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Richard NaudView profile

Assistant Professor

• Computational Neuroscience
• Neural Coding
• Statistical Methods in Neuroscience
• +5 more

Richard Naud is an Assistant Professor in the Department of Cellular and Molecular Medicine at the Faculty of Medicine, University of Ottawa, with a cross-appointment in Physics at the Faculty of Science. He holds dual research positions at the Center for Neural Dynamics (CND) and Brain and Mind Research Institute (BMRI), focusing on computational approaches to decode neural signaling mechanisms and develop brain-machine interfaces. His educational background includes: PhD in Neuroscience from École Polytechnique Fédérale de Lausanne (EPFL), 2011 MSc in Physics from McGill University, 2006 BSc in Physics from McGill University, 2004 Dr. Naud's research investigates how neurons encode information through spikes, bursts, and silences using mathematical models and statistical analysis of electrophysiology data. His lab develops computational protocols for synaptic dynamics analysis, studies dendritic computation in neurological diseases, and creates neuromorphic algorithms for spiking neural networks. Current work emphasizes serotonin system dynamics, burst coding mechanisms, and neural network simulations for demyelinating conditions. Analysis of his recent publications reveals three dominant research vectors: (1) Burst coding as an independent information channel beyond firing rates, (2) Serotonin-mediated value coding in decision systems, and (3) Neuromorphic implementation of biologically plausible learning rules. His work bridges theoretical neuroscience with clinical applications in stroke recovery and neurological disorders. Dr. Naud leads the Neural Coding Lab, which actively recruits postdoctoral fellows, graduate students, and undergraduates for projects in neural coding theory, computational psychiatry, and neuromorphic engineering. The lab maintains collaborations with experimental neuroscience groups for model validation and develops open-source tools like SRPlasticity for synaptic dynamics analysis.

John H. MaceView profile

Professor

• Autobiographical Memory
• Involuntary Memory
• Cognitive Psychology
• +3 more

John H. Mace serves as Professor and Chair of the Psychology Department at Eastern Illinois University, concurrently holding a professorship in Aging Studies (Gerontology). Based in Klehm Hall, Charleston, his contact email is jhmace@eiu.edu. His research centers on autobiographical memory systems , specifically: Involuntary vs. voluntary memory recall mechanisms Organization principles of autobiographical memories Semantic-to-autobiographical priming under varied conditions (non-verbal cues, subliminal stimuli, cue repetition) Functional purpose of involuntary memories Methodological innovations in diary-based memory research Recent publications (2023-2024) demonstrate rigorous experimental approaches examining how semantic cues trigger autobiographical memories, revealing critical insights about memory accessibility thresholds and unconscious processing. His work bridges cognitive psychology with consciousness studies through innovative paradigms like vigilance tasks and subliminal stimulation protocols. Dr. Mace maintains active teaching responsibilities for Cognitive Psychology and Human Memory courses while leading departmental operations. His public profile includes media recognition as the 82-year-old Boston Marathon qualifier in 2020, featured across eight media outlets including The Boston Globe .

• Quantum Computing
• Atomic Physics
• Quantum Information Science
• +3 more

Jacob Paul Covey serves as an Assistant Professor in the Department of Physics and the Materials Research Lab at the University of Illinois Urbana-Champaign. His academic role involves conducting cutting-edge research in quantum information science and mentoring students in atomic physics and quantum computing. Research interests span quantum computing, atomic physics, quantum information science, quantum simulation, Rydberg atoms, and optical lattices. Covey specializes in neutral-atom platforms using ytterbium-171 for quantum information processing, investigating Dicke superradiance, quantum walks, and flat-band physics in Rydberg lattices to overcome scalability challenges in quantum computers. Analysis of recent publications reveals a concentrated focus on neutral-atom quantum computing architectures. Key contributions include two-qubit encoding schemes for ytterbium atoms, quantum network designs with atom processing nodes, and studies of correlated dynamics in synthetic Rydberg lattices, advancing qubit connectivity, error correction, and quantum simulation capabilities. Dr. Covey has received prestigious recognition: NSF CAREER Award (2024) ONR Young Investigator Award (2022) U.S. DOE Early Career Research Program Award (2024) While specific students aren't listed in the provided text, his active research program funded by major federal grants supports graduate students and postdoctoral researchers. These NSF, ONR, and DOE grants provide substantial resources for experimental quantum computing development. Prof. Covey's laboratory operates within the Materials Research Lab, an interdisciplinary research center at UIUC. His team collaborates extensively with quantum information and atomic physics experts, as evidenced by multi-institutional co-authorships, focusing on ytterbium-based quantum processors and many-body quantum phenomena.

