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Peter BurkeView profile

Professor

• Nanoelectronics
• Quantum Electronics
• Graphene Electronics
• +7 more

Peter Burke is a Professor of Electrical Engineering and Computer Science (joint appointments in Biomedical Engineering and Materials Science and Engineering ) at the Samueli School of Engineering, University of California, Irvine . His research bridges nanoelectronics with biotechnology , focusing on carbon nanotubes , graphene devices , and mitochondrial bioenergetics . He has received prestigious Young Investigator Awards from the Office of Naval Research and Army Research Office. Education: B.A. in Physics, University of Chicago (1992) Ph.D. in Physics, Yale University (1998) His work spans quantum electronics , high-speed semiconductor devices , and bio-nano interfaces . Recent publications highlight drone technology , mitochondrial electrical activity , and AI-driven nanoscale sensing . Research trends include terahertz spectroscopy , super-resolution imaging , and open-source medical devices like the NanoStat potentiostat . Scientific Awards Young Investigator Award, Office of Naval Research Young Investigator Program Award, Army Research Office As director of the BurkeLab , he develops nano-electronic interfaces for biological systems, including mitochondrial membrane potential assays and graphene-based biosensors . His lab's innovations in carbon nanotube arrays and scanning microwave microscopy have advanced bio-nano applications.

Arezoo EmadiView profile

Associate Professor

• Microelectromechanical Systems (MEMS)
• Bio-Medical Devices
• MEMS Sensors and Transducers
• +8 more

Dr. Arezoo Emadi is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Windsor. She leads the electrical Micro and Nano Devices and Sensors (eMinds) Research Lab, focusing on MEMS-based smart sensor systems for biomedical, environmental, agricultural, and personal electronics applications. Her research spans MEMS sensors, bioMEMS, ultrasonic imaging, and microfabrication technologies . Education: Ph.D., University of Manitoba; Licentiate Degree, Chalmers University of Technology (Sweden). Affiliations: Senior Member of IEEE, Professional Engineer (PEng Ontario), and advisor for IEEE Women in Engineering (WIE). Her research interests emphasize MEMS transducers, chemical sensors, and e-nose systems . Key projects include developing next-generation sensors for medical diagnostics, environmental monitoring, and non-destructive testing. Collaborations with industry and academic partners drive applied innovations. Dr. Emadi has supervised numerous students, including PhD and MASc candidates, undergraduates, and international researchers. Her lab manages advanced fabrication processes and maintains state-of-the-art equipment for MEMS development. Awards: Senior Member, IEEE Professional Engineer (PEng) designation Her lab’s work has produced over 100 publications and patents, including recent advancements in QCM sensors and ultrasonic transduction systems. Current opportunities exist for graduate students and postdocs in MEMS design and sensor integration.

Tim PearceView profile

Professor

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

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.

Vasanthan DevarajView profile

Researcher

• Plasmonics
• 3D Printing
• Biosensors
• +6 more

Dr. Vasanthan Devaraj is a PostDoc Group Leader at the Institute for Photonic Quantum Systems (PhoQS) in the University of Paderborn , leading the Ultrafast Nanophotonics group. His research focuses on plasmonics, 3D printing of nanostructured materials, biosensor development, and quantum emitter engineering. He specializes in self-assembly techniques, metallic nanostructure fabrication, and biohybrid systems. Research Interests : Plasmonic nanostructures and their optical properties 3D printing of metallic and biomaterial nanoarchitectures Smart biosensors for healthcare, environment, and agriculture Quantum dots and photonic devices Bio-inspired self-assembly using M13 bacteriophage Energy-efficient nanomaterials for solar cells Notable Contributions : Pioneered 3D printing of multi-material plasmonic nanostructures with sub-100 nm resolution. Developed biosensors for lung cancer detection, environmental pollutants, and fruit freshness analysis. Optimized plasmonic nanocavities with sub-5 nm gaps for enhanced light-matter interactions. Recent Work Trends : His articles emphasize plasmonic dimer assembly , 3D-printed metallic nanostructures , and biohybrid systems . Key themes include self-assembly optimization, plasmonic field enhancement, and biomaterial integration for diverse applications. Labs & Teams : Leads the Ultrafast Nanophotonics Group , collaborating on projects involving photonics, quantum materials, and bio-inspired engineering.

