جست‌وجوی استاد و پژوهشگر

Tiago Hekkertمشاهده پروفایل

پژوهشگر

• Control Systems
• Automation
• Real-time Systems
• +۳ مورد دیگر

Tiago Hekkert is a Researcher at INESC TEC's Centre for Power and Energy Systems since October 21, 2022, specializing in control systems and automation for energy applications. His work bridges theoretical physics and industrial implementation in nuclear fusion research. His educational foundation includes Engineering Physics training at Instituto Superior Técnico and professional development at the European Space Agency (ESA) in Noordwijk, where he gained hands-on expertise in software development, firmware engineering, and electrotechnics through practical space technology projects. Research focuses on real-time control architectures for plasma systems, with core competencies in ATCA standards, MARTe framework programming, and FPGA-based data acquisition. His technical approach integrates C++ development with hardware-level solutions for tokamak operations, emphasizing stability in alternating current discharges and diagnostic integration. Analysis of his 2014 publications reveals consistent specialization in extending tokamak operational capabilities through synchronized control systems. The research demonstrates cross-disciplinary methodology combining nuclear engineering constraints with real-time computing solutions, particularly advancing long-duration plasma exposure techniques relevant to fusion material testing. As part of INESC TEC's Power and Energy Systems Centre, he contributes to Portugal's energy research ecosystem through collaborations on fusion-relevant technologies, maintaining active development in control system architectures for next-generation plasma devices.

Jan Brederekeمشاهده پروفایل

استاد

• Embedded Systems
• Neural Networks
• FPGAs for Space
• +۷ مورد دیگر

Jan Bredereke is a Professor at Bremen University of Applied Sciences (HSB) in the Faculty of Electrical Engineering and Computer Science, where he specializes in Embedded Systems. He leads the Laboratory for Computer Technology and Digital Circuits, focusing on cutting-edge research in hardware and software integration for specialized computing applications. His research spans two major phases: current work on neural networks for space applications and time/space partitioning for avionics, and earlier foundational work on formal requirements specification, mode confusions in user interfaces, and feature interactions in telecommunications systems. Bredereke's research demonstrates a consistent thread of addressing complex system interactions and reliability concerns across different technological domains. His publication record shows significant contributions to both academic literature and practical applications, with recent work focusing on implementing neural networks on resource-constrained platforms for space applications. His earlier work established important frameworks for managing feature interactions in telecommunications systems, which remains relevant to modern software engineering challenges. Bredereke has maintained an active research profile for over two decades, with publications spanning journals, conference proceedings, and books. His work bridges theoretical formal methods with practical engineering concerns, particularly in safety-critical and resource-constrained environments.

Heiko Hinkelmannمشاهده پروفایل

استاد

• Embedded Systems
• Wireless Sensor Networks
• Energy Efficiency in Computing
• +۳ مورد دیگر

Prof. Dr.-Ing. Heiko Hinkelmann is a Professor at Frankfurt University of Applied Sciences and serves as a member of the FUTURE AGING Research Center office since 2016. Based in Building 8, Room 114, he leads initiatives in developing innovative assistance technology with emphasis on safety, trustworthiness, and user-friendliness for aging populations. His research spans embedded systems design and optimization across multiple domains: Hardware/software co-design of energy-efficient embedded systems Wireless Sensor Networks for real-time monitoring Field Programmable Gate Array (FPGA) implementation Digital circuit and camera system development End-to-end energy analysis from hardware to data processing The FUTURE AGING Research Center provides laboratory infrastructure for prototyping and practical validation of these systems, focusing on early-stage integration of safety and usability requirements in assisted living applications.

• Robotics
• Mechanical Engineering
• Energy Engineering
• +۳ مورد دیگر

Christoph Eck serves as a Professor at the Institute of Mechanical and Energy Engineering within the School of Engineering & Architecture at Lucerne University of Applied Sciences and Arts (HSLU) in Horw, Switzerland. His office is located in Room E309 at Technikumstrasse 21, with direct contact via +41 41 349 33 85. His research expertise spans Robotics, Mechanical Engineering, and Energy Systems with emphasis on practical implementations. Key initiatives include: SITA Better World Robotics for environmental sustainability Robot-based vegetation control in railway track maintenance Virtual Lucerne Robotics Center (vLRC) as a collaborative digital platform Energy-efficient wellness technologies development High-voltage line inspection robotics Earth's magnetic field recording systems While his 2009 publication on FPGA timing parameters indicates foundational work in digital design, current research demonstrates a strategic pivot toward applied robotics and energy solutions. This evolution reflects a strong focus on real-world engineering challenges with societal impact, particularly in infrastructure maintenance and sustainable technology. Professor Eck secures ongoing research funding across multiple projects, with the virtual Lucerne Robotics Center representing a cornerstone initiative for future innovation. His work actively bridges academic research and industrial applications through the Institute of Mechanical and Energy Engineering's CC Mechanical Systems division.

