جست‌وجوی استاد و پژوهشگر

Alyssa B. Apselمشاهده پروفایل

استاد

• RF Mixed Signal Circuit Design
• Ultra-Low Power Radio
• Photonic Integration with VLSI
• +۴ مورد دیگر

Alyssa B. Apsel is a Professor of Electrical and Computer Engineering at Cornell University since 2002 and a Visiting Professor at Imperial College London. She became the IBM Professor of Engineering in 2023 and Director of Electrical and Computer Engineering at Cornell in 2018. Education: B.S., Electrical Engineering, Swarthmore College (1995) M.S., Electrical Engineering, California Institute of Technology (1996) Ph.D., Electrical Engineering, Johns Hopkins University (2002) Research Focus: She specializes in power-aware mixed-signal circuits for scaled CMOS and modern systems. Her group explores cost-effective designs addressing device scaling challenges (variation, noise, reduced analog performance) through analog/mixed-signal innovation, particularly in IoT radios and reconfigurable multi-standard wireless systems. Key areas: RF circuits, VLSI integration, biomedical telemetry, and low-power design. Publication Trends: Her 2016 work spans RF transceiver design, thermometer DAC calibration, biomedical ICs with UWB telemetry, and jitter-measurement circuits. These reflect her expertise in low-power wireless systems, analog/mixed-signal design, and biomedical electronics. Awards: IEEE Fellow (2020) IEEE CAS Distinguished Lecturer (2018-2019) ISLPED Design Contest Second Place (2010) Multiple Student Paper Awards (2000, 1995) Fellowships: Abel Wolman (1997), Caltech Institute (1995) Grants & Leadership: She founded EchoICs, which received a $275,000 NSF STTR Phase I Award (2024) for flexible spectrum radios. Her lab focuses on RF interfaces for implantable electronics and photonic integration.

Kate Smithمشاهده پروفایل

استادیار

• Quantum Computing
• Computer Architecture
• Quantum Compilation
• +۵ مورد دیگر

Kate Smith is an Assistant Professor of Computer Science at Northwestern University, affiliated with the McCormick School of Engineering. She holds a PhD in Electrical Engineering from Southern Methodist University (SMU), along with MS and BS degrees in Electrical Engineering and Mathematics from the same institution. Her research focuses on quantum computing, specifically in system architecture, optimized compilation, error mitigation, and security. Prior to joining Northwestern in 2024, she worked at Infleqtion managing the Superstaq compiler team and as a postdoctoral scholar at the University of Chicago under the CQE/IBM program. She has contributed to over 25 peer-reviewed publications and served on technical committees for major conferences like MICRO, ISCA, and DAC. Education: SMU (PhD 2019, MS 2015, BS in EE/Math 2014). Professional experience includes roles at EPFL (Switzerland), Texas Instruments, and the Darwin Deason Institute for Cyber Security. Her honors include the 2022 HPCA Best Paper Award, MIT EECS Rising Star (2021), and the IEEE TC-MVL Early Career Award (2021). Research interests span quantum compilation, distributed systems, qudit processing, and quantum security. She co-organized the 2023 CCC Workshop on Next Steps in Quantum Computing and chaired the 2022 ISMVL conference. Her work emphasizes bridging hardware-software gaps to enable scalable quantum systems. Grants and collaborations include the EPiQC group at the University of Chicago and projects funded by the Swiss NSF. Teaching experience includes courses on quantum computing fundamentals and digital design at SMU, University of Chicago, and adjunct roles.

Linda S Milorمشاهده پروفایل

استاد

• Reliability Modeling
• Semiconductor ICs
• Analog and Mixed-Signal Testing
• +۳ مورد دیگر

Linda S Milor is a Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. She specializes in reliability modeling of semiconductor circuits, analog and mixed-signal testing, and yield optimization. Dr. Milor holds an IEEE Fellow distinction and has received multiple awards, including 8 best paper awards and the NSF Career Grant (1995). She has advised 18 Ph.D. students and contributed over 200 publications on semiconductor reliability and testing. Education: B.S. in Engineering Physics from UC Berkeley (undergraduate details unspecified) and a Ph.D. in Electrical Engineering from UC Berkeley (1992), focusing on analog/mixed-signal circuit testing. Research Interests Reliability modeling for semiconductor circuits Circuit performance prediction under manufacturing variations Analog and mixed-signal testing methodologies Statistical process modeling for yield enhancement Key Contributions Her work emphasizes aging analysis in SRAM, FinFET technology, and dielectric breakdown mechanisms. She pioneered techniques for on-line testing of memory systems and developed frameworks for accelerated life testing. Awards & Recognition IEEE Fellow (2014) 2004 Best Paper in IEEE Transactions on Semiconductor Manufacturing NSF Career Award (1995) Advising & Grants Advised 18 Ph.D. students and secured grants including the NSF Career Grant. Her research has been applied in industrial contexts through consulting roles for semiconductor manufacturers. Labs & Collaborations Her work integrates semiconductor reliability research with industry partnerships, focusing on practical applications of aging prediction and wearout mitigation.

