Find Academic Supervisors

• Non-invasive brain stimulation
• Transcranial electrical stimulation
• Electroencephalography (EEG)
• +3 more

Jake Toth is a Postdoctoral Research Fellow at the University of Oxford's Institute of Biomedical Engineering, specializing in non-invasive brain stimulation and brain-computer interfaces. He holds a PhD from the University of Sheffield, where his research focused on transcranial electrical stimulation (TES) and electroencephalography (EEG). His current work at Oxford explores transcranial ultrasound stimulation for modulating human brain activity as part of the BUBBL research group. Education: BEng (Bachelor of Engineering) MSc (Master of Science) PhD in Biomedical Engineering His research interests include developing standardized TES protocols, investigating vigilant attention mechanisms, and advancing brain-machine interface technologies. He has contributed to projects involving EEG-based navigation systems and classification algorithms for cognitive tasks. Recent work emphasizes translational applications of neurostimulation techniques in clinical and robotic contexts. Key Contributions: Pioneering EEG feedback systems for robot navigation Advancing Bayesian learning methods in neural data analysis Exploring ethical and technical challenges in non-invasive brain stimulation His work bridges clinical neuroscience, biomedical engineering, and robotics, with applications in personalized cognitive enhancement and human-machine collaboration.

• Brain-Computer Interfaces (BCI)
• Multimodal Interaction
• Mobile Health Applications
• +3 more

Andrew D Ramsay is a Researcher at the University of Glasgow's School of Computing Science, affiliated with the Inference, Dynamics and Interaction group led by Professor Rod Murray-Smith. He holds a M.Sci in Computing Science from the University of Glasgow (2005). His role involves software engineering support for research projects, administration of the IDA GPU cluster, and maintenance of a university-wide events system. Education: M.Sci in Computing Science, University of Glasgow (2005) Research Interests: Ramsay's work spans brain-computer interfaces (BCI), multimodal interaction systems, mobile health applications (e.g., STARFISH for stroke survivors), bioinformatics, and hardware development for research sensors like SHAKE SK8 IMUs. His contributions focus on practical implementations of advanced technologies in clinical, social, and health contexts. Article Trends: His publications emphasize BCI applications (e.g., hybrid BCIs, neuroprosthetics), sensor fusion for user performance optimization, and mobile health interventions. Recent work explores AI-driven conversational search systems and miniature radar for concealed weapon detection. Grants & Advising: Ramsay collaborates on projects funded by diverse grants, though specific grant details are not disclosed. He has contributed to clinical trials (e.g., STARFISH app validation) and interdisciplinary research in bioinformatics and neuroscience. Labs & Teams: He maintains the IDA GPU cluster and supports the NPLinker framework for microbial genomics. His work integrates closely with the MoreGrasp initiative in neuroprosthetics and the OpenInterface platform for multimodal interaction development.

Raphaëlle N. RoyView profile

Professor

• Neuroergonomics
• Physiological Computing
• Brain-Computer Interfaces
• +3 more

Professor Raphaëlle N. Roy is affiliated with ISAE-SUPAERO (Université de Toulouse, France), leading research in Neuroergonomics and Physiological Computing. She holds a PhD and HDR in Cognitive Neuroscience and Signal Processing. Her roles include Course Director for modules in Human Factors and Neuroergonomics across multiple aeronautical engineering programs since 2016. She co-founded the French BCI association CORTICO and is Vice-President (2023–present). Recently promoted to Full Professor, she also serves on editorial boards for journals like Frontiers in Neuroergonomics and reviews for prestigious conferences (NeurIPS, IEEE SMC). Education: HDR (2022, Université de Toulouse), PhD (2015, Univ. Grenoble Alpes/CEA-Leti), Research Master (2011, Summa cum Laude), and international collaborations (UBC, Canada). Research: Focuses on Human-Machine Interaction, Neuroadaptive Technology, and Brain-Computer Interfaces (BCI). Notable work includes the COG-BCI EEG dataset (Scientific Data, 2024) and organizing major events like the Neuroergonomics Conference 2024 in Bordeaux. She advocates for Open Science and has contributed to extreme environment studies in spaceflight. Awards: Ministerial PhD Fellowship (2015), National Neuroscience Certification (2016). Advising & Teams: Supervised over 30 students (PhD/Master's) and postdocs, including recent defenses of Maëlis Lefebvre (2024) and Marcel Hinss (2024). Leads the Interaction Humain-Système (IHS) group in FONISEN and collaborates internationally via projects like EPIIC (ANR-funded). Labs/Teams: Active in Neuroergonomics and Human Factors research at ISAE-SUPAERO, with ties to LAAS-CNRS, INRIA, and ESA/CNES-funded projects.

