جست‌وجوی استاد و پژوهشگر

• Neuromorphic Computing
• Materials Science
• Memristors
• +۴ مورد دیگر

Hongwei Tan is a Visiting Professor in the Department of Applied Physics at Aalto University, affiliated with the School of Science and Technology. He holds a Ph.D. in Natural Sciences from the Chinese Academy of Sciences (2011-2016) and a Bachelor's degree in Natural Sciences from Nankai University (awarded 2011). Research focuses on neuromorphic computing, memristors, wearable health monitoring, and bioinspired materials. Principal Investigator of the Optoelectronic Synapses for Artificial Neuro Networks project (2018-2021). Published 16+ articles in journals like Advanced Materials , Nature Electronics , and ACS Nano . Key research interests include developing neuromorphic systems, flexible synaptic transistors for healthcare, and materials science innovations for machine vision. His work contributes to UN Sustainable Development Goals related to education and technological advancements. Media highlights include coverage of neuromorphic visual sensors and programmable smart fabrics in outlets like Nature Communications and Cell Reports Physical Science . Led projects on optoelectronic synapses and collaborated on datasets like the 2024_CRPS project. His research bridges materials science, computer science, and biomedical engineering.

Francisco Javier Rodriguez Lozanoمشاهده پروفایل

استاد

• Stomatology
• Dental Biomaterials
• Stem Cell Research
• +۴ مورد دیگر

Francisco Javier Rodriguez Lozano is a Professor at the Faculty of Medicine of the University of Murcia, affiliated with the Department of Dermatology, Dentistry, Radiology and Physical Medicine . His research focuses on stomatology, dental biomaterials, and regenerative medicine, with a particular emphasis on the application of stem cells and advanced materials in dentistry. He is a member of the Hematology, Hematopoietic Transplantation and Cell Therapy research group. He holds three doctoral degrees: one from the University of Córdoba in Computer Science (2020), another from the University of Valencia in Biomedical Engineering (2021), and a third from the University of Murcia in Dentistry (2009). His academic supervisors included Dr. Joaquín Olivares Bueno, Dr. Leopoldo Forner Navarro, and Dr. Salvador Martínez Perez. Research Interests: Dr. Rodriguez Lozano’s work spans regenerative dentistry, biocompatible materials, and the interplay between oral health and systemic diseases. He explores artificial intelligence applications in medical diagnostics and has pioneered studies on graphene-based materials for bone regeneration. His research also addresses cytotoxicity evaluations of dental products and the role of stem cells in endodontic therapies. Publications Trends: His recent work emphasizes biomaterials (e.g., calcium silicate-based sealers, graphene composites) and their clinical applications. He has systematically reviewed links between oral dysbiosis and neurodegenerative diseases (e.g., Alzheimer’s, Parkinson’s), as well as oral health in chronic kidney disease. AI-driven diagnostic tools (e.g., bee hive monitoring, autism detection via eye-tracking) highlight his interdisciplinary approach. Awards & Grants: No specific awards or grants were mentioned in the provided texts. However, his extensive publication record reflects sustained research activity. Advising & Labs: While no current advisees are listed, his doctoral theses suggest expertise in guiding research in computational methods and biomaterials. His work is conducted within the University of Murcia’s medical and dental research facilities.

Bernardo Luís Portelaمشاهده پروفایل

پژوهشگر

• Cryptography
• Information Security
• Secure Multiparty Computation
• +۳ مورد دیگر

Bernardo Luís Portela is a Senior Researcher at HASLab/INESC TEC since January 2014 and a fourth-year Ph.D. student in the MAPi doctoral programme at the University of Minho. His research focuses on cryptography, information security, and secure multiparty computation (MPC) leveraging trusted hardware. He contributes to projects like SafeCloud and NanoSTIMA, advancing high-assurance MPC protocols by bridging theoretical and practical implementations. Education: M.Sc. in Informatics Engineering from the University of Minho. Research Interests: Specializes in secure MPC protocols using Isolated Execution Environments (IEEs), privacy-preserving machine learning, and distributed system security. His work includes formalizing security guarantees for IEEs and hybrid schemes for efficient ML computation. Advising & Projects: Supervised multiple theses on topics like telecom fraud detection, speculative execution resilient cryptography, and TLS 1.3 C2 traffic analysis. Active in collaborative projects addressing cloud security and distributed system vulnerabilities. Labs/Teams: Member of HASLab/INESC TEC, contributing to high-assurance software solutions for distributed systems and network security.

