Prof. Dr. med. Andreas K. Engel serves as Director of the Institute of Neurophysiology and Pathophysiology at the Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf (UKE). His research focuses on neural oscillations, brain dynamics, and neurophysiological mechanisms in health and disease, particularly employing EEG, MEG, and brain stimulation techniques like tACS to study cognitive processes, motor control, and multisensory integration. Current affiliation: Institute of Neurophysiology and Pathophysiology, UKE Academic rank: Professor Email: ak.engel@uke.de Key research areas include: Neural oscillations and synchronization Neurodegenerative disease mechanisms (Parkinson's) Brain-computer interface development Neural coupling during social interactions Cortical network dynamics Neuromodulation techniques Recent publications demonstrate expertise in analyzing multisensory integration, phase-amplitude coupling, and applying stimulation methods to modulate cortical activity patterns. His work bridges computational neuroscience with clinical applications in movement disorders and cognitive impairments.
Tamir Gonen is a Professor of Biological Chemistry and Physiology at the David Geffen School of Medicine, University of California, Los Angeles (UCLA) , and an Investigator at the Howard Hughes Medical Institute (HHMI) . He is a pioneer in microcrystal electron diffraction (MicroED) , a transformative cryo-EM method for atomic-resolution structure determination. Education: Doctor of Science (DSc), University of Auckland (2025) PhD in Structural Biology, Harvard Medical School (2005) PhD in Biochemistry, University of Auckland (2002) BSc (Hons) in Inorganic Chemistry and Biochemistry, University of Auckland (1998) His research focuses on membrane protein structure and function , particularly those in the blood-brain barrier , using MicroED, X-ray crystallography, NMR, and molecular dynamics. He has determined structures of ion channels, transporters, and drug compounds at resolutions better than 1 Å, advancing drug discovery and understanding disease mechanisms. Recent work includes high-throughput MicroED for ion channel dynamics, energy filtering to enhance resolution, and polymorphic drug characterization . His lab also develops protocols for suspended drop crystallization and focused ion-beam milling of samples. Scientific Awards: Fellow, American Crystallographic Association (2025) Doctor of Science, University of Auckland (2025) Carl Branden Award, The Protein Society (2024) Investigator, HHMI (2017) Member, Royal Society of New Zealand (2017) American Diabetes Association Career Development Award (2009) He leads the Gonen Lab , which emphasizes multidisciplinary approaches and method development in structural biology. His trainees have become faculty at top global institutions, extending his impact on the field.
Dr. Stamos Katsigiannis is an Associate Professor in the Department of Computer Science at Durham University. His research focuses on bioinformatics, health informatics, affective computing, and GPU computing. He holds a BSc, MSc, and PhD in Computer Science from the University of Athens and the Athens University of Economics and Business. Before Durham, he was a Postdoctoral Research Fellow and Lecturer at the University of the West of Scotland (2016–2020). His work spans biometric identification via EEG signals, medical image analysis, and deep learning applications in healthcare. Education: BSc (Hons.) in Informatics and Telecommunications from National and Kapodistrian University of Athens MSc in Computer Science from Athens University of Economics and Business PhD in Computer Science from National and Kapodistrian University of Athens Research interests include bioinformatics (e.g., microarray analysis), health informatics (e.g., ECG-based emotion modeling), and GPU computing for real-time applications. He has pioneered studies on EEG-based biometrics and affect recognition in human-horse interaction. Recent articles explore chest X-ray classification using deep learning , AI-generated content detection , and trajectory prediction with graph networks . His research emphasizes interdisciplinary applications of machine learning in healthcare and education. He advises six postgraduate students and collaborates on UK parliamentary AI governance reports. Notable contributions include the BED EEG dataset and the DREAMER emotion recognition database.
