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Tim Pearce is a Reader in Bioengineering at the School of Engineering, University of Leicester. He holds a PhD from Warwick University and has served as a Research Assistant Professor at Tufts University Medical School. His work focuses on machine olfaction, neuromorphic engineering, and interdisciplinary applications of chemical sensing technologies. Key contributions include the development of electronic noses, biomimetic infochemical communication systems, and neuromorphic implementations inspired by insect olfactory pathways. Research Interests: Machine olfaction and sensor arrays Neuromorphic engineering and bio-inspired computation Integration of neuroscience principles into engineering systems Applications in environmental monitoring, healthcare, and security Publications highlight advancements in odor classification, spatio-temporal signal processing, and AI-driven world modeling. Notable collaborations include EU projects like Neuro-IT and AMOTH, which translated biological olfactory principles into real-world technologies. He has authored over 100 articles, including the seminal Handbook of Machine Olfaction . Awards include Fellowships from the Institute of Physics and the Higher Education Academy. Editorial roles span Frontiers in Neuromorphic Engineering and Connection Science . He actively contributes to global initiatives in neuroengineering and computational neuroscience.

• Machine Olfaction
• Neuromorphic Engineering
• Neuroscience
• +4 more

Gregory Jefferis is a Professor and Research Leader at the MRC Laboratory of Molecular Biology (MRC LMB), University of Cambridge, where he heads a group investigating olfactory processing in Drosophila . His work bridges neural circuitry, behaviour, and computational neuroanatomy within the Cambridge neuroscience ecosystem. Jefferis' research focuses on how odour information transforms into behaviour through higher olfactory centres, particularly examining third-order neurons in the lateral horn that integrate specific olfactory channels. His lab employs cutting-edge techniques including genetic labelling, in vivo whole-cell patch clamp recording, and high-resolution computational neuroanatomy to decode innate and learned behavioural responses to general odours and sex pheromones. Recent work demonstrates strong trends in connectome mapping and computational analysis, with 2024 publications in Nature and Cell detailing the complete adult fly brain connectome and neurotransmitter classification via machine learning. His group actively contributes to open-source neuroanatomy tools like the natverse while exploring fundamental questions about sensory processing and memory retrieval in olfactory circuits. Jefferis leads a collaborative team including Isabella Beckett, Sebastian Cachero, Shahar Frechter, Florian Kampf, Myrto Mitletton, Markus Pleijzier, Gerald Rubin, Philipp Schlegel, Valeria Silva-Moeller, Tomke Stuerner, and Catherine Whittle, with extensive international partnerships evident in recent multi-institutional publications.

• Neuroscience
• Neurobiology
• Olfaction
• +4 more

Prof. Volker Steuber heads the Biocomputation Research Group at University of Hertfordshire's Centre for AI and Robotics Research. With a PhD in Computational Neuroscience from University of Edinburgh, his work develops biologically realistic models of neural systems and applies neuromorphic algorithms to real-world problems. Research combines multi-level neural simulations with experimental collaborations, focusing on cerebellar function, olfactory processing, and spiking neural networks. Current projects include NeuroNex initiatives on olfactory-guided behavior and adaptive robot controllers using synaptic plasticity principles. Recent publications demonstrate advances in olfactory receptor modeling, cerebellar-inspired robotics, and eye movement prediction. His group's interdisciplinary approach bridges computational neuroscience, machine learning, and robotics. President, Organization for Computational Neurosciences (2019-2022) NeuroNex Grant: From Odor to Action (2020-2025) FWF Project: Neuronal mechanisms of odor identification Steuber has supervised multiple PhD students and leads international collaborations across 15+ countries. He serves on editorial boards and has organized major computational neuroscience conferences.