• Hardware Design
• VLSI Systems
• Digital Circuit Optimization
• +۴ مورد دیگر

Rajkumar Sarma is a Research Fellow at the Department of Computer Science & Information Systems at Lero – the Research Ireland Centre for Software, University of Limerick. His work focuses on hardware design, VLSI systems, and optimization techniques for digital circuits. He specializes in areas such as low-power architectures, floating-point arithmetic, and evolutionary algorithms for automated design. His research emphasizes hardware-software co-design, reliability analysis under PVT (Process, Voltage, Temperature) variations, and efficient implementations of multiply-accumulate (MAC) units critical to digital signal processing and image processing applications. Key technical contributions include the development of the UCM algorithm for delay optimization, grammatical evolution for synthesizable HDL code generation, and novel approaches to reduce power consumption in MAC architectures. His work bridges theoretical algorithmic innovation with practical VLSI implementation challenges, addressing both performance and reliability under extreme operating conditions. Rajkumar’s publications span 2012–2025, with a strong focus on digital circuit design, including hybrid adders, low-power flip-flop implementations, and quantum gate-based reversible circuits. His research also extends to reliability analysis of electronic components like multi-layer ceramic capacitors. He has utilized advanced simulation tools such as Cadence ADE-XL for accelerated PVT analysis, demonstrating expertise in both computational modeling and hardware validation. While no specific awards or grants are listed, his extensive publication record reflects sustained engagement with cutting-edge challenges in computer architecture and VLSI systems design.

Lloyd W Massengillمشاهده پروفایل

استاد

• Radiation-Hardened Circuits
• Microelectronics
• Analog Circuit Design
• +۳ مورد دیگر

Lloyd W. Massengill is a Professor of Electrical and Computer Engineering at Vanderbilt University's School of Engineering. His research focuses on radiation-hardened circuit design, simulation of radiation effects on microelectronics, soft error analysis, and analog circuit design. He holds a Ph.D., M.S., and B.S. in Electrical Engineering from North Carolina State University. Dr. Massengill's work addresses critical challenges in semiconductor reliability under ionizing radiation, including total ionizing dose (TID) effects, single-event upsets (SEUs), and transient analysis in advanced FinFET technologies. His contributions span radiation-hardened analog-to-digital converters, mitigation techniques for soft errors, and advanced node radiation testing methodologies. His scientific achievements include receiving the Outstanding Conference Paper Award at the 2024 IEEE Nuclear and Space Radiation Effects Conference and the 2014 counterpart. His research has been published in over 50 peer-reviewed articles, emphasizing radiation effects in nanoscale circuits and space electronics. Notable projects include CubeSat-based real-time soft error measurements in low Earth orbits and the RadFxSat flight campaign for characterizing commercial electronics in space. His work bridges semiconductor physics with practical applications in aerospace and high-reliability systems. His educational background includes degrees from North Carolina State University, demonstrating a deep technical foundation in electrical engineering. While no specific grants or advising details are listed here, his prolific publication record underscores his leadership in radiation effects research.

VANESA FERNANDEZ CAVEROمشاهده پروفایل

استادیار

• Electrical Engineering
• Fault Diagnosis
• Induction Motors
• +۳ مورد دیگر

Dr. Vanesa Fernandez Cavero is an Assistant Professor in the Department of Electromechanical Engineering at the Higher Polytechnic School, University of Burgos. Her primary research area is Electrical Engineering, with a focus on fault diagnosis in induction motors, signal processing techniques, and power electronics. She also contributes to educational technology research, particularly in Moodle-based learning frameworks. She holds a PhD from the University of Valladolid (2018), where her dissertation investigated fault detection in inverter-fed induction motors under transient conditions, supervised by Dr. Daniel Moríñigo Sotelo, Dr. Óscar Duque Pérez, and Dr. Joan Pons Llinares. Her recent publications (2021-2025) predominantly explore advanced time-frequency analysis methods for motor fault detection, harmonic monitoring in adjustable speed drives, and innovative diagnostic approaches for broken rotor bars. A secondary research thread involves e-learning strategies, evidenced by her work on Moodle-based collaborative learning.