Luís Soares Barbosaمشاهده پروفایل

استاد

• Program Semantics
• Coalgebra Theory
• Modal and Hybrid Logics
• +۳ مورد دیگر

Luís Soares Barbosa is a Full Professor at the Department of Informatics, University of Minho, and Senior Researcher at HASLab INESC TEC. He serves as Deputy Head of UNU-EGOV (United Nations University Unit on Electronic Governance) and leads the Quantum Software Engineering Research Group at INL. His research focuses on program semantics, coalgebra theory, and quantum computing applications. He has coordinated multiple national and international projects, including the ALFA EU-Latin America network. Barbosa has supervised numerous PhD students, with one recipient of the 2013 IBM Scientific Prize. He actively contributes to academic governance, serving as Director of the Joint Doctoral Programme MAP-i and Chair of IFIP TC1 on Foundations of Computer Science. Research Interests: Program semantics and calculi for systems understanding Coalgebra theory and modal/hybrid logics Quantum software engineering and algorithms Paraconsistent transition systems for inconsistency management Publications: His recent work spans quantum reinforcement learning, non-perturbative quantum simulations, and formal methods for software engineering. These contributions highlight advancements in quantum advantage, scalable algorithms, and robust system modeling. Professional Roles: Member of IFIP WG1.3 and Chair of IFIP TC1 Invited lecturer at Universities of Bristol, Tartu, and Peking Founder of MAP-i Joint Doctoral Programme Labs/Teams: Leads the Quantum Software Engineering Group at INL, advancing quantum algorithm development and software rigor.

• Digital Forensics
• Cybersecurity
• Information Security
• +۴ مورد دیگر

Philip Anderson is a Senior Lecturer at Northumbria University, specializing in digital forensics and cybersecurity. He is the Programme Leader for the BSc (Hons) Computer Forensics course, teaching modules such as Computer Forensic Applications and Legal and Evidentiary Aspects of Computer Forensics. His roles include managing the university’s dedicated computer forensics lab and participating in recruitment events. With a BSc in Business Information Technology (1997) and an MSc in Distance Education (2008), Anderson has over two decades of experience in technical support and full-time teaching. He was appointed an ENISA expert (2010, 2012) for his work on ICT risk assessment and has served as a Durham Constabulary Special Constable for 14 years. Anderson’s research focuses on digital forensics within the criminal justice system, cybersecurity collaboration between CSIRTs and law enforcement, and AI-driven solutions for online threats like grooming and phishing. His work emphasizes practical applications, such as developing tools for forensic disclosure confidence and enhancing cybercrime detection systems. He has published extensively on topics like network visualization (NETIVAR) and robotic exoskeleton control systems. Key Awards: ENISA Expert Appointment (2010, 2012) Professional Activities: Invited talks on cybersecurity and digital forensics (2016–2022), collaborations with institutions like Waynesburg and Columbus State Universities. Labs/Teams: Manages Northumbria’s computer forensics lab, supporting hardware/software development for forensic investigations.