• Computational Neuroscience
• Biologically-Inspired Machine Learning
• Spiking Neural Networks
• +2 more

Dr Alan Holloway is Deputy Head of the School of Engineering & Built Environment at Sheffield Hallam University, overseeing teaching, student experience, and academic outcomes. He holds a PhD (2005) and BEng (2001) from SHU, with professional affiliations as MIET and FHEA. His research focuses on electronic sensors, robotics, and machine olfaction systems, with involvement in EU/EPSRC projects like REINS and Guardians. He actively supervises PhD students and collaborates on industrial projects through Knowledge Transfer Partnerships. Education: PhD: Advanced Quartz Crystal Microbalance Techniques Applied to Calixarene Sensing Membranes (SHU 2005) BEng (Hons): Electronic Systems & Information Engineering (SHU 2001) Research Interests: Development of embedded systems, robotics control, electronic-nose sensors, and sensor coatings. Current projects include Industry 4.0 IoT automation and sensor lab innovations for education. His work bridges academia-industry through device prototyping for healthcare and environmental monitoring. Awards: Fellow Higher Education Academy (FHEA) Teaching & Leadership: Teaches microprocessor systems modules and leads pedagogical reforms like Project-Based Learning assessment models. Presented at conferences on engineering education and remote laboratory solutions. Serves as External Examiner in Electrical/Electronic/Mechatronic Engineering.

• Embedded/microprocessor Systems
• Robotics/Control Systems
• Sensors for machine olfaction (electronic-nose)
• +3 more

Fatema Albalooshi is an Assistant Professor in the Computer Engineering department at the University of Bahrain since 2015. She holds a Ph.D. in Electrical and Computer Engineering from the University of Dayton (2015) and an MSc in Electrical Engineering from the University of Nottingham (2009). Education: PhD, Electrical and Computer Engineering, University of Dayton (2015) MSc, Electrical Engineering, University of Nottingham (2009) BSc, Electrical Engineering, University of Nottingham (2009) Research Interests: Deep Learning Image Processing Computer Vision Biometrics Machine Olfaction Environmental Remote Sensing Peer Review Contributions: Applied Intelligence (5 reviews) Signal, Image and Video Processing (16 reviews) Electronics (1 review) Computers in Biology and Medicine (1 review) Email: falbalooshi@uob.edu.bh

• Electrical and Computer Engineering
• Deep Learning
• Image Processing
• +5 more

Alin-Sasa Tisan is a Senior Lecturer in the Department of Electronic Engineering at Royal Holloway, University of London. His research focuses on neuromorphic systems, pervasive healthcare, and sensor-based applications. He holds a PhD in Electronic Engineering from Technical University of Cluj Napoca (2008) and has certifications in teaching and learning from Anglia Ruskin University (2012). Key research areas include neuromorphic designs for smell recognition, body hydration monitoring, low-cost air quality systems, and FPGA-accelerated signal processing. His work contributes to UN Sustainable Development Goals related to affordable and clean energy, industry innovation, and climate action. Recent projects include developing air quality monitoring systems for Tanzania, creative sensing methods for indoor environments, and cross-disciplinary approaches to industrial electronics challenges. He serves as an External Examiner at the University of Huddersfield and has supervised multiple collaborative projects involving international teams.

• Neuromorphic Systems
• Pervasive Healthcare
• Pattern Recognition
• +9 more

Thomas Nowotny is a Professor of Informatics at the University of Sussex, School of Engineering and Informatics. He is Co-Director of Sussex AI and Head of the AI Research Group, with a research focus on computational neuroscience and bio-inspired artificial intelligence. His work bridges theoretical neuroscience with practical applications in machine learning, neuromorphic computing, and robotics. His primary research interests include: Spiking Neural Networks and neuromorphic computing GPU acceleration of brain simulations (GeNN framework) Information processing in insect olfactory systems Machine learning for electronic noses Bio-mimetic controllers for autonomous robots Hybrid computer-brain experimentation His recent publications demonstrate a strong trend in developing and applying advanced computational methods to model biological neural systems, particularly in insects, and leveraging these models to advance energy-efficient AI. Key themes include gradient learning in spiking networks, neural mechanisms of navigation and olfaction, and high-performance simulation tools. His work frequently appears in top journals such as Nature Machine Intelligence , Nature Communications , and Frontiers in Computational Neuroscience . Nowotny has secured significant research funding from major bodies including EPSRC, BBSRC, the European Union (Human Brain Project), Leverhulme Trust, and HFSP. His grants support projects on embodied cognition, neuromorphic computing, insect-inspired navigation, and memory consolidation. He leads a research group, supervises students, and is actively involved in the global computational neuroscience community as President of the Organization for Computational Neuroscience (OCNS). His technical contributions include the development of the GeNN simulation framework and associated tools like PyGeNN and Brian2GeNN, which enable efficient GPU-accelerated neural network simulations.

