جست‌وجوی استاد و پژوهشگر

• Computational Fluid Dynamics (CFD)
• Turbulence Simulation
• Wind Farm Optimization
• +۵ مورد دیگر

Professor Sylvain Laizet is a faculty member in the Department of Aeronautics at Imperial College London, part of the Faculty of Engineering. He holds a PhD and Habilitation à Diriger des Recherches from the University of Poitiers in France, specializing in Computational Fluid Dynamics (CFD). His research focuses on turbulent flows and their engineering applications, including wind farm optimization, quantum algorithms for fluid mechanics, and machine learning integration in CFD. Key research areas include: Wake-to-wake interaction in wind farms Bayesian optimization for drag reduction and energy efficiency Immersed boundary methods for moving objects Quantum computing for solving PDEs in fluid dynamics His work leverages high-order numerical methods and large-scale simulations, with contributions to frameworks like Xcompact3D and WInc3D. Recent publications emphasize quantum algorithms, turbulence entrainment, and data-driven optimization strategies for renewable energy systems. Scientific contributions span over 50 peer-reviewed articles in top-tier journals, focusing on advancing CFD methodologies and their applications in environmental and industrial fluid mechanics. His team collaborates globally, including partnerships in France and Brazil.

Amer Qounehمشاهده پروفایل

دانشیار

• Computer Architecture
• High-performance Computing
• Data Centers
• +۲ مورد دیگر

Amer Qouneh serves as an Associate Professor in the Department of Electrical and Computer Engineering at Western New England University, where his research centers on computer architecture, high-performance computing, data centers, Internet of Things (IoT), and embedded systems with emphasis on energy efficiency and practical implementations. Education: Ph.D. in Computer Engineering, University of Florida, 2014 M.S. in Computer Engineering, University of Florida, 2010 M.S. in Computer Science, University of Wisconsin-Milwaukee, 2007 M.S. in Electrical Engineering, Fairleigh Dickinson University, 1988 B.S. in Electrical Engineering, Fairleigh Dickinson University, 1985 Dr. Qouneh's research integrates theoretical innovation with real-world applications across multiple domains. His computer architecture work addresses thermal resilience in photonic networks and processing-in-memory systems, while his data center research focuses on renewable energy integration, resource allocation, and containerization. In IoT and embedded systems, he develops practical solutions like solar array trackers and edge-based machine learning deployments, demonstrating a commitment to sustainable and accessible technology education. Publication analysis from 2009-2022 reveals a strategic evolution from foundational work in transactional memory and containerization toward advanced energy-efficient architectures. His recent output emphasizes IoT educational integration and embedded AI applications, maintaining consistent contributions to top venues like IEEE Transactions on Parallel and Distributed Systems while adapting to emerging computational challenges in green computing and edge intelligence. Dr. Qouneh actively mentors undergraduate researchers, evidenced by multiple co-authored conference papers on IoT implementations and curriculum development. His scholarly impact spans both technical innovation in data center optimization and educational leadership in modernizing engineering curricula for emerging technologies.

• Microwave Engineering
• Semiconductor Device Modeling
• Nonlinear Circuit Analysis
• +۳ مورد دیگر

Giorgio Vannini is a Full Professor of Electronics at the Department of Engineering, University of Ferrara, where he has been since 2005. His academic career spans over three decades, with prior roles as a Research Fellow and Associate Professor at the University of Bologna. He has held leadership positions including Head of the Engineering Department (2007-2015) and membership in the Academic Senate (2012-2015). Education: Laurea in Electronic Engineering from the University of Bologna (1987), Ph.D. in Electronic and Computer Science Engineering from the University of Bologna (1992). Research: Focused on nonlinear semiconductor device modeling (e.g., GaN HEMTs, III-V FETs), advanced microwave circuit design, and electromagnetic simulation techniques. Key contributions include the Nonlinear Integral Model (NIM) and dynamic I/V characterization systems. Awards: Best Paper Awards at the European Microwave Conference (1995), GAAS98 (1998), and GAAS2001 (2001). Projects: Led over 20 research contracts with industry leaders like Leonardo, Sumitomo, and Huawei, and participated in EU Framework Program initiatives including TARGET and Eurostars. Spin-off: Co-founded MEC srl, an academic spin-off for microwave engineering solutions.

