جست‌وجوی استاد و پژوهشگر

• Electrical Engineering
• Electromagnetic Processes
• Electromechanical Systems
• +۳ مورد دیگر

Serhiy Mykhailovych Tykhovod is an Associate Professor and Head of the Department of Electrical Machines at the Electrotechnical Faculty of Zaporizhzhia Polytechnic National University. With a Doctor of Technical Sciences degree, he has been actively contributing to the university since 1986. His academic career spans several decades of teaching and research in electrical engineering disciplines. Dr. Tykhovod's research focuses on modeling of electromagnetic and electromechanical processes, with particular emphasis on transient phenomena in transformers and electrical circuits. His work bridges theoretical electrical engineering with practical applications, developing innovative computational methods for analyzing complex electromagnetic systems. His research has resulted in numerous publications and a textbook on transformer modeling using magnetoelectric equivalent circuits. His scholarly output demonstrates consistent focus on transient process analysis, magnetoelectric modeling, and computational methods in electrical engineering. The research shows progression from fundamental theoretical work to practical applications in transformer and converter systems, with increasing sophistication in numerical methods and computational approaches over time. Badge 'Excellent Educationist of Ukraine, 3rd degree' Dr. Tykhovod has taught key electrical engineering subjects including Theoretical foundations of electrical engineering, General electrical engineering, and Theory of electrical circuits. His academic leadership as department head has shaped electrical engineering education at the university for many years. While specific grant information isn't provided, his extensive publication record suggests successful research funding throughout his career. As Head of the Department of Electrical Machines, he leads academic and research activities focused on electrical machinery, transformer systems, and electromagnetic processes. His department likely serves as a center for both theoretical and applied research in electrical engineering at Zaporizhzhia Polytechnic National University.

Milan Marjanovićمشاهده پروفایل

استادیار

• Thermal Engineering
• Thermoenergetics
• Renewable Energy
• +۷ مورد دیگر

Milan Marjanović is an Assistant Professor at the Department of Mechanical Engineering, Faculty of Technical Sciences in Čačak, University of Kragujevac. Holding an M.Sc. in Mechanical Engineering, he teaches Thermodynamics, Applied Thermodynamics, Renewable Energy Sources, and Machine Elements. His research focuses on Thermal Engineering, Thermoenergetics, and Renewable Energy systems. Born 1990 in Užice Completed primary/secondary education in Požega Faculty of Mechanical Engineering and Civil Engineering, Kraljevo (2012) Master's in Energy Engineering (2014) Research spans biomass combustion optimization, solar energy systems, and hydraulic simulation tools. Active in academic projects like the national PRIZMA 2023 initiative for Active Condensation Hybrid Systems. Key publications include work on: Biomass-fired district heating efficiency AI-driven solar energy prediction models Hybrid photovoltaic-thermal collector testing Industry 4.0 curriculum development for Mechatronics Scientific contributions appear in journals like Case Studies in Thermal Engineering and conferences including COAST 2024. Awards include Ministry scholarships and 'Mašinijada' competition victories. Collaborates with industry partners on mechanical testing equipment development.

• Nonlinear Dynamics
• Bifurcation Theory
• Piecewise Smooth Systems
• +۷ مورد دیگر