Venkatesh N. MurthyView profile

Professor

• Neuroscience
• Olfaction
• Neural Circuits
• +3 more

Venkatesh N. Murthy is a neuroscience faculty member specializing in olfactory processing and neural circuit dynamics. His research focuses on deciphering how neural systems encode, process, and respond to sensory stimuli, particularly odors. Key areas include odor mixture perception, neural algorithms for compressed sensing, and the role of feedback loops in olfactory bulb-cortex communication. Murthy employs rodent models and computational approaches to study adaptive behavior, learning mechanisms, and sensory navigation in dynamic environments. Research Focus: Murthy's work bridges experimental neurobiology and theoretical modeling, with emphasis on: Neural representation of odorants and mixtures Cortical feedback mechanisms in sensory processing Biomimetic applications for electronic nose design Dopamine signaling in associative learning His recent publications demonstrate consistent focus on olfactory coding, neural plasticity, and adaptive algorithms, with emerging themes in social behavior circuitry and AI-driven neural signal analysis.

• 2D Materials
• Carbon Nanomaterials
• Energy Storage
• +12 more

Dr. Ievgeniia Kovalska is a Lecturer in Advanced 2D Energy Materials within the Department of Engineering at the University of Exeter, and a member of the Nano Engineering Science and Technology (NEST) Group and the UK Metamaterials Network. With over a decade of expertise in 2D and carbon materials, her work spans synthesis, characterisation, and applications in energy, (bio)sensing, (opto)electronics, wearables, and sustainable devices. Education: PhD in Chemistry, Chuiko Institute of Surface Chemistry, National Academy of Sciences of Ukraine MSc in Chemistry and Biology, National Pedagogical Dragomanov University, Kyiv BSc in Biology, National Pedagogical Dragomanov University, Kyiv Her research focuses on innovative materials for energy storage (Li-/non-Li batteries) and renewable energy (triboelectric nanogenerators), leveraging graphene, transition metal dichalcogenides, pnictogens, and tetrels. She employs interdisciplinary methods in material synthesis, device fabrication, and testing to advance sustainable technologies. Her work combines fundamental science with practical applications in sensing and energy harvesting. The 15 most recent articles reflect a strong trend in functional 2D materials, with emphasis on energy storage, optoelectronics, sensing, and sustainability. Keywords span materials science, nanotechnology, and engineering, while subfields include graphene applications, TMDCs, flexible devices, and hydrophobic coatings. Her publications demonstrate a consistent focus on scalable synthesis, device integration, and real-world impact. Scientific Awards and Recognition: Over 50 high-ranking publications with 900+ citations and an h-index of 16 Three granted patents, including a novel method for 2D material synthesis Sole inventor of a hydrophobic coating for stone-wall protection Recognition from global research community and media Dr. Kovalska is actively involved in research supervision (PhD and Masters), consultancy, peer review, and external examining. She has received funding for her postdoctoral and current research roles and is committed to advancing diversity in STEM through initiatives like 'Women in Smart Nanomaterials Technology', 'It's Her', and 'Soapbox Science Exeter'. She serves on the Wellbeing, Inclusion, and Culture Committee, promoting equity and inclusion in science. She leads projects on sustainable energy devices and participates in collaborative networks such as the UK Metamaterials Network. Her lab work involves the NEST Group, where she develops hybrid material systems for next-generation technologies. Future work aims to expand the application of 2D materials in climate-responsive and wearable systems.

• Analytical Chemistry
• Environmental Chemistry
• Sensor Technology
• +3 more

Larisa Lvova is a researcher affiliated with the University of Rome Tor Vergata, Italy. She holds M.S. and Ph.D. degrees from St. Petersburg State University, Russia, and a Dr.Sc. in Analytical Chemistry (2017) and a second Ph.D. in Chemical Sciences (2012) from Tor Vergata University. Her research focuses on the development of chemical sensors and multisensory systems for environmental monitoring, pharmaceutical analysis, and biomedical applications. Her educational background includes: M.S. in Physical Chemistry (1996), St. Petersburg State University Ph.D. in Physical Chemistry (1999), St. Petersburg State University Ph.D. in Chemical Sciences (2012), University of Rome Tor Vergata Dr.Sc. in Analytical Chemistry (2017), St. Petersburg State University Research interests emphasize: Optical and electrochemical sensors for heavy metals and pharmaceuticals Electronic nose and tongue systems for environmental and food analysis Novel materials for gas and liquid sensing (e.g., porphyrins, corroles, nanocellulose) Her recent publications highlight advancements in sensor design for pollutants like PFOA ('forever chemicals'), drug monitoring (e.g., ketoprofen), and environmental contaminants. She serves as a Review Editor for Supramolecular Chemistry in Frontiers in Chemistry. Lvova collaborates internationally on sensor arrays for ecological and biomedical applications. Her work bridges material science, analytical chemistry, and engineering to address real-world challenges in environmental protection and healthcare.