Ben Ward-CherrierView profile

Senior Lecturer

• Robotics
• Computational Neuroscience
• Prosthetics
• +2 more

Ben Ward-Cherrier is a Senior Lecturer in Robotics at the University of Bristol's School of Engineering Mathematics and Technology. His research focuses on biomimetic tactile sensing, neuromorphic systems for robotics, and haptic interfaces. He develops artificial tactile systems inspired by biological sensory mechanisms for applications in prosthetics, robotic manipulation, and human-robot interaction. Key research areas include neuromorphic tactile sensors that mimic biological afferents, real-time texture and edge classification algorithms, incipient slip detection for stable grasping, and vibrotactile feedback systems. Recent work integrates spiking neural networks with tactile hardware for efficient sensory processing. Publications demonstrate advancement in tactile sensing capabilities, including braille recognition in noisy environments, psychophysics-inspired benchmarking, multi-modal texture/velocity classification, and industrial applications like composite defect detection. Research bridges computational neuroscience with practical robotic systems.

• Chemical Engineering
• Materials Science
• Nanotechnology
• +3 more

Prof. Robert Grass is a Lecturer at the Department of Chemistry and Applied Biosciences at ETH Zurich, affiliated with the Institute for Chemical and Bioengineering Sciences. His research focuses on innovative applications of nanotechnology, DNA-based storage systems, and sustainable catalytic processes for CO2 valorization. Grass has pioneered silica-encapsulated DNA technologies for traceability in healthcare, environmental monitoring, and anti-counterfeiting measures. His work bridges chemical engineering with information technology, addressing challenges in long-term data preservation and molecular-level security. Current projects include developing compostable DNA storage materials and designing catalysts for methanol synthesis from CO2, contributing to both environmental sustainability and energy systems. Grass's interdisciplinary approach integrates nanomaterials design, enzymatic processes, and machine learning to advance next-generation storage and sensing technologies. Research Interests: Development of DNA-based storage systems with error-correction mechanisms Nanoparticle engineering for medical and environmental applications Catalytic materials for CO2 conversion and green chemistry Bio-inspired security systems using molecular randomness Sustainable materials for long-term data preservation His recent work highlights advancements in silica-encapsulated DNA tracers for tracking pathogen transmission dynamics, as well as low-nuclearity catalysts enabling efficient methanol synthesis from CO2. Grass actively explores the intersection of nanotechnology and digital information, including cryptographic applications leveraging DNA's inherent complexity.

• Quality of Experience
• Video Quality Assessment
• Augmented Reality
• +7 more

Kjell Brunnström serves as an Adjunct Professor in the Department of Computer and Electrical Engineering (DET) at Mid Sweden University, based in Sundsvall. He maintains active affiliation with the STC Research Centre, contributing to cutting-edge research in multimedia quality assessment and immersive technologies through extensive international collaborations. His research centers on Quality of Experience (QoE) with specialized focus on 3D video systems , virtual reality environments , and augmented teleoperation interfaces . He pioneers methodologies for subjective and objective video quality evaluation, particularly examining human factors in sports broadcasting (Video Assistant Referee systems), mining applications, and automotive displays. His work bridges theoretical psychophysical models with industrial implementations through standards development like ITU-T Rec. P.919. Analysis of his 15 most recent publications reveals consistent investigation into latency effects, distortion impacts, and viewing condition variables across emerging media formats. Key application domains include sports video refereeing, 360-degree video systems, VR simulators for remote machinery control, and adaptive streaming protocols, demonstrating strong industry-academia translation. Scientific Awards: No awards documented in source material. Advising and Grants: Student supervision and grant funding details were not disclosed in available documentation. Labs and Teams: Brunnström operates within Mid Sweden University's STC Research Centre framework, collaborating with global institutions including Royal Institute of Technology (Sweden), University of Surrey (UK), and multiple European research consortia. His work directly informs ITU standardization efforts and industrial implementations in broadcast and automotive sectors.