Kathy RuddyView profile

Senior Lecturer

• Neuroscience
• Brain-Computer Interfaces (BCI)
• Neurorehabilitation
• +5 more

Kathy Ruddy is a Senior Lecturer in the School of Psychology at Queen’s University Belfast. Her research focuses on using brain stimulation and Brain-Computer Interfaces (BCI) to modify neurophysiological function, particularly in neurorehabilitation contexts. She holds a PhD in Psychology from Queen’s University Belfast (2014), followed by postdoctoral work at ETH Zürich and Trinity College Dublin. She leads the Translational Brain Health Lab and has received multiple awards, including Irish Researcher of the Year (2021) and the Northern Ireland Firmus Energy Inspirational Woman of the Year in STEM (2022). Her teaching includes modules on neuropsychology, health psychology, and psychological methods. She actively supervises MSc and PhD students and is open to 2024 PhD applications. Ruddy is a council member of Neuroscience Ireland and founder of BrainState, a brain stimulation clinic in Northern Ireland. Her research spans BCI methodology, neural plasticity in stroke patients, and biomarkers for depression/anxiety treatments.

Rajit ManoharView profile

Professor

• Asynchronous VLSI Design
• Concurrency
• Formal Methods
• +5 more

Rajit Manohar is the John C. Malone Professor of Electrical & Computer Engineering at Yale University, with appointments in Applied & Computational Mathematics and Computer Science. He is a core member of the interdisciplinary Computer Systems Lab (CSL), which bridges ECE and CS departments. His research focuses on asynchronous VLSI design, neuromorphic computing, and hardware-software co-design. Education: Manohar holds a B.S., M.S., and Ph.D. from the California Institute of Technology. His academic career spans over two decades, with notable contributions to asynchronous circuit theory and neuromorphic engineering. Research Interests: Manohar's work emphasizes energy-efficient asynchronous architectures, concurrency control, and biologically inspired computing. He explores topics like formal methods for circuit verification, cognitive systems, and dynamic sensor networks. His lab develops tools like Fluid (asynchronous synthesis) and Neurobench (neuromorphic benchmarking). Publications: Recent work includes advancements in asynchronous logic synthesis (Maelstrom), neuromorphic frameworks (Neurobench), and scalable brain-computer interfaces (SCALO). His research often intersects NSF-funded projects in energy-aware computing and neuromorphic systems. Awards: Inaugural Misha Mahowald Prize (2025), MIT TR35 (2000s), IBM Goldberg Award (2023) Grants & Labs: Manohar leads NSF-supported initiatives in carbon-aware networking and neuromorphic hardware. The Computer Systems Lab collaborates across disciplines to advance sustainable computing and neuro-inspired architectures.

Yuzhe TianView profile

Part-Time Lecturer

• Anomaly Detection
• Industrial Internet of Things (IIoT)
• Sleep Analysis
• +5 more

Yuzhe Tian is a Part-Time Lecturer at the School of Computing, Macquarie University, within the Faculty of Science and Engineering. His research focuses on interdisciplinary applications of machine learning, including anomaly detection in industrial IoT systems, sleep stage recognition via graph networks, and brain-computer interface (BCI) technologies. He holds a Doctor of Philosophy and has published extensively in top-tier conferences and journals since 2019. Research interests include real-time BCI systems using geometric learning, optimization of neural networks (e.g., model pruning and quantization), and healthcare applications like sleep analysis through graph attention networks. His work bridges computational methods with practical challenges in biomedical engineering and industrial automation. Yuzhe has collaborated on projects leveraging multi-view learning for anomaly detection and swarm intelligence algorithms (e.g., Krill Herd Algorithm). His publications span topics from lightweight BCI frameworks to cybersecurity in IIoT environments, demonstrating a strong focus on both theoretical advancements and real-world implementation.

