جست‌وجوی استاد و پژوهشگر

Vincent Beroulleمشاهده پروفایل

استاد

• Microelectronics
• Hardware Security
• Fault Modeling
• +۴ مورد دیگر

Professor Vincent Beroulle at Grenoble Institute of Technology's Esisar campus leads the LCIS laboratory, focusing on security and safety of complex integrated circuits and systems. His work bridges fault modeling, fault injection, and security for IoT and RFID technologies. Education: Engineer Degree (INPG, 1996), Master (University of Montpellier II, 1999), Ph.D. (University of Montpellier II, 2002) Current Role: Director of LCIS Laboratory, Professor in Embedded System Security & Safety Research spans hardware security, fault injection attacks, and vulnerability analysis of embedded systems. Recent work includes clock glitch fault injection studies, lightweight ECC countermeasures for RFID, and aging effects on PUF architectures. His team explores cross-layer methodologies to enhance fault models and security protocols. Supervision includes 12 current and former PhD students tackling topics like secure RFID tags, fault injection countermeasures, and PUF-based security. Projects under ANR, PEPR Cyber, and ERASMUS+ funding drive his lab's innovation in secure embedded design.

• Artificial Intelligence
• Neuroscience
• Circuits and Systems Theory

Neslihan Serap Şengör is a Professor at the Department of Electronics and Communication Engineering, Istanbul Technical University . Her work bridges Artificial Intelligence , Neuroscience , and Circuits and Systems Theory . Research areas include: Neuromorphic computing with Intel Loihi Basal ganglia and motor control modeling Spiking neural networks for hardware Cognitive process simulation Projects focus on: Hardware implementation of motor learning Computational models for Parkinson's disease Cortex structure simulation on neuromorphic chips Contact: sengorn@itu.edu.tr

Martin Elsmanمشاهده پروفایل

استاد

• Programming Languages
• Theory of Computation
• Functional Programming
• +۵ مورد دیگر

Martin Elsman is a full-time Professor in the Programming Languages and Theory of Computation section at the Department of Computer Science, University of Copenhagen (DIKU). He serves as head of the PLTC section and head of studies for the BSc education in Computer Science and Economics. Elsman is also an active maintainer of several software tools including the MLKit and SMLtoJs. Joined DIKU in 2012 after 4 years at SimCorp (2008-2012) and previous Associate Professorship at IT University of Copenhagen (2003-2008). Co-developer of Futhark, TAIL APL compiler, SMLtoJs, and SMLserver. Education: M.Sc. in Engineering, Technical University of Denmark Ph.D. in Computer Science, University of Copenhagen (DIKU), supervised by Mads Tofte. Research Interests: Elsman works on programming language design and implementation, with a focus on functional programming, module systems, domain-specific languages for financial contracts, region-based memory management, compilation techniques for parallelism, program optimization, and static type systems. His work spans both theoretical and applied domains, including blockchain-based financial contract execution, web technology, and GPU programming using functional languages. Publication Trends: His recent articles focus on functional programming, array programming, parallelism, and memory management. Topics include region inference, type systems for data-parallelism, program optimization techniques, and domain-specific compilation for financial and quantum computing. He frequently collaborates with Troels Henriksen and others on tools like Futhark and MLKit.

Gul N. Khanمشاهده پروفایل

استاد

• Embedded Systems
• Hardware/Software Co-design
• Network-on-Chip (NoC)
• +۷ مورد دیگر

Dr. Gul N. Khan is a Professor in the Department of Electrical, Computer and Biomedical Engineering at Toronto Metropolitan University (formerly Ryerson University). He has held academic positions at the University of Saskatchewan, Nanyang Technological University, RMIT University, and Quaid-i-Azam University. His career spans over three decades with a focus on embedded systems , network-on-chip (NoC) , and heterogeneous computing . Education: Ph.D. (Imperial College, 1989), M.Sc. (Syracuse University, 1982), B.Sc. (UET Lahore, 1979) Dr. Khan’s research interests include hardware-software co-design , CPU-GPU systems , fault-tolerant computing , and smart RFID systems . His work has led to over 125 refereed publications and three US patents. His recent publications highlight advancements in GPU auto-tuning , NoC synthesis , and digital time interpolators . Despite being listed in a Google Scholar block with unrelated public health topics, these appear to be errors, as his core expertise remains in computer engineering. Dr. Khan has supervised numerous graduate projects in embedded systems and SoC design . He served as Program Director for Computer Engineering from 2004–2015 and leads the Microsystems Research Lab at Toronto Metropolitan University.