• Chaos theory
• Compressed sensing
• Electromagnetic interference
• +۱۴ مورد دیگر

Fabio Pareschi is an Associate Professor at the Department of Electronics and Telecommunications (DET), Politecnico di Torino, where he conducts research in circuit architectures, embedded systems, and signal processing with applications in security, AI, and power electronics. He is affiliated with the VLSILAB research group and leads multiple high-impact research projects. Research Interests: Chaos theory and true random number generation for cryptographic applications Compressed sensing for secure and efficient signal acquisition EMI reduction techniques in DC-DC power converters Tiny machine learning and low-power embedded systems Circuit design for IoT and biomedical applications The recent articles highlight a strong trend in integrating compressed sensing with encryption, leveraging chaos-based randomness for security, and optimizing power electronics for EMI reduction. His work bridges theoretical foundations with practical hardware implementations in microelectronics and embedded systems. Scientific Awards: Best Student Paper Award (IEEE, 2005) Best Paper Award (IEEE, 2005) IEEE PRIME Gold Leaf Certificate (2019) BioCAS Transactions Best Paper Award (2019) Best Student Paper Award at EMCCompo (IEEE, 2019) Advising and Grants: He supervises multiple PhD students in the Electrical, Electronics, and Communications Engineering program. He is the Scientific Director of the CESOIA project (Non-EU International Research, 2025–2028) on low-complexity AI models, and leads the ECS4DRES project (EU-funded, 2024–2027) on resilient energy systems. He also heads a commercial research project on high-performance DC-DC converters (2022–2025). His editorial roles include Associate Editor for IEEE Transactions on Circuits and Systems and guest editorships in multiple IEEE journals. Labs and Teams: He is a key member of the VLSILAB Group (DET), which focuses on VLSI systems, embedded signal processing, and secure hardware design.

• Augmented Reality
• Robotics
• Human-Computer Interaction
• +۵ مورد دیگر

Ke Huo is a researcher focused on advanced interactions in Augmented Reality (AR) , Robotics , and Sensor Systems . His work bridges physical and digital environments through innovative tools like GhostAR , V.Ra , and iSoft , enabling intuitive authoring of context-aware applications. Research Interests : Augmented Reality (AR) systems for collaborative task planning Soft sensor technology with multimodal sensing Context-aware robotics and IoT integration 3D design ideation in mixed reality Autonomous driving decision-making frameworks Publication Trends : 2014–2024: 15+ papers on AR, sensor design, and human-robot collaboration Key venues: UIST , CHI , Sensors , ACM DIS Collaborations with Karthik Ramani, Yuanzhi Cao, and Sang Ho Yoon

• Renewable Energy Systems
• Artificial Intelligence
• Electrical Energy and Power Systems
• +۱ مورد دیگر

Dr. Oğuz Taşdemir serves as a Lecturer in the Department of Electrical and Electronics Engineering at Kırşehir Ahi Evran University's Faculty of Engineering and Architecture since 2025, following his tenure as full-time teaching staff at the university's Kaman Vocational School (2017-2025). His academic foundation includes PhD and MSc degrees in Electrical and Electronics Engineering from Gazi University and Nevşehir Hacı Bektaş Veli University respectively. His educational credentials: PhD in Electrical and Electronics Engineering, Gazi University (2020-2024) MSc in Electrical and Electronics Engineering, Nevşehir Hacı Bektaş Veli University (2017-2020) BSc in Electrical and Electronics Engineering, Kırıkkale University (2009-2010) Taşdemir's research integrates artificial intelligence with renewable energy systems, specializing in photovoltaic/wind power prediction, distributed generation optimization, and electrical facility analysis. His methodology leverages metaheuristic algorithms (JAYA, PSO, ABC) and neural networks to enhance renewable energy forecasting accuracy and power system efficiency, with particular emphasis on environmental factors like PM10 particulates and seasonal variations affecting solar/wind output. His 12 publications (2021-2025) reveal a concentrated research trajectory: 70% focus on AI-driven renewable energy solutions (primarily photovoltaics), 20% on power system optimization, and 10% on electrical control systems. The works demonstrate progressive technical sophistication from foundational microgrid studies (2021) to recent innovations in bifacial PV analysis and hybrid storage optimization (2025), consistently applying computational intelligence to energy challenges. As academic advisor, he has co-supervised two master's theses on photovoltaic forecasting and power system optimization. His research portfolio includes six projects: principal investigator for a TÜBİTAK-funded study on bifacial photovoltaic panels (2025-2027), and researcher roles in five projects addressing PV cooling techniques, hydrogen heating systems, and battery comparisons. His teaching encompasses core electrical engineering courses including Power Transmission, Fault Analysis, and Electromechanical Control Systems.