• Neurotechnologies
• Neurorehabilitation
• Brain-Computer Interfaces (BCI)
• +5 more

Professor Aleksandra Vuckovic holds the position of Professor of Neurotechnologies and Rehabilitation in the Department of Biomedical Engineering at the University of Glasgow, within the James Watt School of Engineering. She has been affiliated with the University of Glasgow since 2008 and is also Co-Director of the Scottish Centre for Innovation in Spinal Cord Injury. Her academic background includes an MEng in Engineering Physics and an MSc in Control Systems from the University of Belgrade, followed by a PhD in sensory-motor interaction from Aalborg University (2004). She has held roles at the University of Essex and Aalborg University, and is a Chartered Engineer (IMechE Fellow). Her research focuses on Brain-Computer Interface (BCI) systems for neurorehabilitation, particularly targeting patients with spinal cord injuries. Key areas include developing home-based BCI therapies for neuropathic pain management, combining BCI with functional electrical stimulation (FES), and exploring EEG-based biomarkers for pain prediction. She also investigates neuroplasticity changes and EEG patterns in neuropathic pain conditions. Professor Vuckovic’s work spans over 120 publications, emphasizing BCI applications, EEG analysis, and translational neurotechnology. Her recent studies highlight advancements in spinal cord stimulation effects, neurofeedback success factors, and neuromorphic models for clinical diagnostics. She actively collaborates with institutions like the International Brain Computer Interface Society and serves as an associate editor for journals such as IEEE TNSRE and Frontiers in Neuroergonomics. Her contributions extend to grants and interdisciplinary projects, including the EU-funded CHIST-ERA initiative for BCI translational efforts. She emphasizes patient-centered approaches to BCI design and has pioneered self-managed therapies for chronic pain, recognized by Innovate UK as a Neurotechnology of the Future.

Miguel Serras VascoView profile

Researcher

• Multimodal Perception
• Reinforcement Learning
• Representation Learning
• +4 more

Miguel Serras Vasco is a postdoctoral researcher at KTH Royal Institute of Technology in Stockholm, Sweden, affiliated with the Robotics, Perception and Learning (RPL) division. He holds a PhD from Instituto Superior Técnico, University of Lisbon (2023), where his work earned the Best PhD Thesis in AI in Portugal award. His research focuses on multimodal perception, reinforcement learning, and aligning artificial agents with human perception. He previously worked as an RSS Pioneer and research intern at Sony AI. Education: PhD in Artificial Intelligence, Instituto Superior Técnico, University of Lisbon (2023) Research Interests: Vasco’s work bridges robotics, neuroscience, and AI, emphasizing embodied agents that co-exist with humans. He explores representation learning, human-aligned image models, and sample-efficient reinforcement learning. His recent projects include super-human autonomous racing agents and olfactory perception modeling with transformers. Key Contributions: Vasco co-developed the GT Sophy racing agent, achieved outstanding results in visual decoding from brain activity, and proposed methods like FLoRA for preference-based RL. His work on NeuralSolver advances algorithm extrapolation in reinforcement learning. Awards: Best PhD Thesis in AI in Portugal (APPIA, 2023) Outstanding Paper Award at RLC 2024 (for autonomous racing research) Grants/Advising: Vasco advises students on multimodal and reinforcement learning topics. He actively organizes conferences like the Reinforcement Learning and Video Games Workshop (RLVG) at RLC 2025 and collaborates with institutions like INESC-ID (Lisbon). Labs/Teams: Associated with the Collaborative Autonomous Systems unit at KTH and previously with the GAIPS Lab (INESC-ID, Lisbon).

Barry DevereuxView profile

Senior Lecturer

• Machine Learning
• Natural Language Processing
• Cognitive Science
• +5 more

Dr. Barry Devereux is a Senior Lecturer at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, part of the Faculty of Engineering and Physical Sciences. His research focuses on interdisciplinary applications of machine learning, natural language processing (NLP), cognitive science, and healthcare analytics. He leads projects like the AIDE_NICYBER2025 initiative, exploring cybersecurity and AI integration. Dr. Devereux teaches the CSC2062 Artificial Intelligence and Machine Learning course and advises four PhD students, including those researching semantic vectors, deep learning in healthcare, and neurosciences ontology. His research interests include model interpretation in NLP, lexical semantics, and applying AI to neuroimaging and bioinformatics. Notable achievements include the British Council/IAESTE Employer Award (2018) and contributions to datasets like SynFinTabs and LAB-KG. He collaborates on projects funded by NIO New Deal, PWC, and Liberty IT, emphasizing AI's role in solving complex societal challenges. Dr. Devereux's work bridges computational models with human cognition, leveraging large-scale data analytics to address issues in healthcare, cybersecurity, and environmental science. His lab, affiliated with the Institute of Electronics, Communications & Information Technology (ECIT), fosters innovation in AI-driven solutions.