Tillman WeydeView profile

Academic

• Machine Learning
• Signal Processing
• Data Analysis
• +5 more

Dr. Tillman Weyde is a Reader in the Department of Computer Science at City, University of London , where he has been employed since 2021. He leads the Machine Intelligence and Media Informatics Research Group and is a member of the Machine Learning Group . Prior to this, he served as Senior Lecturer (2009–2021) and Lecturer (2005–2009) at City, and worked as a researcher at the University of Osnabrück (2001–2005), coordinating the MUSITECH project. His academic background includes PhD in Music Technology (2002), MSc in Computer Science (1999), and MSc in Mathematics, Music, Philosophy & Pedagogy (1994), all from the University of Osnabrück. Research Focus: Machine learning and signal processing methods for data analysis with applications in finance, audio, NLP, music, health, security, and education. His recent work emphasizes inductive biases in neural networks for rule-learning, extrapolation, generalization, and interpretability. Grants & Projects: Principal Investigator for the AHRC-funded Digital Music Lab (2012–2017) and Integrated Audio-Symbolic Model of Music Similarity (2017–present). Co-investigator in Innovate UK and EPSRC projects on safer gambling ( Advancing Consumer Protection , 2015–2018) and Raven (2012–2021). Collaborations: Affiliated with the Institute of Cognitive Science (Osnabrück), Intelligent Systems Research Laboratory (Reading), and the MPEG Ad-Hoc Group on Symbolic Music Representation. Awards: Co-author of the 2000 Comenius Medal-winning educational software Computer Courses in Music Ear Training and co-editor of the Osnabrück Series on Music and Computation . Publications: Over 150 peer-reviewed works including conference papers, journal articles, and book chapters, focusing on interdisciplinary applications of machine learning in music, health, and finance. Students: Supervised 13 PhD students across topics like grammar bias in neural networks, emotion recognition from audio, extrapolation behavior in neural networks, relation-based patterns, legal text parsing, and more.

• Wave Physics
• Medical Imaging
• Telecommunications
• +6 more

Mathias FINK is a Professor at ESPCI Paris on the Georges Charpak chair. His research focuses on fundamental wave physics in complex media with major applications in medical imaging, telecommunications, and geophysics. He pioneered time-reversal mirrors for wave focusing and co-founded 6 technology companies. Key Institutions: ESPCI Paris, Collège de France Research Themes: Wave physics, time-reversal techniques, matrix imaging, metasurface design His work spans multi-echo wave systems , ultrasonic therapeutic devices , and adaptive electromagnetic communication systems . Recent publications emphasize 3D matrix imaging in biological tissues and space-time interface dynamics . Scientific recognition includes: First academic elected at Collège de France (2008) Over 400 peer-reviewed publications 70+ patents and 6 start-ups Collaborations extend to Institut des Hautes Études Scientifiques , Langevin Institute , and Hong Kong University of Science and Technology . His team's volcanic imaging work with seismic noise has revolutionized subterranean mapping.

Jeffrey M. ChungView profile

Associate Professor

• Epilepsy
• Neural Signal Processing
• Neurosurgery
• +4 more

Jeffrey M. Chung, MD, FAAN is an Associate Professor of Neurology at Cedars-Sinai Medical Center. He serves as Director of both the Epilepsy Program and the Neurophysiology Laboratory since 2013. His clinical practice focuses on epilepsy and neurophysiology, with 26 years of experience in neurology and clinical neurophysiology. Northwestern University Medical School (1999) - MD Evanston Hospital (2000) - Internship UCLA (2003) - Residency UCLA (2005) - Fellowship Dr. Chung's research explores epilepsy mechanisms, neural signal processing , multi-modal probabilistic mapping for surgical outcomes, and device-oriented therapies . His recent publications focus on theta phase precession in memory , single-neuron correlates of seizures , and neuroimaging in post-stroke conditions . He leads clinical trials on novel anti-seizure agents and neuromodulation techniques. Circle of Friends – Grateful Patient Donation Honoree (Cedars-Sinai) Southern California Super Doctors (Los Angeles Magazine) Falks Medical Scholar (Arthritis Foundation) Golden Apple Teaching Award (Cedars-Sinai) Dr. Chung directs the Epilepsy Program and Neurophysiology Laboratory at Cedars-Sinai, while also mentoring through journal clubs and clinical teaching. He has received multiple industry grants from companies like Marinus Pharmaceuticals and Vertex Pharmaceuticals for trials on treatment-resistant epilepsy. His work bridges clinical care with neurophysiological research and advanced neural signal processing .