• Quantum Computing
• Hybrid Quantum-Classical Algorithms
• Workflow Scheduling
• +۳ مورد دیگر

Katarzyna Rycerz is a Lecturer at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, Poland. She holds the academic rank of Lecturer as part of the assistant professors group, with her office located at D-17, ul. Kawiory 21, room II, 3.54. Her research spans quantum computing, hybrid quantum-classical algorithms, and distributed systems, with significant contributions to workflow scheduling and complex network optimization. Dr. Rycerz's primary research focuses on quantum optimization techniques, particularly quantum annealing and variational algorithms applied to combinatorial problems. Her work bridges theoretical quantum computing with practical high-performance computing challenges, including load rebalancing in HPC systems and community detection in complex networks. She has developed software tools like QHyper for hybrid quantum-classical optimization and explored quantum solutions for thermoelectric properties in graphene and quantum game theory paradoxes. Her 15 most recent publications (2019-2025) reveal a dominant trend toward quantum-classical hybrid methods, with 80% focused on quantum annealing applications for workflow scheduling, network analysis, and optimization problems. Key themes include D-Wave system implementations, quantum game theory extensions, and thermoelectric material simulations, demonstrating a consistent shift from earlier multiscale simulation work toward cutting-edge quantum computing applications. No scientific awards are documented in the available information. Details regarding student advising, research grants, laboratory affiliations, or collaborative teams are not provided in the source materials.

Gil Bubمشاهده پروفایل

دانشیار

• Cardiovascular Research
• Cardiac Dynamics
• Imaging Techniques
• +۳ مورد دیگر

Gil Bub is an Associate Professor in the Department of Physiology at McGill University, focusing on cardiovascular research and cardiac dynamics. His lab develops advanced imaging and computational methods for studying excitable cell networks in heart and brain tissues. Current research involves high-speed microscopy technologies (Temporal Pixel Multiplexing, RAP imaging, remote focusing) and optogenetic techniques to control and image cardiac excitation patterns. Teaching includes the course Mathematical Models in Biology (BIOL 309) , with supplementary tools like cellular automata and logistic map iterators. Research themes explore excitable media, spiral wave dynamics, and real-time optical control of cardiac tissue. The lab combines bioengineered myocyte sheets, co-cultures, and whole-heart models with novel microscopy and simulation programs. Instrumentation projects include ultra-fast sensors, three-photon microscope prototypes, and parallel imaging systems for high-throughput screening. Optogenetics work collaborates with Emilia Entcheva's COOL lab to sensitize tissues to light control, enabling precise manipulation of wave patterns and rhythms. Lab members include postdocs, PhD/MSc students, and undergraduate trainees. Prior students have pursued careers in academia, medicine, and industry. Collaborators span institutions including Oxford, UBC, and industry partners like Cordin Scientific Imaging.

Erivelton Nepomucenoمشاهده پروفایل

دانشیار

• Computer Arithmetic
• Chaotic Cryptography
• Green Computing
• +۶ مورد دیگر

Erivelton Nepomuceno is an Associate Professor at Maynooth University's Faculty of Science & Engineering , affiliated with the Hamilton Institute and Centre for Ocean Energy Research . He holds a PhD in Electrical Engineering from UFMG (2005) and has held visiting positions at Imperial College London, Saint Petersburg Electrotechnical University, and City, University of London. Educational Background BEng, UFSJ (2001) PhD, UFMG (2005) Research Interests Computer Arithmetic Chaotic Cryptography Green Computing Ocean Energy Sustainable Circuits and Systems System Identification His recent publications focus on computational chaos, reinforcement learning applications, and sustainable energy systems. His work bridges chaos theory , cybersecurity , and renewables , with a strong emphasis on energy transition and finite-precision arithmetic challenges. Scientific recognitions include Senior Member of IEEE and Chair-Elect of IEEE Technical Committee on Nonlinear Circuits and Systems . He has served as Deputy Editor-in-Chief for multiple IEEE journals and currently holds associate editor roles. Erivelton supervises 5 active PhD students and has advised 7 PhD completions. His funded projects include studies on hybrid wind-wave energy control (€587,975.18), green computing (€3,700), and chaotic system simulation (€7,500). He leads the Hamilton Institute's research group on computational chaos and sustainable systems.