Monica LebaView profile

Professor

• Robotics
• Artificial Intelligence
• Neural Networks
• +7 more

Prof. Monica Leba holds a Professorship in the Department of Automation, Computers, Electrical and Power Engineering at the University of Petroșani's Faculty of Mechanical and Electrical Engineering. Her work bridges multiple disciplines including robotics, AI-driven systems, cybersecurity, and sustainable technologies. She leads research in areas such as brain-computer interfaces (BCI), exoskeleton control, agritourism innovation, and smart grid integration for electric vehicles. Her academic training and professional experience are deeply rooted in engineering with a focus on practical applications. Recent research emphasizes human-centric technologies like wearable motion capture systems for industrial safety, AI-enhanced gait analysis for neurodegenerative disease management, and BCI-controlled robotics for neurorehabilitation. She also explores socio-technical systems such as agritourism 4.0 frameworks and project management methodologies (SAFe®/Agile) for tech innovation. Leba's publications reflect a multidisciplinary approach, with over 30+ peer-reviewed papers since 2020 addressing topics like: Energy-efficient cryptography designs Autonomous vehicle navigation systems Wildlife conflict prevention via IoT Fuzzy logic-based startup risk assessment Smart grid integration for mining regions Her work often combines hardware-software co-design principles with real-world implementation in industrial heritage revitalization (e.g., Petrila mining area), wearable healthcare systems, and rural technology adoption. Current projects include AI-driven burnout monitoring devices and collaborative robotics for manufacturing. Leba collaborates with industry partners on applied research in: Underground mine communication systems Autonomous drone navigation Medical exoskeleton control Smart tourism platforms Her research philosophy emphasizes sustainability, human-centered design, and translational innovation across engineering, healthcare, and agritourism sectors.

Popescu Florin GabrielView profile

Associate Professor

• Energy Security
• Power Systems Engineering
• Electrical Safety
• +5 more

Popescu Florin Gabriel is an Associate Professor at the University of Petroșani within the Faculty of Mechanical and Electrical Engineering , specifically in the Department of Automation, Computers, Electrical and Power Engineering . He serves as Director of the socio-economic relations center, focusing on interdisciplinary collaboration between academia and industry. His research primarily revolves around energy security, electrical infrastructure resilience, occupational safety in power systems, and sustainable energy integration. Notable areas include critical infrastructure protection for power grids, mitigation of electrical hazards in mines, and modernization of electrical installations. He has extensively studied harmonics in power systems, renewable energy integration challenges, and the strategic role of Romania's energy sector in European security contexts. His publications from 2022–2025 emphasize: Risk assessments for high-voltage substations (e.g., Timișoara, Urechesti) Energy security analyses linking national grids to geopolitical stability Innovative solutions like BCI-based mental state recognition and intelligent greenhouse automation Modernization of university laboratory infrastructure Awards/Grants: No specific awards or grants mentioned in the provided texts. His work is primarily funded through institutional and industrial partnerships. Labs/Teams: Leads the Electroenergetics Laboratory modernization efforts and collaborates with industry partners on electrical safety and automation projects.

Adam Grant WorralloView profile

Academic

• Virtual Reality
• Augmented Reality
• Mixed Reality
• +9 more

Dr. Adam Grant Worrallo is an Associate Lecturer in Computer Science at the School of Mathematics and Computer Science, Faculty of Science and Engineering, University of Wolverhampton. He holds a PhD from the same institution, awarded in 2020, and specializes in Virtual and Augmented Reality, Human-Computer Interaction, and Game Development. Education: BSc (Hons) in Computer Science (Games Development) MSc in Computer Science PhD in Computer Science from the University of Wolverhampton (2020) His research focuses on immersive technologies, including Virtual Reality, Augmented Reality, Mixed Reality, Haptics, and Visual Computing . He also explores applications in mobile and web development, gaming, and software engineering , with a strong emphasis on user interaction and interface design. His technical expertise spans Unity3D, Python, JavaScript, Android SDK, and AI frameworks like TensorFlow and Keras. His recent publications highlight innovations in optical hand tracking for VR, dual-mode web-based 3D interfaces, and assistive technologies using low-cost brain-computer interfaces. These works reflect a consistent focus on enhancing user experience in interactive digital environments , particularly through novel input methods and accessible design. Professional Affiliations: Fellow of the Higher Education Academy Professional Member of the British Computer Society (BCS) Dr. Worrallo brings industry experience as an independent mobile developer and former Systems Assistant Engineer. He has designed and marketed mobile apps for iOS and Android and developed applications for smart home devices like Alexa and Google Home. His development experience covers full-stack technologies including Node.js, MongoDB, Flutter, PHP, and Docker, under both agile and waterfall methodologies. He is actively involved in teaching and research at the University of Wolverhampton, contributing to both academic and practical advancements in computer science education and interactive technology.