Mircea Stanمشاهده پروفایل

استاد

• Computer Engineering
• VLSI Design
• Low-Power Circuits
• +۶ مورد دیگر

Mircea R. Stan is the Virginia Microelectronics Consortium Professor of Electrical and Computer Engineering at the University of Virginia School of Engineering and Applied Science. He currently serves as Director of UVA's Computer Engineering Program, leading efforts to integrate interdisciplinary research in areas like AI/ML, IoT, and energy-efficient computing. His academic career includes 28+ years at UVA, where he has mentored 26 Ph.D. students and established the High-Performance Low-Power Lab. Educational Background: Earned Ph.D. and M.S. from University of Massachusetts Amherst (1990s), and a diploma from Polytechnic Institute in Bucharest, Romania. His research focuses on high-performance low-power VLSI systems, spintronic devices, and cross-layer resilience strategies. He is a Fellow of the IEEE and recipient of the NSF CAREER Award. Research Interests: Pioneers innovations in thermal-aware 3D-IC design (e.g., Cool-3D framework), magnetic racetrack memory, and energy-harvesting systems. Collaborates with the Link Lab (cyber-physical systems) and CRISP (in-memory computing). Current work emphasizes AI-driven hardware for edge computing and fault-tolerant architectures. Awards: Recognized for contributions to cross-layer resilience (CLEAR initiative), memory system reliability, and energy-efficient computing. His work bridges foundational research with practical applications in biomedical engineering and autonomous systems. Leadership: Served as interim director of NSF's Division of Translational Impacts (2022-2024) and led UVA's computer engineering program since 2022. Advocates for curriculum integration of AI/ML with traditional EECS disciplines. Spearheading faculty searches to expand capabilities in terahertz systems and neuromorphic engineering. Labs/Teams: Directs the High-Performance Low-Power Lab and collaborates with the Center for Research in Intelligent Storage and Processing in Memory (CRISP). His team develops open-source tools like PiMulator for PIM emulation and Grapefruit for FPGA-based automata processing.

Nisal Ranasingheمشاهده پروفایل

پژوهشگر

• Machine Learning
• Artificial Intelligence
• Neurodegenerative Diseases
• +۳ مورد دیگر

Nisal Ranasinghe is a Researcher in the Department of Mechanical Engineering at the University of Melbourne. His research focuses on Explainable AI, interpretable machine learning algorithms, and their applications in biomedical engineering and neurodegenerative disease analysis. He is supervised by Prof. Saman Halgamuge and Dr. Damith Senanayake, and affiliated with the Robotics research group. Education: BSc. Engineering (Electronic and Telecommunication Engineering), University of Moratuwa, Sri Lanka (2018). Research interests include developing interpretable ML models for equation discovery from data, analyzing electrophysiological signals in ALS, and applying AI across healthcare, agriculture, and telecommunications. Recent work emphasizes mathematical and statistical transparency in neural networks. Publications span interdisciplinary topics like biomedical AI, equation generation via graph models, and FPGA-based video transport systems. His work bridges computational science and practical applications in healthcare and engineering. No scientific awards listed. Active in collaborative projects involving robotics and interdisciplinary research teams.