Professor Viktor Avrutin is an extraordinary professor (Apl. Prof.) at the University of Stuttgart, Germany, affiliated with the Institute for Systems Theory and Automatic Control. He holds a Dr. rer. nat. habil. degree in Computer Science from the University of Stuttgart, where he was appointed as an extraordinary professor in 2020 after obtaining his Privatdozent status in 2011. Avrutin completed his academic journey with a B.Sc. from St. Petersburg State Polytechnical University (1992), an M.Sc. in Computer Science with Mathematics from the University of Stuttgart (1997), and a Ph.D. from the University of Stuttgart (2003) with a thesis on piecewise-smooth dynamical systems. His research focuses on nonlinear dynamics with particular emphasis on bifurcation theory for piecewise smooth systems, border collision and homoclinic bifurcations, low-dimensional chaos, and bifurcations of chaotic attractors (crises). He also investigates numerics, simulation software, algorithms, and neural networks. His work spans multiple disciplines including electrical engineering (power converters and inverters), mechanical systems (vibration machines), biological modeling (Goodwin's oscillator), and ecological systems (predator-prey models). Analysis of his recent publications reveals a consistent focus on piecewise smooth dynamical systems, with particular attention to border collision bifurcations, chaotic attractors, and their transformations. His research demonstrates strong interdisciplinary applications, connecting theoretical mathematics with practical engineering problems in power electronics, mechanical systems, and biological modeling. The recurring themes across his work include the study of complex nonlinear phenomena in systems with discontinuities, transformation of attractors, and the interplay between deterministic and stochastic elements in nonlinear systems. Professor Avrutin teaches courses including Nonlinear Dynamics and Chaos Theory I (summer term), Dynamics of Nonsmooth Systems, and Nonlinear Dynamics and Chaos Theory II (winter term) at the University of Stuttgart.

Behzad Abdolmalekiمشاهده پروفایل

استادیار

• Cryptography
• Post-Quantum Cryptography
• Zero-Knowledge Proofs
• +۷ مورد دیگر

Behzad Abdolmaleki is an Assistant Professor and member of the Security of Advanced Systems research group at the University of Sheffield . He focuses on cryptographic schemes in post-quantum and quantum settings, with applications to zero-knowledge proofs, cryptocurrencies, and concurrent systems. Previously, he held postdoctoral and senior researcher roles at the Max Planck Institute for Security and Privacy (MPI-SP) and the University of Tartu , and visited institutions like the AIT Austrian Institute of Technology and Friedrich-Alexander University of Erlangen-Nuremberg . Research Interests include constructing secure cryptographic protocols, with a focus on post-quantum foundations, zero-knowledge proofs, blockchain technologies, and universally composable security models. His work bridges theoretical cryptography with practical applications in secure systems. Scientific Awards Best Paper Award at CANS 2021 One of Three Best Papers at ASIACRYPT 2017 Grants DIDShield : A Privacy-Centric Approach to Digital Wallet Security (Innovate UK, 04/2025–07/2025, £22,757, as PI) Academic Services Program Committee member at IACR CiC (2025), ISDIA (2024), ASIACRYPT (2023), and others.

Théodore Cherriereمشاهده پروفایل

پژوهشگر

• Topological Optimization
• Electrical Machines
• Actuators
• +۳ مورد دیگر

Théodore Cherriere is a researcher at the Laboratory of Electrical and Electronic Engineering in Paris, specializing in topological optimization of electrical machines and actuators. His work focuses on advanced computational methods for designing rotating machines, magnetic circuits, and multi-material systems. Research Interests : Topological optimization of magnetic devices Finite element analysis for electrical machine design Multimaterial filtering techniques Magneto-mechanical interactions Density-based optimization methods Nonlinear material behavior modeling Key Article Trends : His recent publications emphasize multimaterial design strategies, geometric optimization without initial constraints, and novel filtering techniques to enhance magnetic flux efficiency in permanent magnet synchronous machines and reluctance motors.

• Hardware Security
• Embedded Systems Security
• Physically Unclonable Functions (PUFs)
• +۷ مورد دیگر