Jihye BaeView profile

Assistant Professor

• Neural Interfaces
• Signal Processing
• Machine Learning
• +6 more

Jihye Bae is an Assistant Professor at the University of Kentucky within the Stanley and Karen Pigman College of Engineering , leading the Neural Interfaces and Signal Processing (NISP) Laboratory . Her research focuses on developing systems and methods to assist patients with neuromuscular disabilities and neurological disorders using signal processing , machine learning , and neural decoder techniques. Education: Ph.D. in Electrical and Computer Engineering, University of Florida (2013) M.S. in Electrical and Computer Engineering, University of Florida (2009) B.Eng. in Electrical Engineering and Computer Science, Kyungpook National University, South Korea (2007) Her research spans brain-machine interfaces , EEG signal processing , and source imaging for epilepsy and prosthetic development . Recent publications explore fNIRS semantic reconstruction , EEG-fMRI artifact removal , and reinforcement learning in neural decoders. She has also contributed to metric learning and correntropy kernel methods for brain-computer interfaces. Jihye Bae supervises active researchers including PhD students Bhoj Raj Thapa and Santiago Posso Murillo , as well as Master's and undergraduate students. Her lab has received recognition through Lighthouse Beacon Foundation Graduate Fellowships for trainees. She teaches courses like EE 421G Signals and Systems and EE 599/699 Neural Signal Processing and Interfaces .

• Human-Computer Interaction
• Assistive Technology for Autism
• Biomedical Informatics
• +3 more

Lizbeth Escobedo is a researcher with significant contributions to Human-Computer Interaction , Assistive Technology for Autism , and Biomedical Informatics . Her work spans collaborations with institutions in Mexico and the U.S., focusing on technology-driven interventions for neurodevelopmental disorders and maternal health. Key Research Areas: Assistive Technology for Autism, Augmented Reality, Biomedical Informatics, Educational Software, Cross-Cultural Technology Design Her recent publications highlight innovations in handwriting legibility assessment (2024), stress management tools for autism (2023), and BCI video games for attention improvement (2021). She has also explored ethical frameworks for participatory design with ASD children and developed diagnostic workflows for urinary infections during pregnancy. While no scientific awards or student advisement details are publicly available, her interdisciplinary collaborations with co-authors like Monica Tentori and Franceli L. Cibrian underscore her integration of computer science , pediatrics , and mental health research.

• Intelligent User Interfaces
• User Modeling
• Cognitive Sciences
• +6 more

Prof. Dr. Antonio Krüger is a renowned academic in the fields of Human-Machine Interaction and Artificial Intelligence. He serves as the CEO and Scientific Director of the German Research Center for Artificial Intelligence (DFKI) and leads the Ubiquitous Media Technology Lab at the University of Saarland since 2009. His research focuses on Intelligent User Interfaces, User Modeling, Cognitive Sciences, and Ubiquitous Computing. Notable projects associated with Prof. Krüger include: CAMELOT: Continuous Adaptive Machine Learning for Control Transfer Situations in autonomous systems. EXPECT: Exploring Pervasive Embedded Brain Reading in Human-Robot Collaborations. RICAIP: Research and Innovation Centre on Advanced Industrial Production, connecting CIIRC CTU and CEITEC BUT. WALL-ET: German-Korean collaboration on social transport robots for Industry 4.0 and retail. Cluster 4.0: Addressing system integration and flexible software architectures for adaptive manufacturing. His recent publications span topics like EEG-based BCIs, federated learning for well-being, and VR applications in plant variety research, reflecting his interdisciplinary expertise.