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

• Postharvest Technology
• Food Loss Reduction
• Electronic Nose Applications
• +3 more

Asgar Ali serves as an Adjunct Professor within the Institute of Agriculture at The University of Western Australia (UWA), based at the Perth campus. His academic role centers on advancing research in postharvest physiology and food security, with a strong commitment to addressing global challenges in agricultural sustainability and reducing food waste through innovative technological solutions. His research expertise encompasses: Postharvest Technology and Physiology Food Loss and Waste Reduction Strategies Electronic Nose Applications for Quality Monitoring Polyphenols and Antioxidants in Food Systems Biostimulants for Crop Enhancement Recent scholarly contributions (2024-2025) demonstrate a multidisciplinary approach integrating agricultural science, food technology, and pharmacology. Notable trends include nanotechnology for targeted biostimulant delivery in chili peppers, electronic nose systems for papaya ripening assessment, and resveratrol's therapeutic potential for COPD. These efforts align with Sustainable Development Goals 2 (Zero Hunger) and 12 (Responsible Consumption and Production), particularly through innovations that mitigate postharvest losses in developing countries. Scientific awards and honors were not documented in the available profile information. While the profile does not specify current advisees or grant funding, Dr. Ali's collaborative research network includes co-authors from diverse institutions, suggesting active engagement in international agricultural research initiatives focused on food security and postharvest innovation. Details regarding specific laboratories or research teams led by Dr. Ali are not provided in the current profile snapshot, though his fingerprint analysis indicates significant contributions to postharvest agricultural science (100%) and food loss reduction (80%).

Mark ElshawView profile

Lecturer

• Robotics
• Neural Networks
• Electronic Noses
• +6 more

Dr. Mark Elshaw is a Lecturer in Computer Science at the School of Science, with expertise in robotics, neural networks, and biologically inspired computing systems. He has worked at the University of Sunderland, Sheffield University, and Coventry University, contributing to projects like the development of a bio-inspired robot that won the British Computer Society Intelligent Machine Prize. His research spans speech recognition, robot-human interaction, and emotion recognition in robots. Research Interests : Neural architectures, biomimetic robotics, unsupervised learning, experimental methodologies for social robots. Key Contributions : Edited computational neuroscience books, organized conferences, and contributed to robotics and deep learning advancements. Scientific Awards : British Computer Society Intelligent Machine Prize (team member). Recent Publications focus on emotion recognition, deep learning for autonomous vehicles, and neural architectures for social robots. He has also explored reinforcement learning, mirror neuron systems, and multimodal learning in robotics.

Pamela AbshireView profile

Professor

• VLSI Circuit Design
• Bioengineering
• Information Theory
• +7 more

Pamela Abshire is a Professor in the Department of Electrical and Computer Engineering and the Institute for Systems Research at the University of Maryland, College Park. She holds the rank of Fischell Institute Fellow and is affiliated with the Maryland Robotics Center, Brain and Behavior Institute, and Robert E. Fischell Institute for Biomedical Devices. Her work bridges VLSI circuit design and bioengineering, focusing on performance-resource tradeoffs in natural/engineered systems. Education: B.S. Physics (Caltech, 1992), M.S. and Ph.D. in Electrical Engineering (Johns Hopkins University, 1997 and 2001). Pre-UMD career included R&D roles at Medtronic (1992-1995). Research focuses on CMOS biosensors, low-power microsystems, and bio-inspired designs for applications like cell-based sensing, robotics, and medical devices. Notable projects include nose-on-a-chip odor detection systems, ant-like microrobots, and lab-on-CMOS platforms for real-time cell monitoring. Awards include IEEE Fellow (2018), NSF CAREER Award (2003), and 2021 University Distinguished Scholar-Teacher honor. Active in academic leadership roles including ADVANCE Professor (2020-2021) and editorial work for IEEE Transactions on Circuits and Systems. Grants include NSF funding for olfactory sensing, AFOSR bio-inspired flight tech, and DARPA CogniSense initiatives. Her Integrated Biomorphic Information Systems Lab collaborates on semiconductor innovation through partnerships like the Mid-Atlantic Semiconductor Collaborative. Labs/Teams: Leads the Integrated Biomorphic Information Systems Lab and contributes to Microelectronics at Maryland group. Co-develops biohybrid systems integrating CMOS, MEMS, and biological components.

