جست‌وجوی استاد و پژوهشگر

Peter Wilsonمشاهده پروفایل

استاد مهمان

• Power Electronics System Modelling
• Autonomous Systems & Robotics
• Renewable Energy Systems
• +۳ مورد دیگر

Peter Wilson is a Visiting Professor in the Department of Electronic & Electrical Engineering at the University of Bath. He holds affiliations with The Foundry Centre for Digital Manufacturing, the Institute of Sustainability and Climate Change, and serves as Executive Vice President of the IEEE Power Electronics Society. His professional background includes industrial roles at Ferranti, GEC-Marconi, and Analogy, Inc., as well as a prior academic position as Associate Professor at the University of Southampton. Wilson holds a BEng from Heriot-Watt University, an MBA from Edinburgh Business School, and a PhD from the University of Southampton. He has authored over 150 publications, three books, and holds a patent. His research focuses on power electronics systems, autonomous robotics, renewable energy systems, and neuromorphic computing. He leads Bath's postgraduate teaching initiatives and advises Formula Student Electric racing teams (TBRe) and Zero Emissions Motorcycle teams. Recent research projects include EPSRC-funded initiatives on 3D printing in healthcare (BioMed 4.0), autonomous surface vehicle technologies (OCEAN2020), and automotive systems design automation. Wilson has secured numerous grants and holds leadership roles in international conferences such as the IEEE Workshop on Behavioral Modelling and Simulation. His accolades include IET Fellowship and IEEE Senior Membership. Supervision focuses on topics like behavioral modeling, renewable energy design, and autonomous systems development across marine and automotive domains.

Federico Corradiمشاهده پروفایل

استادیار

• Neuromorphic Computing
• Spiking Neural Networks
• Energy-Efficient Computing
• +۷ مورد دیگر

Federico Corradi is an Assistant Professor in the Electrical Engineering Department at Eindhoven University of Technology (TU/e), where he leads the Neuromorphic Edge Computing Systems Lab. He also holds the position of EAISI Foundational Assistant Professor at the Eindhoven Artificial Intelligence Systems Institute. His research focuses on neuromorphic computing and engineering, spanning from efficient computational models to novel microelectronic architectures for deep learning and brain-inspired algorithms. Dr. Corradi's academic background includes a Ph.D. in Neuroinformatics from the University of Zurich and an international Ph.D. from the ETH Neuroscience Centre Zurich (2015). Prior to joining TU/e in 2022, he worked at IMEC in the Netherlands (2018-2022) where he started a group focused on neuromorphic IC design. Before that, he was with Inilabs, a spin-off from the Institute of Neuroinformatics, developing event-based cameras and neuromorphic processors (2015-2018). His research interests center around understanding natural neural computation principles to develop energy-efficient sensing and computing technologies. Key areas include: Neuromorphic computing and engineering Spiking neural networks Event-based vision systems Energy-efficient microelectronic architectures Applications in robotics, machine vision, and biomedical signal analysis Dr. Corradi's recent publications demonstrate a strong focus on practical implementations of neuromorphic systems for edge applications. His work shows consistent innovation in translating theoretical neural models into efficient hardware implementations, with particular emphasis on handling temporal data and developing brain-realistic computational models. The research spans multiple domains including radar signal processing, optical computing, and error correction systems. He serves as an active review editor for Frontiers in Neuromorphic Engineering, IEEE, and IOP Science journals, and participates in technical program committees for several machine learning and neuromorphic conferences including ICTOPEN, AICAS, AIAI, ICONS, NEWCAS, DSD, and EUROMICRO. His work has received significant media attention with coverage from multiple news outlets and social media mentions. Dr. Corradi leads the Neuromorphic Edge Computing Systems Lab, which bridges theoretical neuroscience with practical engineering challenges, creating novel solutions for real-world problems. The lab's research has practical applications in robotics, autonomous systems, and biomedical technologies, reflecting his commitment to developing energy-efficient computing solutions that can operate effectively at the edge.