Jean-Luc Danger is a Professor at TELECOM Paris where he currently heads the Digital Electronic Systems Research Group. He is affiliated with the Secure and Safe Hardware (SSH) Research Team within the Information Processing and Communication Laboratory (LTCI). With a career spanning over three decades in academia after 12 years in industrial research at PHILIPS and NOKIA, Professor Danger has established himself as a leading expert in hardware security and cryptographic implementations. Professor Danger received his degree in electrical engineering from SUPELEC in 1981 before embarking on his industrial career. His academic journey began in 1993 when he joined TELECOM Paris, where he has since made significant contributions to the field of hardware security. His educational background in electrical engineering provided the foundation for his later specialization in secure hardware design and analysis. Professor Danger's research primarily focuses on embedded systems security , physically unclonable functions (PUFs) , side-channel attacks and countermeasures , and fault injection techniques . His work bridges the gap between theoretical cryptography and practical hardware implementations, addressing critical security challenges in modern computing systems. His research has evolved from foundational work on cryptographic algorithms to more recent investigations into hardware Trojans, aging effects on security primitives, and automotive security systems. Professor Danger has been particularly influential in developing methodologies for analyzing and protecting against electromagnetic fault injection attacks and side-channel information leakage. His extensive publication record demonstrates a consistent focus on hardware security challenges, with recent work showing increased attention to automotive security systems, machine learning applications for intrusion detection, and reliability issues in security primitives affected by aging and process variations. The trajectory of his research shows a natural progression from pure cryptographic implementations to more holistic security approaches that consider the entire hardware stack and its vulnerabilities. Through his leadership of the Secure and Safe Hardware research team, Professor Danger has fostered a collaborative environment that bridges theoretical security research with practical hardware implementation challenges. His work has contributed significantly to the development of standardized methodologies for evaluating hardware security and has influenced both academic research and industry practices in secure hardware design.

Farah Mohammadiمشاهده پروفایل

دانشیار

• Electro-thermal Analysis of Integrated Circuits
• RF and Microwave Circuit Design
• Applied Electromagnetics
• +۲ مورد دیگر

Farah Mohammadi is an Associate Professor in the Department of Electrical and Computer Engineering at Toronto Metropolitan University, where she has held a faculty position since 2003. Her prior academic experience includes a lectureship at Iran University of Science & Technology (1992-1993), followed by industry work as a Senior System Architect at Nortel Networks Laboratories in Ottawa (2000-2002). Her educational background features a B.Sc. and M.Sc. in Telecommunication Engineering from Iran University of Science & Technology (1988, 1991), and a Ph.D. in Electronic Engineering from the Institute d'Electronique et Microelectronique du Nord (IEMN) at the University of Science and Technology of Lille, France (1998). Research focuses on advanced electro-thermal analysis of integrated circuits, development of electro-thermal test tools, microwave circuits CAD, applied electromagnetics, and modeling of interconnects and packaging effects in high-speed circuits. Her work bridges theoretical electromagnetics with practical RF/microwave component design methodologies. Publication analysis (2008-2010) reveals consistent integration of thermal and electromagnetic modeling for ICs and microwave components, with significant contributions to electro-thermal simulation tools, thermal management of dual-core processors, and efficient CAD for RF/microwave circuits.

• Machine Learning
• Quantum Computing
• Computational Biology
• +۲ مورد دیگر

Lasse Bjørn Kristensen is a Research Fellow at the Department of Computer Science, University of Copenhagen, specializing in Machine Learning with a focus on quantum computing applications. Research Interests His work bridges quantum computing, machine learning, and computational biology, with contributions to: Quantum neural networks and spiking neurons Quantum error correction and circuit robustness Quantum chemistry simulations Information flow in parametrized quantum systems Notable Research Trends Kristensen's publications reveal a strong emphasis on quantum-classical hybrid models, entanglement-enhanced devices, and computational methods for chemistry and physics. His recent work explores error-driven learning paradigms and quantum eigensolvers. Contact Email: lakr@di.ku.dk Address: Universitetsparken 1, 2100 Copenhagen Ø

• Machine Learning
• Quantum Computing
• Natural Language Processing
• +۳ مورد دیگر