• Quantum Information Theory
• Quantum Optics
• Quantum Computing
• +۳ مورد دیگر

Dr. Daniel Malz is an Assistant Professor at the Department of Mathematical Sciences, University of Copenhagen. His research focuses on quantum many-body systems, quantum optics, and quantum computing, with affiliations to research groups QA, QMATH, and QfL. His work bridges theoretical physics and mathematical modeling, addressing topics like superradiance, entanglement dynamics, and quantum state preparation. Key research interests include quantum information theory, non-Markovian dynamics, and the development of efficient quantum simulation techniques. His recent publications explore advanced topics such as photonic cluster states, tensor network simulations, and cross-platform quantum network verification. Much of his work addresses foundational questions in quantum mechanics while maintaining practical relevance for quantum technologies. His contributions span both theoretical derivations and numerical methods, with a focus on bridging classical and quantum many-body dynamics.

Tsung-Wei Huangمشاهده پروفایل

استادیار

• Computer-aided Design
• High-performance Computing
• Quantum Computing
• +۳ مورد دیگر

Tsung-Wei Huang is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of Wisconsin at Madison, where he focuses on developing software systems for performance-critical applications in design automation, machine learning, and quantum computing. Previously, he held the same position at the University of Utah from 2019 to 2023. He earned his PhD from the University of Illinois at Urbana-Champaign (2017) and dual MS/BS degrees from National Cheng Kung University in Taiwan (2011). Education : PhD in ECE, University of Illinois at Urbana-Champaign (2017) MS in CS, National Cheng Kung University (2011) MS in CS, National Cheng Kung University (2010) Research Interests : Huang’s work emphasizes high-performance computing frameworks, quantum computing systems, and computer-aided design. His systems are widely adopted in academia and industry. Key contributions include GPU-accelerated quantum circuit simulators and task-parallel frameworks for static timing analysis. Publications : His research spans GPU acceleration, graph partitioning, and parallel algorithms, with recent focus on optimizing task-based execution and resource management for heterogeneous systems. Awards : ACM SIGDA Outstanding PhD Dissertation Award NSF CAREER Award Humboldt Research Fellowship ICCAD 10-year Most Influential Paper Award Multiple awards in international programming and design contests Advising & Grants : Recipient of NSF Faculty Early Career Award and Humboldt Fellowship. His research is supported by grants focusing on parallel computing systems and EDA tools. He advises students in the areas of high-performance computing and quantum systems. Labs & Teams : Leads research in parallel computing frameworks and GPU acceleration, with collaborations on taskflow systems and quantum circuit design tools.

• Electromagnetics
• Signal Integrity
• High-Speed Interconnects
• +۵ مورد دیگر

Andreas C Cangellaris is a Professor at the University of Illinois at Urbana-Champaign, affiliated with the College of Engineering and the Department of Electrical and Computer Engineering. He leads research in the Coordinated Science Lab, focusing on electromagnetic modeling, signal integrity, and high-speed interconnects. His work spans nanotechnology, stochastic analysis, and machine learning applications in electromagnetics. Education details are not explicitly provided in the text, but his academic career includes significant contributions to computational electromagnetics, including the development of PEEC methods and neural network-based models for high-speed systems. Research interests emphasize modeling uncertainties in electromagnetic systems, metamaterials, and power delivery networks. He has pioneered techniques like the Stochastic Latency Insertion Method (LIM) and FFT-based macromodeling for stochastic systems. Key awards include the Humboldt Research Award (2004) and IEEE Fellow designation (2000). His grants and advising activities are not detailed here, but his lab focuses on advancing electromagnetic compatibility and high-speed link design. Notable collaborations involve stochastic modeling of fiber-weave effects in PCBs and inverse design methodologies using tandem neural networks.

Junzhong Xuمشاهده پروفایل

دانشیار

• Quantitative MRI Methods
• Neurodegenerative Diseases
• Cancer Imaging
• +۳ مورد دیگر