Dr. Stamos Katsigiannis is an Associate Professor in the Department of Computer Science at Durham University. His research focuses on bioinformatics, health informatics, affective computing, machine learning, and GPU computing applications. He holds a PhD in Computer Science from the National and Kapodistrian University of Athens (Greece), with prior roles including Postdoctoral Research Fellow and Lecturer at the University of the West of Scotland (2016-2020). Education: BSc (Hons) Informatics and Telecommunications, National and Kapodistrian University of Athens (Greece) MSc Computer Science, Athens University of Economics and Business (Greece) PhD Computer Science, National and Kapodistrian University of Athens (Greece) Research Interests: Bioinformatics, health informatics, affective computing (e.g., emotion recognition using EEG/ECG signals), machine learning applications in medical imaging and video quality, GPU-accelerated algorithms for biomedical data analysis, and biometric identification systems. His work bridges computational methods with healthcare, education technologies, and human-computer interaction. Advising & Students: Supervising postgraduate students in AI-driven healthcare, computer vision, and affective computing. Recent collaborations include projects on AI-generated content detection (De-Factify 4.0), chest X-ray image analysis (CLN network), and trajectory prediction using graph neural networks. Labs/Teams: Active in Durham's AI research groups, contributing to interdisciplinary projects in medical imaging, cybersecurity, and educational technology. Collaborates internationally in EU-funded initiatives and UK parliamentary AI governance consultations (AGENCY project).
Matthew A. Smith is a Professor in the Department of Biomedical Engineering and the Carnegie Mellon Neuroscience Institute, where he serves as Co-Director of the Center for the Neural Basis of Cognition. His research bridges computational and experimental neuroscience to understand visual perception, cognition, and motor control. Dr. Smith's research focuses on neural engineering, visual perception, cognition, eye movements, and neural circuits . His laboratory investigates how groups of neurons interact to construct visual perception and translate it into cognitive processes and motor outputs. The lab employs a multi-scale approach combining single-neuron electrophysiology with global signals like EEG and near-infrared imaging, examining both normal and disease states of the brain. Analysis of his recent publications reveals strong trends in brain stimulation optimization (e.g., MiSO/OMiSO frameworks), neural population dynamics during cognitive tasks, visual cortex plasticity , and non-invasive neurotechnology development. His work spans fundamental neuroscience questions about working memory and perception while developing practical tools for brain monitoring and intervention. NIH K99/R00 Pathway to Independence Award Research to Prevent Blindness Career Development Award Dr. Smith has secured substantial funding from NIH, NSF, Research to Prevent Blindness, Schaffer Foundation for Glaucoma Research, and Hillman Foundation to support his research program. His laboratory actively develops novel methodologies for neural recording and stimulation while investigating fundamental mechanisms of visual processing and cognition. The lab maintains strong collaborative ties within Carnegie Mellon's neuroscience ecosystem through the Center for the Neural Basis of Cognition.
Senem Velipasalar is a Professor in the Department of Electrical Engineering and Computer Science (EECS) at Syracuse University, affiliated with the Smart Vision Systems Laboratory and the Aging Studies Institute. She holds a Ph.D. and M.A. from Princeton University, an M.S. from Brown University, and a B.S. from Bogazici University. Her research focuses on machine learning, computer vision, and wireless smart camera systems, with applications in human activity classification, driver behavior analysis, and defense against adversarial attacks. Her honors include the NSF CAREER Award (2011), 2021 IEEE Technological Innovation Award, and multiple doctoral prizes for her advisees. She leads grants totaling over $4M, including ARPA-E projects on occupancy detection and DOE-funded research on aerial energy modeling. Research interests span embedded vision, distributed multi-camera tracking, and energy-efficient algorithms. Her lab develops technologies like wearable camera-based fall detection and autonomous UAV navigation. Notable publications include works on adversarial attacks, fNIRS brain activity analysis, and thermal pedestrian detection.
Krishna V. Shenoy is the Hong Seh and Vivian W. M. Lim Professor of Engineering at Stanford University, an Investigator at the Howard Hughes Medical Institute (HHMI), and Director of the Neural Prosthetic Systems Laboratory (NPSL). He also co-directs the Neural Prosthetics Translational Laboratory (NPTL) and serves on scientific advisory boards for institutions like the University of Washington’s Center for Sensorimotor Neural Engineering and companies such as CTRL-Labs Inc., MIND-X Inc., and Heal Inc. Research Interests Shenoy’s work bridges neuroscience and neuroengineering. His neuroscience research explores the neural basis of movement preparation and generation using electrophysiological, behavioral, computational, and theoretical approaches. His neuroengineering focus centers on developing high-performance neural prosthetic systems (brain-machine interfaces) to restore function for individuals with paralysis. Scientific Awards Burroughs Wellcome Fund Career Award in the Biomedical Sciences McKnight Technological Innovations in Neurosciences Award NIH Director’s Pioneer Award 2010 Stanford Postdoc Mentoring Award Alfred P. Sloan Fellowship AIMBE Fellow The Andrew Carnegie Prize in Mind and Brain Sciences (2018) Labs & Collaborations Shenoy leads the Neural Prosthetic Systems Laboratory (NPSL) and co-directs the Neural Prosthetics Translational Laboratory (NPTL), emphasizing translational research to bridge basic science and clinical applications.