William Henrich Due serves as a Lecturer at the Department of Computer Science (DIKU), University of Copenhagen, within the Machine Learning section. His work intersects with the SCIENCE AI Centre and leverages the department's high-performance compute cluster for research in quantum computing, sustainable AI, and medical applications. Research focuses span quantum machine learning (biomolecular simulations, photonic processors), sustainable AI systems (energy efficiency, climate impact), and clinical applications (EEG analysis, medical imaging). His recent publications reveal strong activity in quantum-classical hybrid systems, with 8/15 recent papers addressing quantum computing challenges. The work emphasizes practical implementations in medical imaging and resource-constrained environments. His research aligns with DIKU's Machine Learning section priorities including medical imaging biomarkers and sustainable computing. Key infrastructure includes TreeSense for remote sensing and the department's dedicated compute cluster. No scientific awards were explicitly documented in the provided materials. Due contributes to DIKU's teaching mission as a Lecturer while engaging with the SCIENCE AI Centre's interdisciplinary initiatives. His work connects with medical imaging applications and quantum computing infrastructure development. Active in the Machine Learning section's research ecosystem, his work intersects with medical imaging analysis and quantum computing applications, utilizing specialized resources like TreeSense for environmental monitoring.

Giovanni De Carneمشاهده پروفایل

استاد

• Power Engineering
• Electrical Power Systems
• Smart Grids
• +۳ مورد دیگر

Prof. Giovanni De Carne is a Professor at the Department of Electrical Engineering and Information Technology (ETIT) at the Karlsruhe Institute of Technology (KIT). His research focuses on real-time systems in power engineering, energy storage systems, smart grid technologies, and advanced power electronics. He specializes in developing innovative solutions for grid integration of renewable energy sources, including solid-state transformers, DC microgrids, and hybrid energy storage systems. His work addresses challenges in grid stability, load management, and cybersecurity for modern power systems. De Carne leads research initiatives such as KARA, KITTEN, and EL2.0, which explore digital twins for particle accelerators and sustainable energy management. His contributions include advancements in power hardware-in-the-loop testing, voltage and frequency control strategies, and the application of machine learning in superconductivity. He has published extensively on topics like energy storage optimization, DC fast charging infrastructure for electric vehicles, and fault-tolerant grid operations. Key areas of expertise include: Smart transformer design and grid integration DC/AC converter technologies Real-time system simulation and validation Renewable energy system modeling Grid stability and resilience enhancement His research has been applied to improve grid-edge control, mitigate disturbances in power systems, and optimize energy storage solutions for high-renewable grids. De Carne's work bridges theoretical advancements with practical implementation, contributing to sustainable energy infrastructure and grid modernization efforts.

Matthew Nicolمشاهده پروفایل

استاد

• Ergodic Theory
• Dynamical Systems
• Probability Theory
• +۳ مورد دیگر

Matthew Nicol is the John and Rebecca Moores Professor in the Department of Mathematics at the University of Houston. His career includes positions at UMIST, University of Surrey, and visiting appointments at Warwick and New Mexico State. Research specialties encompass ergodic theory, dynamical systems, probability, and extreme value theory. His work applies mathematical frameworks to climate science, medical imaging, and statistical mechanics. Notable publications examine hurricane modeling, nonstationary extremal analysis, and surgical planning algorithms. He received the Leverhulme Trust Research Fellowship (2002-2003). Publication analysis reveals interdisciplinary applications across: Dynamical systems and statistical mechanics Extreme event modeling for climate phenomena Medical applications of mathematical modeling Probability theory in chaotic systems

Paul Lowمشاهده پروفایل

استاد

• Organometallic Chemistry
• Molecular Electronics
• Quantum Interference
• +۳ مورد دیگر