Yunus Can Gültekinمشاهده پروفایل

پژوهشگر

• Wireless Communication
• Optical Communications
• Quantum Key Distribution
• +۵ مورد دیگر

Yunus Can Gültekin is a Researcher at the Eindhoven University of Technology (TU/e), affiliated with the Signal Processing Systems department within the Electrical Engineering school. He holds a B.Sc. and M.Sc. from Middle East Technical University (Turkey) and a Ph.D. from TU/e (2020). His research focuses on future wireless/optical communication systems, quantum key distribution, and signal processing solutions using information theory tools. Key contributions include developing coded modulation techniques and mitigating nonlinear interference in optical systems. Education: B.Sc., Middle East Technical University, Ankara, Turkey (2013) M.Sc., Middle East Technical University, Ankara, Turkey (2015) Ph.D., Eindhoven University of Technology, Netherlands (2020) Research Interests: Quantum Key Distribution (QKD) systems Optical and free-space communication systems Probabilistic shaping and nonlinear mitigation Coded modulation design for high-speed transmission Notable Achievements: Best Paper Award at WIC/IEEE Symposium (2018) Optica Student Paper Award (2022) Quantum Delta NL Exchange Visit Grant (2023) International Excellence Fellowship (2024) Teaching: Current courses: Communication Theory, Digital Wireless Communication Exploration Lab Past courses: Analog Electronics Lab, Digital Design Lab Key Projects: LaiQa: Quantum Satellite Communications (2024–2026) BIT-FREE: Free-Space Optics (2024–2028) COCOLI: Optical Link Complexity (2022–2028) Labs/Teams: Active in the Signal Processing Systems group, collaborating on quantum and optical communication initiatives at TU/e.

• Signal Processing
• Analog-to-Digital Conversion
• Unlimited Sampling Theory
• +۲ مورد دیگر

Dorian Florescu is a Lecturer in the Department of Electronic & Electrical Engineering at the University of Bath. His research specializes in signal processing theory and hardware implementations, particularly in unlimited sampling techniques that overcome dynamic range limitations in analog-to-digital conversion systems. Primary research domains include: 1) Development of novel algorithms for time-encoded signal recovery; 2) Computational demodulation methods through bandpass undersampling; 3) Hardware validation of unlimited sampling architectures; 4) Applications of hysteresis in signal acquisition systems. His work bridges theoretical foundations with practical implementations across communication systems and signal processing hardware. Dr. Florescu's publications demonstrate consistent innovation in sampling theory, with recent advances in generalized signal recovery frameworks and neural network applications for computer algebra optimization. His research group explores fundamental limits of signal acquisition systems.

• Machine Learning
• Biomedical Engineering
• Signal Processing
• +۵ مورد دیگر

Amir Nassibi is a Postdoctoral Research Associate at Imperial College London's Communication and Signal Processing Research Group (CSP), Department of Electrical and Electronic Engineering. He holds a PhD from Imperial College London and an MSc in Advanced Digital Systems from the University of Hertfordshire. His research focuses on machine learning applications in healthcare, wearable sensor systems, and signal processing for biomedical diagnostics. He is affiliated with the UK Dementia Research Institute (UKDRI) and collaborates on multidisciplinary projects. Education: PhD in Electrical and Electronic Engineering, Imperial College London (UK) MSc in Advanced Digital Systems, University of Hertfordshire (UK) Research interests include EEG-based depression diagnosis, wearable multimodal sensing platforms like BioBoard, and edge computing for AI deployment in healthcare. His work addresses challenges in signal enhancement, algorithm optimization for embedded systems, and reducing bias in medical device outputs. He explores topics such as memristor modeling for integrated circuits and in-ear ECG/PPG fusion for vital signs monitoring. Awards: None explicitly stated. Advising & Grants: While specific grants are not detailed, his role as a postdoctoral researcher suggests involvement in funded projects. He collaborates on lab initiatives within the CSP group and UKDRI. Labs/Teams: Active contributor to the Communication and Signal Processing Group at Imperial College London and the UK Dementia Research Institute's interdisciplinary teams.