• Wireless Positioning
• GNSS Algorithms
• Wearable Computing
• +۷ مورد دیگر

Prof. Simona Lohan is a Full Professor at the Electrical Engineering unit of Tampere University, Finland, and a visiting professor at Universitat Autònoma de Barcelona. Her research focuses on wireless positioning, GNSS algorithms, and wearable computing, with an emphasis on privacy-aware localization and interference mitigation. She leads the Signal Processing for Wireless Positioning research group and coordinates the H2020 MSCA European Joint Doctorate A-WEAR (2019-2023). She holds a PhD in Telecommunications from Tampere University of Technology (2003), and has authored/co-authored over 250 peer-reviewed publications. Education background includes an MSc in Electrical Engineering from Polytechnics University of Bucharest (1997), a DEA in Econometrics from École Polytechnique, Paris (1998). Her research spans satellite navigation (Galileo/GPS/GLONASS), UMTS/WCDMA positioning, 5G positioning, IoT localization, and medical applications of positioning systems. She is an associate editor for the RIN Journal of Navigation and IET Journal on Radar, Sonar, and Navigation . Key projects include the H2020 A-WEAR project (wearable health tech), Academy of Finland ULTRA (2020-2022), and SJU GATEMAN (2018-2019). Her work addresses global navigation challenges through LEO-PNT constellations, low-cost positioning solutions for Africa, and fusion of 5G/mmWave radar for airport surveillance. She has pioneered datasets like TUJI1 for indoor localization and developed open-source tools like SyDR for GNSS algorithm benchmarking. Her research themes include: LEO satellite-based positioning systems Anti-spoofing techniques for GNSS RF fingerprinting for device identification Privacy-preserving localization algorithms IoT and industrial internet applications Embedded signal processing systems Her team's innovations bridge communication and navigation domains, with applications in aviation, healthcare, and smart infrastructure. Recent work emphasizes energy-efficient GNSS signal processing and multi-constellation PNT solutions for global accessibility.

Alexandru DINUمشاهده پروفایل

مدرس

• Functional verification of ASICs
• Digital electronics
• Microcontrollers
• +۴ مورد دیگر

Alexandru Dinu is a Lecturer at the Department of Electronic and Computers within the Faculty of Electrical Engineering and Computer Science at the Technical University of Brasov. His research focuses on functional verification of ASICs, digital electronics, and AI integration in embedded systems. He has contributed to projects involving hardware reconfiguration, sensor peripherals, and cost-efficient verification methodologies. Research interests include: AI-driven hardware verification Microcontroller-based systems Functional coverage optimization Embedded systems programming His recent work explores automation in verification processes using genetic algorithms and reinforcement learning, with applications in FPGA-based sensors and energy management systems. Collaborations include industry-oriented laboratory redesign and educational platforms for alphabet learning. No scientific awards or grants are listed. Advising information is unavailable. Current affiliations include the Technical University of Brasov and participation in interdisciplinary projects spanning engineering education and environmental technology.

Daniel Tudor Cotfasمشاهده پروفایل

استاد

• Renewable Energy
• Photovoltaic Systems
• Hybrid Energy Systems
• +۵ مورد دیگر

Professor Daniel Tudor Cotfas is affiliated with the Department of Electronic and Computers at the Faculty of Electrical Engineering and Computer Science, University of Technical Education Bucharest. His research focuses on renewable energy systems, particularly photovoltaic (PV) and hybrid energy solutions. He explores topics such as solar thermoelectric generators, low-power sensor networks, and cybersecurity in IoT-integrated energy systems. His work emphasizes improving energy efficiency through advanced materials, optimization algorithms, and policy frameworks. Key research areas include dust impact on PV panel performance, parameter extraction for solar cells using metaheuristic algorithms, and virtual instrumentation for educational and industrial applications. He has contributed to remote laboratory systems and smart energy monitoring technologies. His publications address challenges in concentrated solar power, hybrid PV-thermoelectric systems, and energy harvesting for wireless sensors. Notable collaborations involve experimental setups for studying thermoelectric materials under concentrated light and developing frameworks for secure IoT integration in renewable energy infrastructure. Cotfas is also engaged in educational initiatives, leveraging LabVIEW and FPGA-based tools for hands-on learning in renewable energy and control systems.

• Educational Technology
• Artificial Intelligence in Education
• Digital Electronics
• +۳ مورد دیگر

Nikoletta Tolner is an Assistant Professor and Deputy Head of the Institute of Engineering at the Alba Regia Faculty of Óbuda University. Her research focuses on educational technology, artificial intelligence in academic environments, digital electronics, and e-learning frameworks. She holds a prominent role in shaping engineering education through innovative teaching methodologies and technology integration. Her work emphasizes practical applications such as AI-driven online proctoring systems, modular curriculum design using IT project management, and advancing digital circuit education through embedded systems and FPGA technologies. Tolner actively contributes to academic integrity research, exploring cheating motivations and strategies in modern educational settings. Publications span topics from teacher perceptions of AI integration to hardware-software co-design in engineering education. She maintains an accessible profile with an institutional email address and regularly updates her publication repository at MTMT .