Junzhong Xu is an Associate Professor of Radiology and Radiological Sciences, Biomedical Engineering, and Physics and Astronomy at Vanderbilt University. His research focuses on developing advanced quantitative MRI methods for applications in neurodegenerative diseases and cancer, including MRI cell size imaging and tumor treatment response assessment. He holds affiliations with the Vanderbilt University Institute of Imaging Science (VUIIS) and has expertise in microstructural diffusion MRI and GPU-accelerated imaging tools. Xu’s work spans interdisciplinary collaborations in biomedical engineering and physics. Education: B.S., University of Science and Technology of China M.S., University of Science and Technology of China Ph.D., Vanderbilt University Research Interests: Development of MRI cell size imaging for cancer and neurodegenerative diseases Quantitative assessment of tumor microstructure and treatment response Applications of microstructural diffusion MRI in multiple sclerosis and oncology Key Contributions: Advancement of MRI cytometry for non-invasive disease assessment GPU-accelerated tools for diffusion MRI simulation (MATI) Imaging biomarkers for early detection of neurodegenerative pathology Labs/Teams: Active member of the Vanderbilt University Institute of Imaging Science (VUIIS), collaborating on interdisciplinary imaging projects.

Fatemeh Babaeianمشاهده پروفایل

پژوهشگر ارشد

• Applied Electromagnetics
• High Power Microwave
• RF Sensing
• +۳ مورد دیگر

Fatemeh Babaeian is a Research Fellow in the Department of Electrical and Computer Systems Engineering at Monash University. She holds a PhD from Monash University (2016–2020), focusing on advanced electromagnetic systems. Her expertise spans applied electromagnetics, high-power microwave systems, RF sensing, antenna design, and signal processing, with notable contributions to chipless RFID technologies and cascaded oscillator modeling. Research interests include high-power RF systems, antenna-oscillator interaction modeling, and innovative RFID applications for sensor networks and secure communications. Her work addresses challenges in microwave engineering, terahertz systems, and inverse scattering problems, leveraging hybrid optimization algorithms and metamaterial principles. Fatemeh has published over 29 peer-reviewed articles, including seminal works on switched oscillator performance evaluation and phase shifter designs. She received the Postgraduate Publications Award (2020) for her impactful contributions. Current research emphasizes antenna-circuit co-design methodologies and high-data-capacity RFID systems for emerging IoT and industrial applications. Collaborations span global institutions, with active projects in high-power microwave systems, THz antenna arrays, and orientation-insensitive RFID tag innovations. She actively supervises PhD students and contributes to interdisciplinary research bridging electromagnetic theory and practical engineering solutions.

Tania Morimotoمشاهده پروفایل

دانشیار

• Robotics
• Medical Robotics
• Soft Robotics
• +۳ مورد دیگر

Tania Morimoto is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of California San Diego. Her research focuses on the design and control of flexible and soft robots for medical and exploration applications, including personalized surgical robots and intuitive human-in-the-loop interfaces. She leads efforts in haptic device development for education, notably creating the Hapkit and H3Kit systems used in STEM labs globally. She holds a B.S. in Mechanical Engineering from MIT, and M.S. and Ph.D. from Stanford University's CHARM Lab. Her work bridges robotics, haptics, and medical engineering, with key innovations in continuum robot design, wireless sensing, and surgical teleoperation systems. Key research areas include soft robotics for minimally invasive surgery, wearable haptic devices, and scalable pneumatic control systems. Her team has developed novel methods for patient-specific robot design using preoperative medical imaging, along with virtual reality interfaces for surgical planning. Notable achievements include the NSF CAREER Award (2022) for work on handheld continuum robots, and contributions to wireless force sensing technologies. Her educational initiatives have expanded access to hands-on robotics learning through low-cost hardware kits adapted for remote instruction.

Sarah Harrisمشاهده پروفایل

استاد

• Computer Architecture
• FPGA Design
• RISC-V Systems
• +۳ مورد دیگر

Sarah Harris is Professor and Undergraduate Coordinator in the Department of Electrical and Computer Engineering at University of Nevada, Las Vegas. Her research focuses on computer architecture education, FPGA-based systems, and hardware implementations of neural networks. Research areas include: RISC-V architecture education tools FPGA-based hardware design Embedded AI systems Computer engineering pedagogy Her publication portfolio shows strong focus on educational innovation with 7 publications (2021-2024) on RISC-V teaching tools and MOOCs, alongside hardware implementations of neural networks and contributions to bioinformatics tools. Earlier work includes digital design fundamentals and memory systems.