Hans-Joachim Wunderlichمشاهده پروفایل

استاد

• Computer Architecture
• Hardware Reliability
• Fault Tolerance
• +۷ مورد دیگر

Prof. Hans-Joachim Wunderlich is a Professor at the University of Stuttgart's Institute of Computer Architecture and Computer Engineering, within the Faculty of Computer Science, Electrical Engineering, and Information Technology. His research focuses on hardware reliability, fault tolerance, and testing methodologies for VLSI circuits and embedded systems. He specializes in areas such as delay fault testing under PVT variability, approximate communication, and aging-aware design. Key research interests include robust testing techniques for small delay faults, error-tolerant communication protocols (e.g., RAPPER and Gray code-based approaches), and GPU-accelerated simulation of faults. His work addresses challenges in functional safety, interconnect reliability, and securing reconfigurable architectures against security violations. He explores energy-efficient iterative solvers for approximate computing environments and develops methods for predicting device aging and early life failures. Prof. Wunderlich’s contributions span academic and industrial applications, with a focus on real-time systems and dependable multi-processor systems-on-chip (MPSoCs). His research integrates formal verification, machine learning for defect detection, and hybrid protection schemes for reconfigurable scan networks. Recent work emphasizes stress-aware testing strategies and optimization of sensor data streaming in resource-constrained environments.

• Semiconductor Device Physics
• Nanoscale Electronics
• Monte Carlo Simulation
• +۵ مورد دیگر

Professor Scott Roy is a Professor of Electronics in the Department of Electronics and Electrical Engineering at the University of Glasgow, where he also serves as Senior Senate Assessor for Academic Appeals. His research focuses on device transport phenomena, Monte Carlo simulation techniques, device scaling challenges, and the development of practical compact models for nanoscale devices subject to statistical variability. He is an active member of the Device Modelling and Microelectronics Systems Groups at the university. Professor Roy obtained his B.Sc. in Physics and Electronic Engineering in 1987 from the Department of Natural Philosophy at the University of Glasgow. He completed his Ph.D. in 1994 investigating "Engineering aspects of extended single electronic systems" under the supervision of Prof. John Barker. In the late 1990s, he worked as a Research Assistant with Prof. John Barker and Prof. Asen Asenov on several semiconductor projects including design of parallel processing machines and Monte Carlo simulation of advanced transistor devices. His research centers on the fundamental challenges of nanoscale semiconductor devices, with particular emphasis on statistical variability arising from atomic-scale effects. Professor Roy has made significant contributions to understanding random dopant fluctuations, line edge roughness, and their combined impact on transistor behavior and circuit performance. His work bridges device physics with practical circuit design, developing compact models that accurately capture statistical variations while remaining computationally efficient for circuit simulation. Recent extensions of his research include applications in photovoltaic systems and flexible electronics. Analysis of Professor Roy's publication record shows a consistent focus on statistical variability in nanoscale transistors, with increasing sophistication in modeling approaches and expanding application domains. His most recent work demonstrates evolution from fundamental device physics toward practical applications in photovoltaics and flexible electronics, while maintaining the core expertise in statistical variability analysis that has defined his career. Serves on program committee of ULIS (Ultimate Integration of Silicon) Investigator or co-investigator on grants from SEMATECH, EU, Fujitsu, and 11 EPSRC grants (6 currently active) Professor Roy has published over 100 papers in the field of semiconductor device physics and nanoelectronics. His research group likely includes PhD and Masters students working on various aspects of nanoscale device modeling, though specific student names are not provided in the available information. His work has significant implications for the semiconductor industry as device dimensions continue to shrink and statistical variations become increasingly critical for circuit design and manufacturing yield. As a member of the Device Modelling and Microelectronics Systems Groups, Professor Roy contributes to cutting-edge research in semiconductor device simulation using advanced methodologies including three-dimensional Monte Carlo techniques, drift-diffusion modeling, and non-equilibrium Green's function approaches. The group focuses on addressing the challenges of nanoscale electronics through sophisticated simulation and modeling techniques.

Dominique Ginhacمشاهده پروفایل

استاد

• Hardware design of smart vision systems
• Real-time image processing applications
• VLSI CMOS imaging technology
• +۵ مورد دیگر

