School of Humanities and Sciences . He co-directs Stanford's Cracking the Neural Code Program and holds affiliations with the Bio-X , Wu Tsai Neurosciences Institute , and multiple graduate programs. Research focuses on neural circuit dynamics and optical imaging innovations for studying learning, memory, and motor behaviors in awake animals Develops high-resolution fluorescence microscopes and miniaturized imaging systems for clinical translation Scientific contributions include: 2019 Nature Methods Method of the Year for miniature fluorescence microscope HHMI Investigator (2008) NIH Director's Pioneer Award (2007) Allen Distinguished Investigator Award (2010) Teaching roles include: Advanced Imaging Lab in Biophysics (APPPHYS 232/BIO 132) Introduction to Biophysics (APPPHYS 205/BIO 126) Multiple independent study and graduate research courses Laboratory affiliations span biomedical engineering , neuroscience , and molecular imaging initiatives at Stanford.
Niels Tas is an Associate Professor at the University of Twente, Faculty of Science and Technology, Department of Chemical Engineering, leading the Mesoscale Chemical Systems (MCS) group since 2014. He obtained his MSc (1995) and PhD (2000) in Electrical Engineering, focusing on micro-hydraulics and electrostatic micromotors. His research spans MEMS, NEMS, and Lab-on-a-Chip technologies, emphasizing 3D nanofabrication techniques via corner lithography, anisotropic etching, and convex corner processing. Applications include energy harvesting, biomedical devices (e.g., U-Needle microneedles), chemical analysis, and multi-parameter sensing. 3D nanostructures for mechanical, fluidic, optical, and magnetic domains Capillarity and elasto-capillarity in nanochannels Acoustic resonators and flow sensors Electrochemical sensing with patterned electrodes Recent publications highlight his work on fractal substrates for super-resolution imaging, SERS-active nanostructures, and silicon nanowedge fabrication. He has received awards such as the 2025 Best Poster and 2024 EIPBN Best Journal Paper Award.
Alexander Kozlov is a Researcher at KTH Royal Institute of Technology's Division of Computational Science and Technology. His work focuses on computational neuroscience, particularly modeling neural networks and locomotor control systems. He has contributed to understanding spinal cord networks, striatal connectivity, and neuromodulation mechanisms through in silico studies. Kozlov teaches courses in machine learning, artificial neural networks, and mathematical modeling of biological systems. His research integrates AI frameworks with biological data, emphasizing GPU-accelerated simulations and large-scale microcircuit analysis. Key contributions include studies on Parkinson's disease impact on neural connectivity and the role of sensory feedback in locomotion. He collaborates with the Science for Life Laboratory in Stockholm and maintains active roles in both peer-reviewed and conference publications. Education background and affiliations are not explicitly detailed in the provided text, but his extensive publication record reflects a deep engagement with interdisciplinary neuroscience and computational biology. Awards or grants are not listed here.
Prof. Dr. Simon Jacob is a leading researcher in translational neurotechnology at the Technische Universität München . As head of the Translational NeuroTechnology Laboratory and associate member of multiple neuroscience networks, he bridges rodent models with human neurosurgical research to unravel cognitive mechanisms. Board-certified neurologist Director of preclinical and clinical BCI research His research focuses on Neuronal basis of higher cognition Dopamine's role in executive function Neuromodulation of mental health using advanced methods like optogenetics , multi-scale neuroimaging , and computational modeling . Recent scientific publications reveal groundbreaking insights into Prefrontal cortex organization Striatal dopamine signaling Neuronal distraction filtering with implications for brain-computer interfaces and cognitive disorders. Recognized with a prestigious ERC Consolidator Grant , he mentors a diverse team of students spanning medicine, psychology, and AI. His teaching includes courses on neuroanatomy, cognitive neuroscience, and translational approaches to psychiatric disorders at TUM's elite programs.