Christopher Bidinostiمشاهده پروفایل

استاد

• Nuclear Magnetic Resonance
• Medical Imaging
• Machine Learning
• +۳ مورد دیگر

Dr. Christopher Bidinosti is a Professor in the Department of Physics at the University of Winnipeg. He holds a Ph.D. from the University of British Columbia (2000) and specializes in nuclear magnetic resonance (NMR), magnetic resonance imaging (MRI), and machine learning applications in agriculture. His research spans low-field NMR/MRI, hyperpolarized nuclei, and collaborations like the TerraByte project, aimed at advancing agricultural machine learning through open-access plant image datasets. His research interests include TRASE MRI, neutron electric dipole moment (EDM) searches, GPU computing, and magnetics (coil design, shielding). He teaches courses such as Electricity & Magnetism and Optics and Waves. His work bridges physics and applied technology, with a focus on interdisciplinary innovation. Bidinosti collaborates with institutions like UWinnipeg’s Computer Science department and has developed hardware solutions for NMR/MRI systems. His contributions span experimental physics, computational methods, and agricultural technology, leveraging both theoretical and applied approaches.

Jacob K. Whiteمشاهده پروفایل

استاد

• Computer-aided design
• CAD
• Computational prototyping
• +۱۱ مورد دیگر

Jacob K. White is the Cecil H. Green Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT). He is a principal investigator at the Research Laboratory of Electronics (RLE) and served as its Associate Director since 2001. His academic journey includes positions as an assistant professor (1987), associate professor (1991), and full professor (1996) at MIT. Education: Bachelor's degree in Electrical Engineering and Computer Science from MIT (1980) Master's degree from the University of California, Berkeley (1983) Doctorate from UC Berkeley (1985) Research Interests: Computer-aided design and computational prototyping Numerical algorithms and simulation techniques Optimization of integrated circuits and MEMS devices BioMEMS and biomolecule design Systems biology and fluidic analysis of sensors/actuators Scientific Awards: 2008 IEEE Fellow Major Award at the 50th Design Automation Conference (DAC) Advising and Grants: No student advisees listed. Details on grants are not provided in the text. Labs/Teams: Principal Investigator at the Research Laboratory of Electronics (RLE) and leads the Computational Prototyping Group.

• Energy Storage Systems
• Materials Science
• Electrochemistry
• +۳ مورد دیگر

Rohit Bhagat is a Professor and Centre Director at the Centre for E-Mobility and Clean Growth. His research focuses on advancing energy storage technologies, particularly lithium-ion batteries, through material science innovations and real-time monitoring systems. Key areas of interest include battery degradation mechanisms, sensor integration for diagnostics, and environmental impact assessments of battery production. Research highlights include developing predictive models for lithium plating detection using machine learning, investigating electrolyte degradation under elevated temperatures, and optimizing cathode materials for zinc-ion batteries. He has led projects such as the British Council MRes scholars initiative in STEM, emphasizing interdisciplinary collaboration. Bhagat’s work spans experimental design methodologies for battery modeling, thermal management strategies, and life cycle assessments. His contributions address critical challenges in battery safety, longevity, and sustainability, with applications in electric vehicles and renewable energy systems.

Soroush Faramehrمشاهده پروفایل

دانشیار

• Power Electronics
• Semiconductor Technologies
• Renewable Energy
• +۵ مورد دیگر

Dr Soroush Faramehr is an Associate Professor (Research) at Coventry University's Institute for Future Transport and Cities. He holds a PhD in Electrical Engineering from Swansea University (2015), specializing in wide bandgap semiconductor technologies. His research focuses on developing high-efficiency compound semiconductor devices for decarbonization in automotive, aerospace, renewable energy, and industrial sectors. He has over 10 years of R&D experience, with a strong publication record in peer-reviewed journals, successful grant acquisitions, and supervision of postgraduate researchers. Education: PhD in Electrical Engineering (Swansea University, 2015). Postdoctoral research at Swansea University before joining Coventry in 2019. Research Interests: Power semiconductor devices (GaN, SiC), magnetic sensors, thermal management, and E-mobility applications. His work aligns with UN Sustainable Development Goals related to climate action and sustainable infrastructure. Key Projects: Includes leadership in initiatives such as 'Gallium Nitride Smart Power Integrated Circuit Technology' (2021–2025) and 'GaN Hall Sensors' (2020). He has secured funding for projects like 'High-Voltage fast-charging efficient Electric vehicle Powertrains' (2025–2029). Advising: Supervises students researching topics like GaN HEMT switching behavior, thermal management in e-scooters, and second-life EV battery utilization. His advisees include Xuyang Lu, Arun Mambazhasseri Divakaran, and current students Louiza Mavrovounioti and Vartika Pandey. Publications: Over 30 articles in journals such as IEEE Access and IEEE Transactions on Power Electronics. Research spans CFD modeling, magnetic sensor development, and GaN device optimization.