Sk Khairul Hasanمشاهده پروفایل

استادیار

• Robotics
• Mechatronics
• Nonlinear Control
• +۵ مورد دیگر

Sk Khairul Hasan is an Assistant Professor in the Department of Mechanical and Manufacturing Engineering at Miami University. His research focuses on robotics, mechatronics, nonlinear control, and data-driven modeling, with particular emphasis on exoskeleton systems for human rehabilitation. He teaches undergraduate and graduate courses in electrical and mechanical engineering, emphasizing foundational knowledge transfer. Dr. Hasan holds a Ph.D. in Mechanical Engineering from the University of Wisconsin-Milwaukee (2021), an M.S. in Mechatronics Engineering from International Islamic University Malaysia (2010), and a B.Sc. in Mechanical Engineering from Khulna University of Engineering and Technology (2008). His research interests include exoskeleton robot design, mechatronics systems, mobile robotics, and industrial IoT. Notable projects include an 8-DOF lower extremity exoskeleton for rehabilitation, fuzzy logic controllers for hybrid vehicles, and a 3-DOF programmable manipulator arm. Recent publications highlight advancements in exoskeleton control systems, including radial basis function controllers and sliding mode control algorithms. His work bridges theoretical control strategies with practical robotic applications in healthcare and industry. Recipient of the UWM Chancellor Award for Outstanding Research (2021) Member of IEEE Robotics and Automation Society, SAE, and Institute of Engineers Bangladesh Labs/Teams: Biomechatronics System Design Laboratory.

Marco Caniniمشاهده پروفایل

استاد

• Distributed Systems
• Cloud Computing
• Computer Networking
• +۲ مورد دیگر

Marco Canini is Professor of Computer Science at KAUST's Computer, Electrical and Mathematical Sciences & Engineering division. His research creates next-generation computing infrastructure for distributed AI/ML systems, focusing on network programmability and efficient large-scale computation. Research interests span distributed systems, cloud computing, and programmable networks, with current focus on systems support for distributed machine learning. His work develops practical implementations deployable in real-world environments. Recent publications demonstrate strong trends in optimizing distributed training through hardware acceleration (SmartNICs), communication efficiency (quantization methods), and privacy-preserving techniques (federated/split learning).

Vadim Geurkovمشاهده پروفایل

دانشیار

• Built-In Self-Test and Self-Repair in Reconfigurable Computing Systems
• Digital and Mixed-Signal Systems Testing and Testable Design
• Self-Diagnosis in Microprocessor Based Measurement Instruments
• +۲ مورد دیگر

Vadim L. Geurkov is an Associate Professor at the Department of Electrical and Computer Engineering, Toronto Metropolitan University. He earned an M.A.Sc. in Electrical Engineering from Georgian Technical University (1981) and a Ph.D. in Computer Engineering from the Institute of Control Sciences, Moscow (1993). Research Focus: Specializes in digital and mixed-signal systems testing, with expertise in built-in self-test/repair mechanisms, fault tolerance, error-control codes, and self-diagnosis in reconfigurable computing systems. His work bridges theoretical and applied aspects of hardware reliability. Industry Collaborations: Led projects with OCE-CCIT, MDA Space Missions Inc., NSERC, and other partners on reconfigurable processors, FPGA self-restoration, and error-control applications. Professional Affiliations: Senior IEEE member, ACM member, and licensed with the Ontario Society of Professional Engineers.

• Electrical Engineering
• Environmental Science
• Embedded Systems
• +۳ مورد دیگر

Prof. György Györök serves as a Professor and Dean at Óbuda University's Alba Regia Faculty. His work bridges electrical engineering, environmental science, and embedded systems. He leads research in analog circuit design, fault detection systems, and sustainable industrial processes. His recent studies include innovation ecosystem modeling (Triple Helix Model), FPAA applications in signal processing, and environmental impact assessments of industrial processes. Research interests focus on pragmatic electrical engineering solutions, machine learning-driven systems, and sustainable technology development. Notable areas include battery management systems for electric vehicles, real-time fault detection algorithms, and environmental impact analysis of manufacturing processes. His publications reflect interdisciplinary innovation, combining hardware-software co-design with environmental and educational technology applications. He has pioneered FPAA-based measurement tools and smart monitoring systems for industrial and academic use. No awards are explicitly mentioned, but his extensive publication record indicates significant contributions in technical fields. As dean, he oversees academic governance while maintaining active research in embedded systems and sustainable engineering. Collaborations likely involve industry partners given his focus on pragmatic engineering solutions. His work integrates cutting-edge technologies like neural networks with traditional analog circuit design for real-world applications.