• Wide-bandgap semiconductor devices
• GaN power devices
• Semiconductor device physics
• +۶ مورد دیگر

Dr. Hua Mengyuan is an Associate Professor in the Department of Electronic and Electrical Engineering at Southern University of Science and Technology (SUSTech), where she has been conducting research since September 2018. She was promoted to Associate Professor in May 2024 after serving as an Assistant Professor from 2018 to 2024. Prior to joining SUSTech, she completed a postdoctoral fellowship at The Hong Kong University of Science and Technology (HKUST) from 2017 to 2018. Dr. Hua received her PhD in Electronic and Computer Engineering from HKUST (2013-2017) and earned her B.Sc. in Physics from Tsinghua University (2009-2013). Her academic journey reflects a strong foundation in both physics and electronic engineering, which informs her interdisciplinary research approach. Dr. Hua's research focuses on wide-bandgap semiconductor devices, particularly GaN-based power devices. She investigates device fabrication, material characterization, device physics, and reliability/stability issues. Her work spans fundamental semiconductor physics to practical applications in power electronics. The research encompasses both experimental and computational approaches, including 2D device simulation and modeling. Her group explores novel materials like Ga 2 O 3 monolayers and heterostructures for next-generation electronic applications. Analysis of Dr. Hua's recent publications reveals a strong focus on reliability mechanisms in GaN power devices, particularly threshold voltage instability and dynamic on-resistance issues. Her work increasingly incorporates computational methods, including machine learning potentials for material simulation. There's a clear progression toward exploring novel 2D materials and heterostructures, particularly involving gallium oxide and related compounds, for both electronic and optoelectronic applications. 2017 IEEE ISPSD Charitat Award (Best Young Scholar Award) 2018 Shenzhen Overseas High-Caliber Personnel 2017-2023 IEEE Trans. Electron Devices Golden Reviewer 2018-2023 IEEE Electron Device Lett. Golden Reviewer 2020 IEEE ICSICT Outstanding Youth Scientific and Technological Paper Award National Special Support Program for High-level Talents, 2023 Dr. Hua actively mentors students and researchers, recruiting PhD students, master's students, research assistants, and postdoctoral fellows to her group. Her research has been supported by provincial and ministerial projects, including two projects she has presided over. She serves as an editor for IEEE Trans. Electron Devices and has applied for six invention patents. Her group is currently working on next-generation wide-bandgap semiconductor device research with applications in power electronics and miniaturized power supplies. Dr. Hua's research group operates within the College of Engineering at SUSTech, utilizing advanced semiconductor fabrication and characterization facilities. Her team collaborates with international researchers, as evidenced by publications with colleagues from institutions like HKUST. The group maintains strong connections with the global semiconductor research community, regularly presenting at leading conferences including IEDM and ISPSD.

Roar Skogstromمشاهده پروفایل

مدرس ارشد

• Adaptive systems
• Reconfigurable hardware
• Robotics
• +۲ مورد دیگر

Roar Skogstrom serves as a Senior Lecturer at the University of Oslo, where he is actively affiliated with the Robotics and Intelligent Systems Research Group (ROBIN). His academic role centers on advancing research and education in intelligent systems within the university's technical framework. Skogstrom's research portfolio prominently features adaptive systems that dynamically respond to environmental changes, reconfigurable hardware architectures enabling real-time circuit modification, and robotics applications integrated with artificial intelligence. His work leverages evolutionary computation principles to optimize system design and functionality, creating synergies between hardware reconfigurability and intelligent control mechanisms. This interdisciplinary approach bridges theoretical computer science with practical engineering solutions for autonomous systems. The ROBIN research group provides Skogstrom's primary collaborative environment, focusing on cutting-edge developments in robotics and intelligent systems through cross-disciplinary initiatives that integrate machine learning, hardware design, and adaptive control methodologies.

• Internet of Things
• Computer Networks
• Neural Networks

Dr. Timenko Artur Valentynovych serves as Senior Lecturer at Zaporizhia National Technical University's Department of Computer Systems and Networks within the Faculty of Computer Science and Technologies. Holding a specialist degree in Computer Systems and Networks (2010), he maintains active roles in both teaching and research. His educational background includes graduation from Zaporizhia National Technical University in 2010 with specialization in Computer Systems and Networks. Professional development is evidenced through continuous research output and curriculum development activities. Research focuses on Internet of Things , computer networks , and neural networks , with particular emphasis on protocol verification, device interoperability, and embedded system optimization. Recent work explores semantic chatbots for IoT management, air quality monitoring systems, and MQTT protocol compatibility analysis. His methodology integrates formal verification techniques with practical hardware implementation. Publication trends from 2020-2024 reveal consistent contributions to IoT infrastructure (45%), network protocols (30%), and AI applications (25%). Key journals include Shipbuilding & Marine Infrastructure and Scientific Notes of Vernadsky University. Research demonstrates strong industry relevance with applications in smart homes, environmental monitoring, and critical systems. Teaching responsibilities encompass Python programming basics, computer network design, IoT fundamentals, and wireless technologies. His laboratory guidelines for Embedded Computer Systems and IoT disciplines reflect practical, hands-on pedagogy. Current projects involve developing automated temperature control systems and network anomaly detection using hybrid neural networks. Professional activities include active participation in Ukrainian academic conferences and international collaborations through ZNTU's research infrastructure. His work contributes to the university's strategic focus on digital innovation and sustainable technology development.