• Computational Fluid Dynamics
• Numerical Simulation
• Parallel Computing
• +۳ مورد دیگر

Neil Kelson is a Professor at Queensland University of Technology (QUT), specializing in computational science and engineering. He holds a PhD in Engineering Mathematics from QUT (2000). His primary affiliations are within the Faculty of Science and Engineering, School of Mathematical Sciences. Research Interests: Dr. Kelson's work focuses on computational fluid dynamics (CFD), numerical simulation, and hardware-accelerated computing using FPGAs. He has pioneered methods for solving linear systems on heterogeneous architectures and has contributed to biomedical engineering through CFD applications in aneurysm analysis and heart pump design. His recent work emphasizes parallel computing and FPGA-based algorithms for real-time systems. Key Contributions: Over 78 publications span topics like tridiagonal linear solvers (2019), MHD flow modeling (2018), and FPGA hardware implementations (2012–2016). His CFD research addresses agricultural fumigation (2016) and biomedical devices like biventricular assist devices (2006–2009). He has also developed educational frameworks for computational science curricula (2013). Grants and Collaborations: Collaborations include projects on FPGA-based UAV path planning (2012), ECG signal processing (2014), and turbulence modeling (1990s–2000s). No explicit grants are listed in the provided texts. Labs/Teams: While specific labs aren't mentioned, his work aligns with QUT's computational engineering and mathematical sciences research groups. He has advised on FPGA and CFD-related projects across academia and industry.

Loïc Lagadecمشاهده پروفایل

استاد

• CAD tools for FPGAs
• Homomorphic Encryption
• Cybersecurity
• +۵ مورد دیگر

Loïc Lagadec is a Professor in Computer Science at ENSTA-Bretagne, an engineering school in Brest, France, where he serves as Assistant Head of Research Delegate for Cybersecurity Activities and is a member of LabSticc. His career spans academic leadership, research in reconfigurable architectures, cybersecurity, and hardware-software co-design. Affiliation: ENSTA-Bretagne, LabSticc Research Focus: FPGA CAD tools, Homomorphic Encryption, RISC-V security His research explores CAD tools for unconventional architectures (e.g., NASICs), homomorphic encryption evaluation, and hardware acceleration. He employs Smalltalk-based object-oriented languages for domain modeling and software quality. Current projects include on-chip monitoring for zero-day attack detection and secure RISC-V extensions. Recent publications highlight trends in machine learning hardware acceleration , JIT compiler security , and deep-sea IoT environmental constraints . Grants include DGA-funded "Overlays for long time maintenances" (2014-2016) and "Secure Overlays" (2017-2020), and Région Bretagne CPER Cyber-SSI (2015-2020). He has supervised PhD students including Xuan Sang Le , Théotime Bollengier , and Cyrielle Feron , and collaborates with institutions like Lab-STICC and European MORPHEUS IP FP6 projects. His work bridges theoretical innovation with practical embedded systems implementation.

Reza Sameniمشاهده پروفایل

دانشیار

• Biomedical Signal Processing
• Machine Learning
• Artificial Intelligence
• +۱۰ مورد دیگر

Reza Sameni is an Associate Professor at Emory University's Department of Biomedical Informatics and Adjunct Associate Professor at Georgia Institute of Technology's Wallace H. Coulter Department of Biomedical Engineering. He serves as Scientific Director of Emory's Medical Imaging, Informatics, and AI (MIIAI) Core. PhD in Biomedical Engineering (Sharif University of Technology) PhD in Signal Processing & Telecommunications (INPG) MSc in Biomedical Engineering (Sharif University) BSc in Electronics Engineering (Shiraz University) His research spans biomedical signal processing and model-based machine learning, with applications in cardiovascular diagnostics, maternal-fetal health, psychiatry, and global health equity. The Alphanumerics Lab develops explainable AI tools for multimodal physiological monitoring and open-access platforms like OSET. Current article trends focus on AI-driven diagnostics, cross-modal ECG/PCG analysis, edge computing for rural healthcare, and algorithmic reproducibility in biomedical applications. The lab actively recruits graduate students and postdocs. Georgia Institute of Technology (adjunct appointment) Emory University (tenured associate professor) Former Chair at Shiraz University Former Senior Researcher at GIPSA-lab Lab initiatives include: open-source toolboxes (OSET), crowdsourced AI frameworks for arrhythmia detection, and bias mitigation in clinical AI systems. Research integrates FPGA/ embedded systems for biomedical hardware development.