Prof. Dr. Benjamin Grewe is an Associate Professor at the Department of Information Technology and Electrical Engineering at ETH Zürich. His research focuses on the intersection of artificial intelligence, neuroscience, and neural networks, with a particular emphasis on cortical hierarchies, continual learning, and biologically plausible algorithms. He leads projects involving deep feedback control, synaptic connectivity analysis, and neural ensemble dynamics. Grewe teaches courses such as Learning in Deep Artificial and Biological Neuronal Networks and Reinforcement Learning Basics , integrating theoretical and applied perspectives. His work bridges computational models with biological insights, contributing to advancements in medical robotics, process control, and AI safety. His research interests span neural network architectures , continual learning , and biological neuronal systems . Recent projects explore synaptic plasticity in cortical microcircuits and the application of AI to surgical planning and industrial automation. Grewe’s publications reflect a multidisciplinary approach, addressing challenges in both technical and biological domains. No scientific awards are explicitly mentioned in the provided texts. His advising and grant activities remain unspecified in the available data. His lab, part of the Neural and Intelligent Systems group, focuses on developing biologically inspired algorithms and neural interfaces.
Kun Yang is Chair Professor at the University of Essex, UK, leading the Network Convergence Laboratory (NCL) and Communications and Networks Research Group since 2003. He has held academic roles at Essex since 2003, including Lecturer (2003-2008), Reader (2008-2011), and Chair Professor (2011-present). Fields: Internet of Things, wireless networks, data-energy integrated communication networks, and 6G technologies Labs: Founder of the Network Convergence Laboratory (2008) International Collaborations: Affiliated Professor at UESTC (China), active in EU FP7/H2020 projects His research focuses on energy self-sustainability in communication systems through energy efficiency and harvesting via resource allocation and joint optimization. Experimental work is conducted in his NCL laboratory. Recent publications span neuroscience-inspired AI, including neural sampling, cognitive maps, spiking neural networks, and secure machine learning architectures. These works intersect with Computer Science , Neuroscience , and Artificial Intelligence . 2025: Neural sampling for cognitive modeling 2024: High-dimensional prediction-learning 2023: Sparsity in forward-forward algorithms Professional Recognition: Fellow of IEEE, IET, BCS, HEA, and RSA IEEE ComSoc Distinguished Lecturer (2020-2021) Judicial role: GSMA GLOMO Awards Judge (2019-present) Research Leadership: Essex Principal Investigator in over 10 EU FP7/H2020 projects Founder of IEEE InterCloud Testbed Executive Committee
Ed Walsh is an Associate Professor of Engineering Science at the University of Oxford , affiliated with the Oxford Thermofluids Institute and a Fellow of Brasenose College . His research spans heat transfer, fluid mechanics, and energy reduction, with applications in microfluidics , thermal management , and biotechnology . Key Research Areas : Boundary layer studies, fluid-walled microfluidics, energy-efficient data center infrastructure, and cancer metastasis modeling. Recent Work : Focuses on pool boiling heat transfer, microfluidic platforms for human neuron studies, and fluid dynamics in cancer cell heterogeneity. Collaborations : Partnerships with Hewlett Packard on data center energy efficiency and innovations in fluid-walled systems for biomedical applications. Scientific Awards : Fellow of Brasenose College Publications highlight a blend of thermal engineering (e.g., pin-fin structures, Novec 649 cooling) and biotech microfluidics (e.g., fluid-walled platforms for neuron circuits and cancer studies). His work bridges fluid dynamics and energy systems , with applications in data centers and biomedical devices .