• Graphene sensors
• Biosensors
• Microneedles
• +5 more

Professor Owen Guy serves as Head of Chemistry and Director of the Centre for Nanohealth at Swansea University's Faculty of Science and Engineering. His research bridges semiconductor fabrication and biomedical applications, particularly in graphene biosensors and microneedle technology. Head of Chemistry (2018–Present) Director of Centre for Nanohealth (2015–Present) Former Head of Systems Process & Engineering Centre (2014–2018) With 18 years' experience in cleanroom device fabrication, Guy's work spans epitaxial graphene biosensors , silicon microneedles , and microfluidic integration . His research has commercial implications in cancer risk monitoring, Alzheimer's diagnostics, and transdermal drug delivery. Recent publications highlight advancements in graphene-polymer composites for gas detection, microneedle arrays for therapeutics, and Al2O3 passivation for biosensor reliability. Collaborations with industry partners like SPTS Technologies underscore his translational focus. Awardee of the Royal Academy of Engineering's 2009 Young Entrepreneur Award shortlist, Guy has supervised over 20 postgraduate students and secured £4M+ as PI. His work combines semiconductor engineering with clinical applications , creating novel diagnostic tools through interdisciplinary approaches.

Barani RamanView profile

Professor

• Computational Neuroscience
• Systems Neuroscience
• Pattern Recognition
• +7 more

Barani Raman is a Professor of Biomedical Engineering at the McKelvey School of Engineering, Washington University in St. Louis. His research integrates computational neuroscience, neuromorphic engineering, and sensor technologies to develop bio-inspired systems with applications in biomedical devices, environmental monitoring, and security. He holds a PhD from Texas A&M University and joined Washington University in 2010 after postdoctoral training at NIH and NIST. Education: PhD, Texas A&M University, 2005 MS, Texas A&M University, 2003 B.Eng., University of Madras, 2000 Research Interests: His lab explores how the brain processes sensory signals (e.g., olfactory cues) and translates these insights into technologies like electronic noses and neuromorphic devices. Recent work includes serotonin’s role in locust olfaction and nanoparticle interactions with neurons for treating neurological disorders. Grants & Collaborations: $650,000 NSF Convergence Accelerator grant (2024) for water quality monitoring and electronic nose development Collaborations with Srikanth Singamaneni on neuroengineering He leads the Raman Lab and is affiliated with the Center for Science and Engineering of Living Systems and the Imaging Science PhD Program.

James CovingtonView profile

Professor

• Artificial Olfactory Systems
• Gas Phase Analysis Sensors
• Medical Diagnostics via Bio-Markers
• +4 more

Professor James Covington is a Professor in Electronic Engineering at the University of Warwick's School of Engineering, serving as Associate Head of Department (Impact & Industry). His research focuses on developing chemical/biological sensors for environmental pollutants and medical applications, leading to the creation of the Biomedical Sensors Laboratory in 2010. He has pioneered low-cost chemical sensors licensed to AMS and collaborates with industries like Sony, IBM, and Roche. His work spans sensor fundamentals, instrumentation, and applications in agriculture, automotive, and security sectors. Research interests include artificial olfactory systems, gas phase analysis, clinical biomarker detection, and low-cost sensor materials. Notable projects include VOC-based diagnostics for pancreatic cancer, UTIs, and Alzheimer’s disease, as well as non-invasive preterm birth prediction. He chairs the International Society of Chemical Sensors and contributes to global sensor standards via IEEE and IET. Key grants include Innovate UK funding for antibiotic resistance diagnostics and Wellcome Trust support for urinary tract infection analysis. His sensor systems address urgent healthcare needs while advancing environmental and industrial monitoring. The Biomedical Sensors Laboratory drives interdisciplinary innovation, combining electronics, materials science, and clinical applications.

Dmitry RinbergView profile

Professor

• Olfactory Coding
• Neural Computation
• Systems Neuroscience
• +3 more

Dmitry Rinberg is a Professor in the Department of Neuroscience at the NYU Grossman School of Medicine. His research focuses on understanding how olfactory information is processed in the brain, particularly the neural mechanisms underlying odor perception and the development of bio-electronic nose technology. He holds a PhD from the Weizmann Institute of Science and leads the Rinberg Lab, which employs advanced techniques like optogenetics and two-photon imaging to study neural coding in olfactory systems. Key projects include the BRAIN Initiative consortium to decode olfactory signals and create versatile chemical detection systems. His work bridges theoretical neuroscience with experimental approaches, emphasizing the primacy model of odor coding and the behavioral relevance of neural activity patterns. Education: PhD in Physics from Weizmann Institute of Science Lab Focus: Olfactory coding, neural computation, bio-electronic nose development Techniques: Optogenetics, holographic stimulation, wide-field imaging Collaborations: Shoham Lab (neurophotonics), BRAIN Initiative consortia Research highlights include defining odor identity through primacy coding, decoding neural activity for real-time chemical detection, and advancing optogenetic tools to manipulate olfactory circuits. Students and postdocs in his lab work on projects ranging from perceptual distance measurement in mice to engineering next-generation sensory interfaces.