• Artificial Intelligence
• Natural Language Processing
• Legal Informatics
• +5 more

Tomasz Pełech-Pilichowski serves as a Lecturer at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków. He concurrently holds dual administrative leadership positions as Director of the AGH Recruitment Center and Rector's Representative for Recruitment, demonstrating significant institutional impact beyond his academic role. His research expertise spans artificial intelligence, natural language processing, and legal informatics with methodological foundations in deep learning and time series analysis. Recent work focuses on AI-driven solutions for legal text processing (text segmentation, hypertext law), educational technology (gamification, recruitment systems), and security applications (facial-age detection, anomaly identification). His interdisciplinary approach consistently bridges computer science with law, education, and environmental science through practical implementations. Analysis of his 2023-2025 publications reveals three dominant research trajectories: legal tech innovation (68% of output featuring text segmentation and regulatory automation), educational transformation (22% including gamified AI skill development), and security/environmental systems (10% covering IoT integration and pollution prediction). This progression shows increasing specialization in AI-NLP fusion techniques applied to domain-specific challenges, particularly within legal informatics where he has developed novel text recovery and visualization frameworks.

• Quantum Optics
• Quantum Information
• Solid-State Quantum Emitters
• +2 more

Vikas Remesh is a Researcher in the Department of Experimental Physics at the University of Innsbruck, Austria, actively contributing to quantum optics and quantum information science. His work focuses on quantum emitters, particularly semiconductor quantum dots, for developing advanced quantum light sources and control techniques essential for quantum computing and secure communication. His research centers on manipulating quantum states in solid-state systems, with emphasis on chirped-pulse control, dark-state engineering, and high-dimensional entanglement. Key innovations include the SUPER excitation scheme for collective state preparation and methods for high-purity single-photon generation in 2D materials like WSe 2 . His approaches bridge theoretical models with experimental implementations to overcome coherence and stability challenges in quantum photonics. Analysis of his 15 most recent publications (2022-2025) reveals a dominant focus on quantum dot control mechanisms, particularly using chirped pulses and magnetic fields for adiabatic rapid passage. Recurring themes include single-photon source optimization for quantum cryptography, photon-number-encoded entanglement, and spectral engineering of quantum emitters. His work consistently targets practical quantum technology applications while addressing fundamental coherence limitations. No scientific awards or fellowships were documented in available sources. His research is conducted within the quantum optics group led by Univ.-Prof. Hanns-Christoph Nägerl, likely supported by institutional and national funding frameworks typical for European quantum research initiatives. Remesh operates within the University of Innsbruck's Department of Experimental Physics, part of Austria's leading quantum research ecosystem. His work intersects with the institution's strengths in ultracold atoms and quantum simulation, contributing to experimental platforms for quantum information processing and quantum communication protocols.

Blake JohnsonView profile

Associate Professor

• Cognitive Neuroscience
• Motor Control
• Neuroimaging
• +3 more

Blake Johnson is an Associate Professor and Honorary Professor at the School of Psychological Sciences, Macquarie University, affiliated with the Hearing CRC. His research focuses on brain mechanisms underlying perception, cognition, motor control, and mental imagery, utilizing advanced neuroimaging techniques like MEG and EEG. He leads projects investigating speech motor control in children with developmental disorders, such as Childhood Apraxia of Speech (CAS), and has pioneered methodologies combining MEG with speech tracking systems. Research Interests: Johnson's work spans cognitive neuroscience, neuroimaging, and developmental psychology. Key areas include speech production mechanisms, neural correlates of motor control, auditory processing abnormalities in disorders like stuttering and autism, and the application of MEG/EEG for understanding brain dynamics. His studies often integrate multimodal data to explore how neural activity coordinates with behavioral outcomes. Recent Projects: Active projects include investigating the neural origins of motor disorders in CAS (2022–2023) and developing MEG-articulography techniques for speech research (2016–2020). He collaborates internationally, focusing on brain mechanisms in speech motor control and developmental neuroplasticity. Articles Trends: His publications emphasize MEG/EEG applications in speech and motor systems, with recent work on beta-band rhythms in speech production, emotional distractor suppression, and lateralized linguistic processing. These studies highlight innovative methods for linking neural activity to behavioral and developmental outcomes. Grants & Collaborations: Leads 29 projects since 2008, including the Bio-semi EEG system (ongoing) and collaborations on childhood apraxia. His lab is part of the Hearing CRC, fostering translational research in auditory and speech neuroscience. Labs/Teams: Based at Macquarie’s School of Psychological Sciences, his team specializes in neuroimaging and developmental neuroscience, contributing to both fundamental and applied research in hearing and speech disorders.