Stefan Ehrlich is a Researcher at the Institute for Cognitive Systems (ICS) at the Technical University of Munich (TUM). His work focuses on neuroengineering, particularly non-invasive brain-computer interfaces (BCI) for human-robot interaction (HRI), neuroadaptive systems, and EEG-based neurotechnology. He collaborates closely with Prof. Gordon Cheng and contributes to projects involving error-related potentials (ErrPs), affective neurofeedback, and neuroprosthetics. His research integrates cognitive neuroscience principles with robotics to enhance human-machine collaboration and adaptive systems. Key research areas include: Development of passive BCI systems for real-time robotic adaptation Design of co-adaptive human-agent interfaces using neural signals EEG-based assessment of exoskeleton and humanoid robot performance Neuroimaging techniques for music-brain interactions His publications emphasize interdisciplinary approaches, combining neuromorphic engineering, machine learning, and social robotics. Ongoing work explores low-power neuromorphic hardware for EEG decoding and neurophysiological mechanisms underlying human-robot trust dynamics. Collaborations involve institutions like the Bernstein Center for Computational Neuroscience and industry partners in wearable robotics. Labs/Teams: Active contributor to the EEG Laboratory and projects like the Soft Wearable Robotics initiative. Engages in international conferences (IROS, IEEE EMBC) and co-organizes workshops on HRI and neurotechnology.
Nandini Sidnal serves as Senior Learning Facilitator and National Academic Course Coordinator for Torrens University's Master of Software Engineering program through the Centre for Artificial Intelligence Research and Optimisation (AIRO). With over 20 years of international teaching experience in Computer Science, Engineering, and Networking, she has established herself as a key academic figure in AI and blockchain applications. Her educational foundation includes: PhD in Computer Science and Engineering (Cognitive Computing using Intelligent Agents) from Visvesvaraya Technological University (2012) M.Tech in Computer Science and Engineering (Parallel and Distributed Computing using Intelligent Mobile Agents) (2003) Bachelor of Engineering (1993) Nandini's research spans Artificial Intelligence, Blockchain Security, and Cognitive Computing , with strong emphasis on practical implementations in agriculture and healthcare. Her work integrates intelligent agents with distributed systems to solve real-world problems like food supply chain security and medical diagnostics, demonstrating consistent innovation from her early best paper award-winning thesis to current cutting-edge applications. Recent publications reveal a pronounced trend toward AI-driven agricultural optimization (dairy quality, aeroponics, nut farming) and healthcare diagnostics (epilepsy detection), alongside critical work in edge security. These outputs consistently bridge theoretical frameworks with tangible industry solutions, particularly in blockchain-secured IoT systems and deep learning applications. Her scientific recognition includes: Best Paper Award at an international conference for distributed computing research Nandini actively mentors high-impact projects including 'Strengthening Mobile-Based Services for Agriculture' and 'Enhancing VANET Performance with Cloud and Edge Technology.' Her industry collaborations with Intel (Parallel Programming integration) and Nokia (Mobility Research Lab establishment in Finland) demonstrate exceptional academic-industry synergy. The AIRO Centre serves as her primary research hub where she guides PhD candidates in blockchain-secured agri-supply chains and semantic recommender systems. Her Mobility Research Lab in Finland remains a cornerstone of her practical innovation legacy, focusing on next-generation mobile application development that continues to influence current VANET and edge computing research directions.