Paul Low is a Professor and Head of School in the School of Molecular Sciences at the University of Western Australia (UWA). He holds titles including FRSC, FRACI, and CChem, and has held previous academic positions such as Professor of Chemistry at Durham University, UK. His research focuses on organometallic chemistry and molecular electronics, with particular emphasis on single-molecule junctions, quantum interference effects, and nanotechnology applications. Education B.Sc (Double Major in Chemistry) from University of Adelaide (1992) B.Sc(Hons) from University of Adelaide (1993) PhD in Inorganic Chemistry from University of Adelaide (1997) Research Interests Professor Low’s work explores molecular electronics, organometallic complexes, and quantum interference in molecular systems. He investigates novel materials for electronics applications, including molecular wires, conductance modulation, and device fabrication. His research integrates experimental and computational methods to understand electronic properties at the molecular scale. Grants & Collaborations ARC Discovery Projects (2019–2022): Molecular transistors and radical-based components for electronics ARC Future Fellowship (2012–2016): Molecular electronics platforms Collaborations with global institutions on projects like gold-graphene heterojunctions and CO₂ foundries Awards H.G. Smith Memorial Medal (2020) Friedrich Wilhelm Bessel Research Award (2015) Teaching & Outreach He teaches undergraduate courses in chemistry and mentors students through UWA’s scholarship programs. His outreach initiatives engage Indigenous youth in science through workshops like ‘Molecules, Models, and Morsels’. Labs & Teams His group collaborates with surface scientists, microscopists, and theoreticians to advance molecular electronics. Projects include building large-scale molecular junction arrays and developing CO₂ capture technologies.

Steven Herbertمشاهده پروفایل

مدرس

• Quantum Computing
• Quantum Algorithms
• Quantum Sensing
• +۳ مورد دیگر

Steven Herbert is an Affiliated Lecturer in the Department of Computer Science and Technology at the University of Cambridge, where he teaches the Part II Quantum Computing course. In addition to his academic role, he serves as Head of Quantum Algorithms at Cambridge Quantum and is a By-Fellow at Churchill College. His research focuses on quantum computing, quantum algorithms, and their applications in areas such as sensing, communications, and optimization. A central theme of his work involves developing and analyzing quantum algorithms for Monte Carlo integration, entanglement distribution, and network coding, with a particular emphasis on practical implementations on near-term quantum hardware. He has contributed to theoretical advancements regarding quantum-classical algorithm comparisons, noise-aware techniques, and reinforcement learning applications in quantum compilation. Herbert’s research also explores interdisciplinary applications of quantum computing, including data-centric engineering and scientific computing. He actively investigates the intersection of quantum technologies with machine learning, particularly in generative adversarial networks (GANs), and has pioneered methods to optimize quantum circuit design and resource utilization. His work often bridges foundational theory with practical hardware constraints, addressing challenges such as qubit routing, error mitigation, and algorithmic efficiency in restricted quantum architectures. Through his affiliation with Cambridge Quantum, he collaborates on real-world quantum computing projects, emphasizing the translation of theoretical insights into tangible applications. His contributions span academic publications, industry partnerships, and educational initiatives aimed at advancing quantum literacy and innovation.

• Computational Neuroscience
• Systems Neuroscience
• Neural Engineering
• +۷ مورد دیگر

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.

Monica Marinescuمشاهده پروفایل

دانشیار

• Electrochemistry
• Energy Storage Systems
• Battery Technology
• +۳ مورد دیگر

Monica Marinescu is a Reader in the Department of Mechanical Engineering at Imperial College London's Faculty of Engineering. Her research focuses on understanding the physical and chemical processes influencing energy storage devices, particularly lithium-ion, lithium-sulfur batteries, and supercapacitors. She develops electrochemical and physical models to identify degradation mechanisms under real-world conditions, with applications in electric vehicles, space missions, and ultra-cold climates. Her affiliations include Electrochemical Science and Engineering, Energy Materials, and Mechanics of Materials. She collaborates with Prof. Alexei Kornyshev and has contributed to advancements like the Revolutionary Electric Vehicle Battery and UAV Zephyr projects. Her work emphasizes modeling solvent consumption in SEI layer growth, validation of Li-S battery models, and optimal cell design strategies. Publications highlight her focus on lithium-ion battery degradation, thermal management, and high-throughput computing methods. She is an editorial board member and has published extensively on topics such as cycle aging analysis, equivalent circuit networks, and degradation mode diagnostics. Her research bridges fundamental electrochemistry with practical engineering solutions for sustainable energy storage systems.