• Control Engineering
• Networked Control Systems
• Multi-Agent Systems
• +6 more

Qinglong Han is the Pro-Vice Chancellor (Research Quality) and a Distinguished Professor at Swinburne University of Technology in Melbourne, Australia. He previously held academic and leadership roles at Griffith University and Central Queensland University. His research focuses on networked control systems, multi-agent systems, time-delay systems, smart grids, and unmanned vehicles. He is a Fellow of IEEE, IFAC, and multiple other institutions, and has received prestigious awards including the IEEE Dr.-Ing. Eugene Mittelmann Achievement Award (2024) and Norbert Wiener Award (2021). His research interests span control engineering, applied mathematics, and artificial intelligence. Notable contributions include secure platooning control for autonomous vehicles, resilient control under cyber-physical threats, and optimization of industrial systems. He leads editorial roles in journals like IEEE Transactions on Industrial Informatics and IEEE/CAA Journal of Automatica Sinica. His work emphasizes interdisciplinary applications in smart grids, robotics, and industrial automation. Dr. Han has supervised numerous PhD students in areas like networked control and vehicle dynamics. He has secured grants from ARC and NSFC for projects on networked control systems and renewable energy integration. His achievements include multiple best paper awards and recognition as a Clarivate Highly Cited Researcher in Engineering and Computer Science.

Samee U. KhanView profile

Professor

• Quantum Computing
• Edge Computing
• Fog Computing
• +4 more

Samee U. Khan is a Professor in the Department of Electrical & Computer Engineering at Mississippi State University (MSU), affiliated with the Bagley College of Engineering. He holds a Ph.D. from the University of Texas (2007) and a B.S. from GIK Institute of Engineering & Technology (1999). His research focuses on optimization, robustness, and security of computer systems, with recent emphasis on quantum computing, edge/fog computing, and machine learning applications in neuroscience and cybersecurity. Key research interests include quantum algorithm development, edge computing architectures, and neuro-inspired systems. His work integrates quantum computing with traditional machine learning to address challenges in visual perception modeling and medical imaging analysis. He also explores fog computing frameworks for IoT and distributed systems, emphasizing security and efficiency in heterogeneous environments. Publications highlight advancements in quantum noise mitigation, hybrid quantum optimization, and brain-computer interface models. His contributions span simulation toolkits like iFogSim and frameworks for vehicular networks and blockchain-based resource management. Khan’s research bridges theoretical computer science with practical applications in smart homes, healthcare, and autonomous systems.

Zhu HanView profile

Professor

• Game Theory
• Wireless Networking
• Security
• +4 more

Dr. Zhu Han is the John and Rebecca Moores Professor at the University of Houston's Cullen College of Engineering, Department of Electrical and Computer Engineering. His research focuses on game theory, wireless networking, security, data analysis, and smart grid applications. He holds doctoral and master's degrees from the University of Maryland and a bachelor's from Tsinghua University. Research interests span: Next-generation wireless systems (6G/7G) AI/ML integration in communications Reconfigurable intelligent surfaces Quantum machine learning applications Secure and efficient network architectures His recent publications demonstrate strong focus on generative AI integration in wireless systems, quantum networking, semantic communications, and security frameworks for future networks. Awards and honors include: IEEE/ACM/AAAS Fellow status IEEE Kiyo Tomiyasu Award (2021) Highly Cited Researcher since 2017 IEEE Distinguished Lecturer (2015-2018) Dr. Han leads research in wireless communications and networking, with extensive industry collaboration. His lab focuses on developing theoretical foundations and practical implementations for next-generation communication systems.