Francesco Da Rosمشاهده پروفایل

دانشیار

• Optical Computing
• Optical Machine Learning
• Nonlinear Optics
• +۶ مورد دیگر

Francesco Da Ros is an Associate Professor at the Technical University of Denmark , Department of Electrical and Photonics Engineering. His work focuses on machine learning applications in photonic systems, particularly in optical communication and photonic computing. Active in silicon photonics and nonlinear optics Key contributor to optical machine learning and digital signal processing Research Interests: Da Ros explores the intersection of machine learning and photonics , with specific projects involving: Photonic reservoir computing End-to-end optimization of optical communication systems Neuromorphic photonic circuits Channel equalization techniques Quantum communication systems Thermal crosstalk compensation in integrated photonics Scientific Contributions: His research has produced over 245 publications and 23 projects , including significant work on: Raman amplifier optimization Machine learning for optical matrix multipliers Frequency comb phase noise characterization Security systems using distributed acoustic sensing Awards: Recipient of prestigious awards such as: Best Young Italian Researcher in Denmark (2019) DOPS Prize (2017) Horizon Prize for Breaking Optical Transmission Barriers (2016) Academic Leadership: Actively supervises PhD students in projects related to: End-to-end learning for multi-core fiber systems Nonlinear fiber-optic channel optimization Quantum communication lasers Integrated quantum photonic reservoir computing

Frances Clearyمشاهده پروفایل

استاد پژوهشی

• Artificial Intelligence
• Healthcare Innovation
• Smart Transport Systems
• +۷ مورد دیگر

Dr. Frances Cleary is the Head of Research Division (MEPS) at the Walton Institute, SETU, Ireland. She leads the Mobile Ecosystem and Pervasive Sensing (MEPS) division focusing on healthcare e-textiles, AI, 5G/6G, smart transport, and VR/AR. She has over 20 years of experience in roles spanning test engineering, business development, and technical leadership. Education: PhD in Royal College of Surgeons in Ireland (RCSI) Bachelor of Technology in Electronic Engineering from Waterford Institute of Technology Research Interests: Frances' work spans healthcare innovation, cybersecurity, smart transport systems, and emerging technologies like e-textiles and neuromorphic computing. Her division combines AI, NLP, and pervasive sensing to address challenges in healthcare and urban mobility. Recent Articles: Her 2024 publications include reviews on XR interventions for autism and epileptic seizure detection devices. In 2023, she explored AI-driven e-textiles and soft exosuits. Earlier works focus on 5G networks, cybersecurity frameworks, and smart transport systems. Grants & Funding: She has secured EU and national-level funding for cluster projects and digital innovation initiatives. Her team collaborates with industry partners to drive knowledge transfer. Labs & Activities: Frances organizes events like the Digital Education Conference 2024 and participates in conferences like ICIC24. She mentors researchers in her division and oversees lab management for experimental facilities and prototyping.

Almir Maricمشاهده پروفایل

دانشیار

• Physical Channel Modeling
• Communication Channel Characterization
• Fading Channels
• +۵ مورد دیگر