• Electronics
• Nanoelectronics
• Electrical Engineering
• +۵ مورد دیگر

Cédric Meinen is a Lecturer at the École Polytechnique Fédérale de Lausanne (EPFL), primarily affiliated with the School of Engineering. He holds dual roles as an ETS/HES Engineer in SEL - Management and Operations Manager in DLL-STI Engineering, reflecting his involvement in both technical and administrative capacities. His academic presence spans multiple departments and laboratories, including the Nanoelectronic Devices Laboratory (NANOLAB) under the Institute of Microengineering (IEM) and sections within STI-SEL. Education: Cédric Meinen specializes in Electrical and Electronics Engineering , as highlighted in his profile. This aligns with his teaching portfolio, which includes foundational courses like Electronics I and Electrical and Electronic Systems I/II . Research Interests: His work focuses on analog and digital circuit design, semiconductor device modeling (Bipolar/MOSFET), signal acquisition systems (e.g., physiological signals, bio-sensors), and practical applications of operational amplifiers. He integrates principles from applied physics into his teaching and laboratory work, emphasizing measurement techniques and data analysis. Labs/Teams: He is a core member of the Nanoelectronic Devices Laboratory (NANOLAB), contributing to microelectronic and nanoelectronic research. Additionally, he supports engineering education through STI-SEL and DLL-STI units.

Lawrence R Chenمشاهده پروفایل

استاد

• Engineering Education
• Photonics
• Optical Communications
• +۳ مورد دیگر

Lawrence R. Chen is a Professor at McGill University's Department of Electrical & Computer Engineering within the Faculty of Engineering. He serves as the Academic Lead for ELATE (Enhancing Learning and Teaching in Engineering) and holds Engineer (OIQ) certification. His research focuses on engineering education (e.g., faculty development, learning mechanisms) and photonics (e.g., photonic integration, microwave photonics). He has advised numerous PhD and master’s students, including recent graduates such as Yuxuan Xie and Mostafa Khalil. His work spans theoretical and applied photonics, with recent contributions to quantum dash lasers and optoelectronic systems. Chen’s engineering education research examines student perceptions, career motivations, and pedagogical practices. Notable collaborations include studies on undergraduate engineering identity and student-generated multimedia for professional ethics education. His photonics research includes microwave photonic filters, optical frequency combs, and secure optical communications. Current research group members include PhD students Xi Wang and Zhuoran Wang, alongside undergraduate researchers focusing on engineering education. Past students have secured roles at institutions like Hyperlume and ADVA Optical Networking. Chen’s work is published in venues like the IEEE Journal of Lightwave Technology and Optics Express .

Mark McKinneyمشاهده پروفایل

استاد

• Instrumentation and Measurements
• Circuit Protection Devices
• Electronics
• +۳ مورد دیگر

Dr. Mark McKinney is a full-time Professor and Department Head of Electrical and Computer Engineering at The Citadel, School of Engineering. He has been with the institution since 1997 and holds a Ph.D. in Electrical Engineering from the University of South Carolina. His research focuses on instrumentation, circuit protection, and renewable energy systems, with notable contributions to grid simulator design and testing facilities. Education: Ph.D., Electrical Engineering, University of South Carolina (1999) M.S., Electrical Engineering, University of South Carolina (Year not specified) B.S., Electrical Engineering, University of South Carolina (Year not specified) Research Interests: Dr. McKinney specializes in power systems protection, renewable energy testing, and interdisciplinary projects integrating LabVIEW with FPGA hardware. He has developed megawatt-scale testing facilities for evaluating solar inverters and grid stability. His work emphasizes practical applications, such as robotics education for underserved schools and collaborations with organizations like Clemson University on the Duke Energy eGRID lab. Articles and Trends: His recent publications (2014–2018) highlight advancements in grid simulation, fault ride-through evaluations, and high-power testing methodologies. Earlier work includes contributions to semiconductor device studies and thermal management systems. Awards and Grants: While no specific awards are listed, his sustained research collaborations and facility development projects demonstrate significant academic and industrial engagement. Labs and Teams: He leads the Electrical and Computer Engineering department and has contributed to initiatives like robotics summer camps and eWeek competitions, fostering engineering outreach and education.