• Vibration & Acoustics
• Mechanical Characterization
• Vibration/Noise Control
• +۸ مورد دیگر

Dr. Sebastian Oberst is an Adjunct Associate Professor at the School of Engineering and Information Technology at the University of New South Wales (UNSW) Canberra. His research focuses on vibration and acoustics, mechanical characterization, and vibration/noise control, with particular expertise in microvibrations related to insect communication. He has made significant contributions to the understanding of nonlinear time series analysis, chaotic dynamics, and statistical uncertainty analysis in mechanical systems. Dr. Oberst's primary research interests include: Stability behavior of deployable, flexible structures of nano-satellites Friction-induced vibrations & sound (e.g., automotive disc brake squeal) Vibrational communication in insects (e.g., ants, termites) Mechanical characterization and vibration/noise control Nonlinear time series analysis and chaotic dynamics Statistical and uncertainty analysis in vibration systems His recent publications demonstrate a strong focus on applying advanced signal processing techniques to vibration analysis, particularly in biological systems and engineered structures. Dr. Oberst has pioneered methods for analyzing microvibrations in insect communication and has made significant contributions to understanding brake squeal phenomena through nonlinear dynamics approaches. His work bridges the gap between theoretical vibration analysis and practical engineering applications. Dr. Oberst has secured significant research funding through multiple Australian Research Council grants and industry partnerships: Lead Chief Investigator for "Discovering how termites use vibrations to thrive in a predators' world" (ARC Discovery Project DP200100358, 2020-2022) Chief Investigator for "Metamaterials for control of acoustic radiation forces" (ARC Discovery Project DP200101708, 2020-2022) Chief Investigator for "National Laser-Based Non-Destructive Evaluation System" (ARC LIEF LE180100041, 2018) Lead Chief Investigator for "Bio-inspired vibration-reduction for sensing and detection" (NSW Department of Industry, 2020) Chief Investigator for "Enhanced detection, localisation and identification of sand-covered naval mines" (NSW Department of Industry, 2021) Dr. Oberst teaches across several engineering disciplines including Statics, Dynamics, Thermofluids, Introduction to vibration, Acoustics, Instrumentation, and Statistics. His research lab focuses on experimental and numerical vibration analysis, with particular emphasis on biological vibration systems and engineered mechanical structures. Current projects include developing micro-exciter devices to mimic insect vibration signals, analyzing termite nest morphology, and investigating acoustic radiation forces for contactless manipulation of objects.

• Computed Tomography
• Image Processing
• Super-Resolution
• +۴ مورد دیگر

Sven Simon is Professor and Chair of Computational Imaging Systems at the Institute of Technical Informatics (ITI), University of Stuttgart, Germany. His research focuses on advanced computational imaging techniques with applications across multiple domains including medical diagnostics, industrial inspection, and cultural heritage preservation. Professor Simon's primary research interests include computed tomography, image reconstruction, super-resolution techniques, light-field imaging, and medical imaging applications. His work addresses fundamental challenges in image quality enhancement, scatter correction, beam hardening correction, and processing speed optimization. He has made significant contributions to both theoretical foundations and practical implementations of imaging algorithms. Analysis of Professor Simon's publication record from 2016-2022 reveals a consistent research trajectory focused on enhancing imaging technologies through computational methods. His work demonstrates innovation in applying machine learning techniques to traditional imaging problems and developing specialized hardware implementations (GPU/FPGA) for real-time performance. A notable trend is the cross-disciplinary application of his imaging techniques to solve problems in civil engineering, chemical engineering, and cultural heritage preservation. As head of the Computational Imaging Systems group at the University of Stuttgart, Professor Simon leads a research team that maintains active collaborations across multiple disciplines. His group's work bridges theoretical computer science with practical engineering applications, resulting in publications in high-impact journals including IEEE Transactions on Circuits and Systems for Video Technology, Medical Physics, and Signal Processing.