Silvestro Micera is a Professor specializing in Bioelectronics and Neural Engineering. His research focuses on neural interfaces, neurorehabilitation, and biomedical robotics. He explores applications of machine learning in healthcare and develops wearable robotic systems for mobility assistance. Notable projects include stroke recovery prediction using neural signals and soft wearable robots for shoulder movement support. His work bridges materials science with clinical applications through innovations like conductive hydrogel electrodes. Research interests span neural prosthetics, neuromodulation, and neuroethology in primate models. Recent studies address facial asymmetry classification in neurological disorders and vagal-cardiac neuromodulation. His interdisciplinary approach integrates robotics, materials science, and machine learning to advance neural engineering solutions. Publications highlight trends in neurorehabilitation technologies, implantable devices, and animal model studies. Ongoing work explores brain-to-body neural bypass systems using manifold-based control algorithms.
Erkin Şeker, Ph.D. , is a Professor in the Department of Electrical and Computer Engineering at the University of California, Davis, where he also serves as Co-Director of the Center for Neuroengineering and Medicine and Chair of the Designated Emphasis in Neuroengineering . His research integrates micro- and nanofabrication, electrochemical biosensors, multifunctional neural interfaces, and microfluidic tissue chips to address challenges in healthcare and life-science miniaturization. Education: Ph.D. in Electrical Engineering, University of Virginia (2007) Research Interests Prof. Şeker’s group operates at the intersection of nanoporous metals , microfluidics , and device engineering . Current thrusts include: Nanostructured electrochemical biosensors for nucleic-acid detection in food safety, water quality, and medical diagnostics. Multifunctional biomedical device coatings that combine neural recording with on-demand drug delivery to combat epilepsy and other neurological disorders. Nanoporous metal morphology libraries for high-throughput investigation of structure–property relationships. Microphysiological models of neuroinflammation and gut–brain-axis interactions using tri-culture tissue chips. Publication Trends Over the past decade the group has produced >80 peer-reviewed articles spanning Analytical Chemistry , ACS Applied Materials & Interfaces , Advanced Functional Materials , Lab on a Chip , and Journal of Neuroinflammation . The work reveals a clear trajectory from fundamental studies of nanoporous gold mechanics and surface chemistry to translational applications in closed-loop neural control, nucleic-acid diagnostics, and tissue-level disease models. Scientific Awards & Honors NSF CAREER Award NIH NIBIB Trailblazer Award UC Davis Academic Senate Distinguished Graduate and Professional Teaching Award UC Davis Graduate Studies Distinguished Graduate and Postdoctoral Mentorship Award BMES Cellular & Molecular Bioengineering Young Innovator Next Level Research Award (College of Engineering) Fund for Medical Discovery Award (Massachusetts General Hospital) Elevation to IEEE Senior Member Advising & Funding Prof. Şeker has mentored >25 Ph.D. and M.S. students and numerous undergraduates. Active funding includes NSF, NIH (NIBIB, NINDS, NIA, NCCIH), USDA-NIFA, UC Lab Fees, and industry partnerships totaling several million dollars. He is PI or Co-PI on grants such as: "NeuralStorm: Taking Neuroengineering by Storm" (NSF NRT) "Closed-Loop Electro-Fermentation…" (USDA-NIFA) "Next-Generation Neural Interfaces Based on Axonal Confinement…" (NIH NIBIB Trailblazer) "A Scalable Primary Cortical Tri-Culture Model…" (NIH R03) Labs & Teams He directs the Şeker Research Group , a multidisciplinary team of graduate students, post-docs, and undergraduates housed in the UC Davis College of Engineering. Shared resources include College clean-room facilities, the Center for Neuroengineering and Medicine, and collaborative ties with the UC Davis Alzheimer’s Disease Research Center, Comprehensive Cancer Center, and Environmental Health Sciences Center.
Jessica Ng is a Research Fellow at Princeton University affiliated with the High Meadows Environmental Institute (HMEI). Her primary research focuses on extractivism and the energy transition, particularly examining lithium mining and decolonial climate justice frameworks. She explores just transition strategies rooted in land and labor movements, bridging environmental humanities, earth history, and energy engineering disciplines. Her academic work combines environmental policy analysis with technical investigations into sustainable resource management. Though her current HMEI affiliation emphasizes socio-environmental research, her scholarly outputs include significant contributions to insect olfactory neuroscience, reflecting prior research on mosquito host-seeking mechanisms and odor coding systems. Ng holds a Princeton University email address (jn0090@princeton.edu). Her publications span both environmental humanities and biological research, demonstrating interdisciplinary engagement. While no specific awards or grants are listed, her dual focus areas indicate active participation in both climate justice advocacy and life sciences research. Her work uniquely connects ecological systems analysis with social justice frameworks, offering critical perspectives on resource extraction's socio-environmental impacts. Though no formal student advisement is recorded, her research teams likely engage graduate students in these interdisciplinary projects.