Gim P Homمشاهده پروفایل

مدرس ارشد

• Medical Device Design
• Biomedical Engineering
• Analog Electronics
• +۳ مورد دیگر

Gim P. Hom is a Senior Lecturer at the Massachusetts Institute of Technology , affiliated with the Department of Electrical Engineering and Computer Science since 2005. Their roles include mentoring students in interdisciplinary medical device design and analog/digital electronics projects. Education 1971 SB Electrical Engineering (MIT) 1972 SM Electrical Engineering (MIT) 1973 SM Sloan School of Management (MIT) Research Focus : Medical device innovation, biomedical signal processing, and interdisciplinary engineering education. Projects include fatigue detection systems, vein penetration sensors, and lung condition monitoring tools developed through hands-on student collaboration. Teaching Highlights : Co-designed courses like Medical Device Design (6.025/6.525/2.75/2.750) and Analog Electronics Laboratory (6.101) , emphasizing team-based prototyping and clinical translation. Scientific Awards Departments Head Special Recognition (2014) George B. Morgan '20 Alumni Leadership Award (2017) IEEE/ACM Best Advisor Award (2018) Professional Background : Former engineering and management roles at Digital Equipment Corporation/Compaq/HP, and Senior Member of Technical Staff at Texas Instruments.

Sourav Banerjeeمشاهده پروفایل

استاد

• Computational Nondestructive Evaluation (NDE)
• Structural Health Monitoring (SHM)
• Material State Awareness
• +۶ مورد دیگر

Dr. Sourav Banerjee is a Professor in the Department of Mechanical Engineering at the University of South Carolina (USC), affiliated with the Molinaroli College of Engineering and Computing. He holds a Ph.D. in Engineering Mechanics from the University of Arizona, and bachelor's and master's degrees from IIEST Shibpur and IIT Bombay, respectively. His research focuses on computational nondestructive evaluation (NDE), structural health monitoring (SHM), metamaterials, and topological acoustics. He leads the i-MAPS Laboratory, exploring NDE 4.0, robotic NDE, and digital twin technologies for aerospace and naval structures. Notable contributions include books on computational NDE and topological acoustics. Awards include the Achenbach Medal (2010) and the SHM Person of the Year (2019). His work integrates AI, physics-driven models, and big data analytics for advanced material assessment. Education: Ph.D., Engineering Mechanics (University of Arizona, 2005); M.S., Structural Engineering (IIT Bombay, India); B.S., Civil Engineering (IIEST Shibpur, India). Research interests span ultrasonic NDE, metamaterials for energy harvesting, and biomimetic sensors. He has authored/co-authored over 100 peer-reviewed publications and holds patents in piezoelectric biosensors and acoustic computing. Awards include the Breakthrough Star Award (2019), Michael J. Mungo Teaching Award (2017), DAAD Scholarship (Germany, 2001), and multiple industry recognitions. His lab’s projects are funded by NASA, focusing on autonomous NDE systems and digital twin integration for high-rate manufacturing. Current research emphasizes NDE 4.0, AI-driven predictive models, and quantum-analogous wave phenomena in engineered materials.

I-Hung Khooمشاهده پروفایل

استاد

• High-Speed Circuit Design
• Mixed-Signal Circuit Design
• Analog Signal Processing
• +۳ مورد دیگر

Dr. I-Hung Khoo is a Professor at California State University, Long Beach (CSULB), holding a joint appointment in the Electrical Engineering and Biomedical Engineering departments within the College of Engineering. He joined CSULB in 2006 and currently serves as the advisor for the Electronics and Computer Engineering Technology programs. His research focuses on high-speed and mixed-signal circuit design, analog and digital signal processing, and related fields in electrical engineering. Dr. Khoo earned his Ph.D. in Electrical and Computer Engineering from the University of California, Irvine in 2002. He is an active member of the IEEE and maintains professional roles in academic advising and program leadership. His expertise bridges theoretical and applied aspects of circuit design and signal processing, contributing to advancements in electronic systems.

Mahmoud Wagdyمشاهده پروفایل

استاد

• Microelectronics
• Mixed-Signal Integrated Circuit Design
• Analog Signal Processing
• +۵ مورد دیگر

Dr. Mahmoud Wagdy is a Professor of Electrical Engineering at California State University, Long Beach (CSULB), affiliated with the College of Engineering. He specializes in microelectronics, analog circuit design, and mixed-signal systems. His research focuses on ADC quantization errors, dither signal effects, and behavioral modeling of electronic systems. He has held prestigious fellowships at NASA's Jet Propulsion Lab and the Air Force Research Lab. Dr. Wagdy pioneered techniques for analyzing ADC linearization through dither signals and contributed foundational work in Active-R Networks and ADC testing. He leads the EE Microelectronics Research Lab, funded by Tektronix, and has advised over 50 graduate students (1 PhD, 10 MS thesis, and 40 MS project students). He is a Senior Member of IEEE and has served as a guest editor and conference chair for IEEE publications. His accolades include the 2006 CSULB Distinguished Faculty Award, reflecting his scholarly impact. His teaching spans undergraduate and graduate courses in microelectronics, analog systems, and electronic design methodologies.