Almir Maric is an Associate Professor at the Department of Telecommunications, Faculty of Electrical Engineering, University of Sarajevo. He holds a PhD in Telecommunication Engineering from the same university (2020), preceded by a Master’s (2013) and Bachelor’s (2010) in the same field. His research focuses on geometric-based stochastic channel modeling, communication channel characterization, and fading channel simulation. He has contributed to renowned journals like Wireless Networks and IEEE Communications Surveys & Tutorials , as well as conferences such as the International Conference on Information, Communication and Automation Technologies (ICAT). His work spans topics including composite fading models, error probability analysis in digital modulation, and quantum cryptography in 5G networks. Education: Bachelor’s (2010), Master’s (2013), PhD (2020) in Telecommunication Engineering, University of Sarajevo Maric’s research trends emphasize statistical channel modeling, stochastic processes in wireless systems, and network security in software-defined networks. Notable contributions include the Best Paper Award at the MCSS’17 conference for his work on quantum key distribution signaling protocols. Awards: Best Paper Award at MCSS’17 (2017) His publications reflect a blend of theoretical and applied research, with collaborations on books such as Zbirka zadataka iz mikrotalasnih komunikacija (2020). His work bridges fundamental channel modeling with practical applications in 5G and quantum communication systems.

• Remote Access Laboratories
• Engineering Education
• Robotics
• +۳ مورد دیگر

Associate Professor Andrew Maxwell is affiliated with the School of Engineering at the University of Southern Queensland, specializing in Electronics and Communications Engineering. His research focuses on remote access laboratories, engineering education innovation, and interdisciplinary applications in robotics and biomedical science. He holds a BEng and PhD from USQ. His research interests span telecommunication systems optimization, augmented reality integration in labs, and curriculum development aligning with future professional needs. Over 14233 downloads of his outputs highlight his impactful work in STEM education and engineering technologies. Recent articles explore AI-driven pedagogy, spider population monitoring via vibration, and 3D bioprinting in biomedical education. His work emphasizes bridging theory-practice gaps through remote experimentation and immersive technologies. No scientific awards are explicitly mentioned, but his contributions have been widely accessed globally. He has advised on numerous educational technology projects and contributed to open-source frameworks like RALfie for remote lab management. Labs/Teams: Core contributor to RALfie platform development and international collaborations in STEM education technology.

• Computer Science
• Information Systems
• Formal Methods
• +۵ مورد دیگر

Keijo Tapio Heljanko is a Professor in the Department of Computer Science at the University of Helsinki, affiliated with the Helsinki Institute for Information Technology and the EUROFusion Advanced Computing Hub. He previously held an Associate Professor position at Aalto University (2008–2018) and currently serves as Principal Investigator at HIIT. His research focuses on formal methods, parallel computing systems, machine learning applications, and GPU architecture optimization. He leads the LUMI AI Factory project (2025–2028), an EU-funded initiative for AI infrastructure development. Education details are not explicitly listed in the provided text. His work spans theoretical computer science and applied machine learning, with notable contributions to bike-sharing optimization, GPU consistency analysis, and boreal ecosystem modeling. Media highlights include collaborations with NVIDIA on AI technology centers and innovations in search engine and disinformation detection systems. Professional roles include supervising the Doctoral Programme in Computer Science and managing multi-institutional research projects. He has collaborated internationally on topics ranging from exascale computing to environmental data analysis. His research outputs total 131 publications and 9 press engagements, emphasizing both foundational and applied computational challenges.

• Networking
• Communications
• Cybersecurity
• +۵ مورد دیگر

Martin Reisslein is a Professor at Arizona State University's School of Electrical, Computer and Energy Engineering. His research focuses on advanced networking technologies, cybersecurity, and edge computing, with a specialization in Time-Sensitive Networking (TSN), 5G, and network coding. He collaborates closely with institutions like the National Research Data Infrastructure (NFDI) and has published extensively in top-tier journals and conferences. His work spans theoretical and applied domains, including hardware-software co-design for low-latency systems, cybersecurity for satellite and IoT networks, and AI-driven resource management in transportation networks. Recent projects highlight contributions to TSN testbeds, molecular communication simulations, and unified threat management systems for home networks. Reisslein has co-authored over 270 publications, with notable contributions in IEEE Transactions on Networking, Communications Surveys & Tutorials, and the Journal of Signal Processing Systems. His research emphasizes practical implementations, such as hardware-aligned TSN simulations and flexible measurement frameworks for edge computing.