• High-performance computer architectures
• Cloud-computing systems
• Internet-of-Things (IoT)
• +۷ مورد دیگر

Panayiotis D. Tsanakas is a Professor of Computer Engineering at the National Technical University of Athens (NTUA), serving in the School of Electrical and Computer Engineering within the Department of Information Technology and Computers. Since 2023, he has held the position of Dean of the School of Electrical and Computer Engineering at NTUA. His academic career spans several decades with significant contributions to computer engineering and informatics. His educational background includes a Dipl. in Electrical Engineering from Aristotle University of Thessaloniki (1982), an MSc in Computer Engineering from Ohio University (1985), and a PhD in Computer Engineering from National Technical University of Athens (1988). Tsanakas specializes in high-performance computer architectures, cloud-computing systems, Internet-of-Things (IoT), and AI-based applications in medicine and biology. His research spans parallel and distributed processing, computer architecture, supercomputing applications, and biomedical engineering. He has published over 100 research papers in established scientific journals and conferences, with recent work focusing on AI applications in healthcare, cloud computing security, and advanced medical monitoring systems. His recent publications demonstrate a strong trend toward applying artificial intelligence to healthcare challenges, particularly in mental health monitoring, medical imaging, and biomedical diagnostics. His work frequently combines computer architecture expertise with medical applications, creating innovative solutions for healthcare challenges. 2023-now: Dean of the School of Electrical and Computer Engineering at NTUA 2018-2020: Board member of the EuroHPC Joint Undertaking 2004-2019: Chairman of GRNET, the national research and education network 2005-2009: Member of EETT (The Hellenic Electronic Communications and Posts Regulator) Tsanakas has supervised eight doctoral dissertations and more than 50 diploma theses. He has co-authored seven textbooks on computer systems that have been adopted by several higher-education institutions. His professional experience includes significant roles in national infrastructure development, including leading the design and deployment of advanced networking and cloud services for Greek academic institutions and healthcare facilities.

• Cybersecurity
• Cyber Warfare
• Machine Learning
• +۷ مورد دیگر

Professor Shin Dong-gyu is a faculty member in the Department of Computer Engineering at Sejong University, where he leads research in cybersecurity, cyber warfare, and machine learning applications. He is affiliated with both the Cyber Warfare Research Institute and the Smart Convergence Technology Research Institute, directing the Multimedia & Internet Lab which has produced over 100 graduates since its founding in 1998. His students have gone on to work at government research institutes, corporate research centers, and mid-sized technology companies. Professor Shin's research focuses on cybersecurity with particular emphasis on cyber resilience, intrusion detection systems, malware analysis, cyber range development, and the application of machine learning to security challenges. His work bridges theoretical security frameworks with practical defense mechanisms, often incorporating military and national security applications. The research spans both defensive cybersecurity measures and offensive cyber operations analysis. His recent publications (2023-2025) demonstrate a consistent research trajectory in cyber resilience metrics, data sanitization against poisoning attacks, DNS security, layered defense approaches for critical infrastructure, and the integration of Zero Trust architecture with threat modeling frameworks like MITRE ATT&CK. His work shows increasing sophistication in applying deep learning techniques to security problems while maintaining focus on practical, implementable security solutions. Professor Shin actively mentors graduate students through doctoral dissertation research, master's thesis research, and specialized courses including Algorithms and Practice, Computer Vision and Deep Learning for Drones, and Special Topics in Smart Computing Technology. His teaching schedule indicates regular engagement with both master's and doctoral students.

Park Ki-hoمشاهده پروفایل

دانشیار

• Computer Architecture
• Embedded System Design
• IoT System Design
• +۴ مورد دیگر

Dr. Park Ki-ho is an Associate Professor at the Department of Computer Engineering, Sejong University. His research focuses on computer architecture, embedded systems, IoT systems, and low-power design methodologies. Academic Background: PhD in Computer Science from Yonsei University Professional Experience: Senior Engineer at Samsung Electronics, Post-Doctoral Research Associate at University of Utah Research Interests: Develops innovative solutions for sensor hub design , memory systems , and machine learning hardware acceleration . Key areas include: Non-Volatile Memory (NVM) management 3D Integrated Circuit memory bandwidth optimization Intelligent Edge Device architectures Hybrid Cache Architectures Model Compression Techniques On-Device AI Processing Recent Publications demonstrate expertise in in-memory acceleration , sparse matrix representation , and large language model inference . His work bridges theoretical advancements with practical implementations for IoT and AI applications.