Zhiyuan Yanمشاهده پروفایل

استاد

• Coding Theory
• Wireless Communications
• VLSI Design
• +۴ مورد دیگر

Zhiyuan Yan is a Professor and Associate Chair in the Department of Electrical and Computer Engineering at Lehigh University. He holds a B.E. from Tsinghua University and M.S./Ph.D. degrees from the University of Illinois at Urbana-Champaign. His research focuses on coding theory, VLSI design, wireless communications, and embedded systems. He is a Senior Member of the IEEE and received the NSF CAREER Award in 2011. Educational Background: B.E., Electrical Engineering, Tsinghua University M.S., Electrical Engineering, University of Illinois at Urbana-Champaign Ph.D., Electrical Engineering, University of Illinois at Urbana-Champaign Research Interests: His work spans coding theory (including polar codes and LDPC codes), VLSI implementations for communication systems, and cybersecurity through physical unclonable functions (PUF). He explores neuromorphic computing, memristive neural networks, and hardware-efficient error correction techniques. His contributions include efficient decoder architectures and distributed storage solutions. Scientific Awards: 2011: NSF CAREER Award Advising & Grants: While specific student names aren't listed, his research has been supported by multiple grants. His lab focuses on collaborative projects between academia and industry, emphasizing practical implementations of theoretical advancements. Lab & Teams: His research team develops cutting-edge VLSI systems, neural network accelerators, and secure communication protocols. Collaborations include work on memristive hardware and neuromorphic computing architectures.

• Neuromorphic Engineering
• Computational Neuroscience
• Brain-Inspired Computing
• +۲ مورد دیگر

Alessio Franci is Lecturer in Electrical Engineering and Computer Science at the University of Liege, where he co-founded the ULiege Neuroengineering Lab. His research bridges mathematics, neuroscience and engineering through brain-inspired computing paradigms. Funded by a WEL-T Starting Grant, his work develops neuromorphic controllers and biomorphic systems for robotics and intelligent sensing. Research explores: neurocomputational principles of decision-making; neuromodulation in adaptive systems; and degenerate coding in neural circuits. Publications apply nonlinear dynamics to opinion formation, neural coding, and neuromorphic hardware design, demonstrating consistent innovation in theoretical frameworks. Honors include the WEL-T Starting Grant supporting his investigations into neuronal degeneracy and physiological mechanisms. Current work emphasizes real-world applications in robotics through spiking neural controllers and embodied neuromodulation strategies.

Ali Manzakمشاهده پروفایل

عضو هیئت علمی

• Low Power VLSI Design
• Embedded Systems
• Mixed-Signal IC Design
• +۳ مورد دیگر

Ali Manzak is an Assistant Teaching Professor in the Department of Electrical and Computer Engineering at Florida State University (FSU). He holds a M.Sc. in Control Systems from the University of Colorado Boulder and a Ph.D. in VLSI Systems from Arizona State University. Prior to academia, he worked as a digital IC design engineer at Lattice Semiconductor in California. His research focuses on low-power VLSI design, embedded systems, mixed-signal IC design, and hardware implementation of machine learning algorithms. He actively contributes to academia through teaching and lab supervision, designing ICs for both educational and research purposes. Education: Ph.D., Electrical Engineering (VLSI Systems), Arizona State University M.Sc., Electrical Engineering (Control Systems), University of Colorado Boulder Research Interests: Dr. Manzak’s work emphasizes energy-efficient VLSI circuits, emerging nanotechnologies like carbon nanotube FETs, and applying machine learning to hardware systems. His publications span IEEE journals and conferences, addressing topics such as power-aware cache design, low-power latch optimization, and AI-driven solutions for electromagnetic problems. Teaching & Labs: He instructs courses like EEL 3705/L, EEL 3927, and EEL 4742/L, and maintains hands-on IC design experience across multiple platforms. His labs integrate industry practices with academic research, fostering practical engineering skills.