Professor Hugues MOUNIER is affiliated with Paris Saclay University and the Laboratoire des Signaux et Systèmes (L2S) at CentraleSupélec. His primary role is as a Professor leading the COMEDY team, focusing on control systems and their applications. He has been a permanent member of L2S since 2010 and joined Paris Saclay University in 2008. His research spans theoretical and applied domains: differential flatness (for nonlinear and infinite-dimensional systems), Liouvillian systems, controllability/observability properties, and applications in contemplative neuroscience, physiological systems, and engineering systems like drilling, automotive, and network control. He leads the ANR project MindMadeClear, integrating mathematical models for meditation practices with physiological and phenomenological analysis. Key contributions include modeling oilwell drilling vibrations, model-free control strategies for vehicles and data centers, and neuroscientific studies using EEG classification for meditation states. His work bridges abstract theory (e.g., flatness analysis for HPA axes) with real-world applications (e.g., congestion control, energy management). He collaborates internationally, presenting at venues like ECC, IFAC, and IEEE conferences. His lab teams include SYCOMORE and MODESTY, focusing on dynamical systems modeling and estimation. No awards are explicitly listed, but his extensive peer-reviewed publications reflect sustained academic impact.
Rachel June Smith is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Alabama at Birmingham (UAB), affiliated with the Neuroengineering Program. She joined UAB in August 2022. Her research focuses on biomedical signal processing, dynamical network models, neuroengineering, and brain-computer interfaces. Education: B.S. in Biomedical Engineering from the University of Tennessee, Knoxville; M.S. and Ph.D. in Biomedical Engineering from the University of California, Irvine. Completed postdoctoral training at Johns Hopkins University under Dr. Sridevi Sarma. Research emphasizes developing computational metrics for EEG analysis in neurodegenerative disorders, leveraging dynamical systems and control theory. Highlights include work on seizure onset localization using intracranial EEG and therapeutic response prediction in infantile spasms. Labs: Director of the Neural Signal Processing and Modeling Lab, collaborating with neurologists to advance clinical applications of computational neuroscience methods.
Professor Fred Charles serves as Head of Department for Creative Technology at Bournemouth University, specializing in computational intelligence applied to simulated worlds. His expertise spans artificial intelligence, human-computer interaction, and interactive narrative systems, with significant contributions to virtual reality and brain-computer interface technologies. His research has led to award-winning interactive systems and numerous publications in top-tier conferences and journals. Education: PhD in Computer Science ("Intelligent Virtual Actors in Interactive Storytelling") Master's degree in Computer Aided Graphical Technology Applications BSc in Computer Science Professor Charles' research focuses on the intersection of AI, narrative systems, and immersive technologies. His work explores how computational intelligence can enhance virtual environments, particularly through brain-computer interfaces that enable more natural human-virtual agent interactions. Recent projects investigate social anxiety in VR settings, multimodal interaction frameworks, and personalized dialogue systems for virtual characters. His research bridges theoretical AI concepts with practical applications in healthcare, education, and entertainment domains. His most recent publications demonstrate a clear trend toward applying interactive narrative techniques to real-world problems, particularly in mental health assessment (OCD, social anxiety), responsible gambling initiatives, and educational applications. The work increasingly incorporates multimodal input analysis and neurofeedback mechanisms to create more responsive and adaptive virtual experiences. Scientific Awards: Blue Sky Award (ACM Hypertext, 2018) Best Application (International Conference on Automated Planning and Scheduling, 2013) Professor Charles has successfully supervised numerous PhD students working on topics ranging from crowd simulation to narrative generation systems. His research has been supported by substantial grants from Innovate UK, Economic and Social Research Council, AHRC/EPSRC, and the European Commission, including projects on believable agent behavior in VR, responsible online gambling, and machine understanding for interactive storytelling. He maintains active collaborations with researchers across Europe and has contributed significantly to the development of narrative medicine applications.