• Computational Neuroscience
• Bio-inspired Artificial Intelligence
• Spiking Neural Networks
• +13 more

Dr. Anton Nikolaev serves as a Lecturer in Neuroscience at the University of Sheffield's School of Biosciences since 2013, investigating neuronal circuits for visual information processing using zebrafish models and in vivo calcium imaging techniques to decode object recognition mechanisms and memory encoding processes. Education: PhD, Institute of Cytology, Russian Academy of Science, St.Petersburg (2001-2005) BSc and MSc, University of St.Petersburg (1994-2000) Postgraduate Certificate in Learning and Teaching, University of Sheffield (2015) His research program focuses on how visual systems extract features for object recognition and how synaptic plasticity encodes memory. Using zebrafish larvae expressing calcium indicators, his lab studies neural population dynamics during visual processing, examining feature extraction convergence into object-recognizing neurons and adaptation's role in efficient information processing. Current projects include developing GFP-based reporters for synaptic strength changes during memory formation. Publication trends reveal a consistent neuroscience focus spanning molecular calcium channel studies to systems-level visual processing in zebrafish and Drosophila. His work demonstrates interdisciplinary integration of behavioral paradigms, live imaging, and computational analysis to investigate neural circuit dynamics, synaptic adaptation mechanisms, and sensory information encoding across multiple model organisms. Dr. Nikolaev contributes to the University of Sheffield's Neuroscience Institute and Hearing Research Group, teaching undergraduate neuroscience modules including BMS109-153 Neuroscience and coordinating BMS242 Advanced Concepts in Molecular Physiology as a Fellow of the Higher Education Academy (FHEA).

• Neuroscience
• Visual System
• Neuronal Circuits
• +5 more

Michael Schmuker is Professor of Neural Computation at the University of Hertfordshire, leading research at the intersection of neuroscience-inspired computing and chemical informatics. He develops neuromorphic algorithms for low-power, low-latency chemical sensing systems and applies machine learning to decode olfactory perception. Key research areas: Neuromorphic olfaction for robotic navigation Machine learning for odor prediction Electronic nose technology development Computational modeling of olfactory receptors Schmuker participates in major neuroscience initiatives including the Human Brain Project and NeuroNex consortium, with publications in Science Advances and Nature Machine Intelligence.

• Neuromorphic Computing
• Chemical Informatics
• Machine Learning
• +2 more

Dr Andrej Stancak is a Reader in Behavioural Neuroscience at the University of Liverpool , based in the Department of Psychological Sciences within the Institute of Psychology, Health and Society . His expertise lies in neuroimaging, electrophysiology, and the neural mechanisms of pain, decision-making, and olfaction. He leads multidisciplinary research projects and teaches extensively across undergraduate and postgraduate programs. Education: While specific degrees are not listed in the text, Dr Stancak has held prestigious fellowships including a Fulbright Fellowship (2001), DAAD Fellowship (1997), and DFG Fellowship (1998), indicating advanced training in neuroscience and neuroimaging. Research Interests: Dr Stancak’s work spans pain neurophysiology , brain imaging (EEG, MEG, fMRI) , olfactory modulation of behavior , and economic decision-making . He explores how the brain generates conscious pain experiences and how sensory inputs like odors and textures influence value-based choices, often in collaboration with industry partners such as Unilever and AstraZeneca . Research Trends: His recent publications emphasize mobile EEG applications , machine learning for pain prediction , and cross-cultural neuroscience . There is a consistent focus on translating lab-based findings into real-world contexts, such as online purchasing behavior and chronic pain management. Scientific Awards: He has received several international fellowships and honors, including: Fulbright Fellowship (USA, 2001) DAAD Fellowship (Germany, 1997) DFG Fellowship (Germany, 1998) Ludwig Boltzmann Fellowship (Austria, 1994) Teaching & Supervision: Dr Stancak is the module coordinator for Psychobiology of Pain (PSYC317) and teaches across multiple undergraduate and postgraduate modules. He has successfully supervised 8 PhD students to completion and has 1 pending submission . Labs & Teams: While no specific lab name is provided, his work is conducted in collaboration with the Department of Mathematical Sciences , Institute of Risk and Uncertainty , and international partners such as Charles University in Prague and University of Glasgow .

• Behavioural Neuroscience
• Pain Neurophysiology
• Brain Imaging
• +5 more