Cliff Summers is a Professor in the Department of Biology at the University of South Dakota, where he maintains an active research laboratory focused on stress physiology and behavioral neuroscience. His work bridges molecular, neural, and endocrine mechanisms to understand adaptive behaviors related to stress, social interactions, and mental health disorders. He directs the Stress-Alternatives Model laboratory and has established himself as a leading researcher in neurobiological stress responses. Dr. Summers' educational background includes: Ph D in Endocrinology from the University of Colorado (1987) MA in Reproductive Biology from the University of Colorado (1982) BS in Wildlife Biology from Colorado State University (1978) Professor Summers' research program investigates how social and environmental stressors impact molecular, neural, and endocrine responses that influence adaptive behaviors including learning, coping strategies, social rank relationships, biological rhythms, reproduction, and social interaction. His laboratory has developed innovative models like the Stress Alternatives Model (SAM) to study aggression, learned escape, and conditioned submission. A key focus is understanding individual differences in stress responses and how experience modulates neural and hormonal stress reactivity. His work bridges molecular genetics, physiology, and anatomy with behavior, ecology, and evolution, providing a comprehensive framework for understanding stress adaptation. Analysis of his recent publications reveals a strong emphasis on orexin signaling pathways in stress regulation, with significant work on how orexin receptors in the amygdala and hippocampus modulate anxiety and depression-related behaviors. His research increasingly incorporates psychedelic compounds as potential therapeutic interventions and examines transgenerational and developmental aspects of stress responses. The work spans from molecular mechanisms to behavioral outcomes, maintaining a strong comparative perspective across species. Dr. Summers has received numerous prestigious awards including: Harrington Lecture, College of Arts and Sciences, University of South Dakota (2021) President's Award for Excellence in Research - Established Faculty, University of South Dakota (2021) Nolop Distinguished Professor, University of South Dakota (2020) Keith Bradley Nolop Professor, University of South Dakota (2019) Fellow, International Behavioral Neuroscience Society (2013) Multiple Belbas-Larson Awards for Excellence in Teaching (2012, 1995) Professor Summers has successfully secured substantial research funding from the National Institutes of Health and National Science Foundation, with current projects focusing on orexin stress signaling, designer receptor activation for mental health treatment, and amygdalar modulation of affective disorders. His laboratory has mentored numerous students who have gone on to become prominent researchers in behavioral neuroscience, with many serving as first authors on high-impact publications. Current research directions include exploring psychedelic therapeutics for stress-related disorders and investigating neural circuitry underlying stress resilience. The Summers laboratory operates the Stress-Alternatives Model facility and collaborates extensively with the Center for Brain and Behavioral Research at USD. His team includes postdoctoral researchers, graduate students, and undergraduate researchers working across multiple model systems including rodents, fish, and reptiles to understand conserved mechanisms of stress response. The laboratory maintains strong connections with the International Behavioral Neuroscience Society and participates in multi-institutional research consortia focused on mental health research.
Nikolay Karmanovsky is an Associate Professor at the Faculty of Secure Information Technologies of ITMO University. He has spent his entire career at the university since graduating in 1974, progressing from an assistant to his current role. He earned a PhD in Engineering from ITMO University in 1982. Research Interests: Microelectronics, Optoelectronics, Integrated Microcircuits Design, and Information Security. Teaching: Digital Computational Tools, Fundamentals of Radio Engineering, and Organizational Information Security. Editorial Role: Deputy Editor-in-Chief of the Scientific and Technical Journal of Information Technologies, Mechanics and Optics since 2008. Awards: Honorary Worker of Higher Education in Russia.
Geoffrey Ghose, PhD is a Professor in the Department of Neuroscience at the University of Minnesota Medical School. His research focuses on understanding the neural mechanisms underlying perception, attention, and sensory processing in the brain. He employs advanced neuroimaging techniques like fMRI and electrophysiological recordings in combination with computational modeling to investigate how sensory information is processed across cortical hierarchies. Key research themes include the role of alpha oscillations in visual processing, the impact of attention on auditory and visual cortex activity, and the optimization of neuroimaging methodologies. His work bridges basic neuroscience with translational applications in neurotechnology and perceptual learning strategies. He has pioneered techniques for analyzing task-dependent cortical activity profiles and refining fMRI sensitivity without sacrificing spatiotemporal precision. Recent investigations explore the interplay between top-down microcircuitry and perceptual decision-making, as well as the neurophysiological bases of perceptual ambiguity resolution. His studies utilize both human and non-human primate models, with a particular focus on visual and auditory cortical areas such as V4, MT, and auditory cortex regions. Ghose's contributions have advanced understanding of how neural synchrony and microcircuit dynamics shape sensory perception and cognitive functions.