Dominique Ginhac is a Professor of Electrical Engineering at the Laboratory of Electronics, Informatics and Image (Le2i UMR 6306) at the University of Burgundy in Dijon, France. He joined Le2i as an assistant professor in 2000 and was promoted to professor in 2009, also becoming head of the Sensors & Hardware Architectures team. In 2010, he became head of the Electronic department of Le2i, and in 2011, he was appointed Deputy Director of Le2i, overseeing approximately 200 people across three scientific departments: Computer Sciences, Vision, and Electronic. Ginhac holds a Master's Degree in Engineering from Polytech Clermont-Fd (1995) and a PhD in Computer Vision from Blaise Pascal University (1999). In 2008, he received his Habilitation qualification (Accreditation to supervise research) from the University of Burgundy. From 2007 to 2009, he was a visiting professor at Université Libre de Bruxelles in the Consciousness, Cognition & Computation lab, expanding his expertise into cognitive science applications for imaging systems. His research focuses on the development of smart imaging technology where sensing and processing are integrated as closely as possible to achieve low cost, low power, and high processing capabilities. His work spans hardware design of smart vision systems, implementation of real-time image processing applications, VLSI CMOS imaging technology, and embedded image processing on DSP/FPGA platforms. His research activities represent the crossroads between algorithmic and hardware solutions dedicated to real-time embedded image processing applications. An analysis of Ginhac's recent publications reveals a strong focus on smart camera and sensor development, particularly in high dynamic range imaging, single-photon detection, and configurable hardware accelerators. His work shows a clear trajectory from fundamental VLSI image sensor design toward increasingly sophisticated integrated systems combining sensing, processing, and specialized applications in medical imaging and real-time vision. His interdisciplinary approach bridges electronics, computer vision, and application-specific system design. Throughout his career, Ginhac has supervised 8 PhD students and published 20 papers in international peer-reviewed journals, 3 book chapters, and more than 50 conference papers. His research has resulted in several significant projects including VerIDIS (Vertically Integrated Digital Image Sensor), CAPTIvA (Asynchronous Photon-counTing Image sensor Architecture), HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera), and ASTICO (Assistance Textile Cognitive). Ginhac leads the Electronic department at Le2i, which is part of a research laboratory under the supervision of the University of Burgundy and the CNRS. His work involves close collaboration with industry partners and has resulted in practical implementations of smart imaging systems for applications ranging from medical monitoring to automotive vision systems. His current research continues to push the boundaries of integrated vision systems, with particular emphasis on 3D-stacked image sensors and photon-counting technologies.

Arijit Raychowdhuryمشاهده پروفایل

استاد

• Low Power Digital Circuits
• Compute-in-Memory (CIM)
• Adaptive Clocking and Power Management
• +۷ مورد دیگر

Arijit Raychowdhury is a Professor and the Steve W. Chaddick School Chair at Georgia Tech's School of Electrical and Computer Engineering (ECE). He leads the Center for the Co-Design of Cognitive Systems (CoCoSys) and directs the DoD-sponsored SCALE Workforce Development Program in SoC Design. Current affiliations: Georgia Tech (ECE), Integrated Circuits and Systems Research Lab Prior affiliations: Intel Corporation (6 years), Texas Instruments (1.5 years) Research interests focus on low-power circuits, compute-in-memory (CIM) systems, cryogenic electronics, and neuro-symbolic AI. His work bridges circuit design with emerging device technologies and machine learning applications. Scientific contributions include: Over 250 publications and 27 patents Leadership in top conferences (ISSCC, VLSI Symposium, DAC, CICC) Pioneering 3D Gaussian Splatting acceleration, adaptive echo-cancellation networks, and CIM architectures Advancing GaN-based power converters and cryogenic CMOS Awards : IEEE Fellow (2022) SRC Technical Excellence Award (2021) Qualcomm Faculty Award (2021, 2020) IEEE/ACM Innovator under 40 (2018) Intel Young Faculty Award (2015) Dimitris N. Chorafas Award (2007) Leadership : • Director of CoCoSys Center • Site Director for SCALE Program • Distinguished Lecturer, IEEE Solid-State Circuits Society

• Causal Machine Learning
• Healthcare Informatics
• Medical Data Analysis
• +۳ مورد دیگر

Dr. Vinod Kumar Chauhan is a Research Fellow at the Institute of Biomedical Engineering, University of Oxford. His work focuses on causal machine learning and healthcare applications, including individualized treatment effects estimation and addressing sample selection bias in medical data. Previously, he held a postdoctoral position at the University of Cambridge and earned his PhD from Panjab University, Chandigarh, India. Education: BSc, MCA, PhD (Panjab University, India). Research interests include causal inference, healthcare informatics, and graph neural networks for EHR analysis. Recent projects involve postoperative atrial fibrillation prediction and optimizing treatment effects for composite outcomes. Key Awards: 2021 Institute for Manufacturing Postdoctoral Award (Cambridge), Travel Grant for Asian Conference on Machine Learning 2017. Selected Talks: Keynote on HyperNetworks (2023 Panjab University), invited talks on treatment effects estimation (IISER Pune, 2023). Labs/Teams: Computational Health Informatics group under Prof. David Clifton. Active in departmental EDI committee roles.

Rabab Abdelfattahمشاهده پروفایل

استادیار

• Computer Vision
• Image Processing
• Deep Learning
• +۵ مورد دیگر

Dr. Rabab Abdelfattah is an Assistant Professor at the University of South Carolina-Columbia. She holds a PhD (2023), MS (2012), and BS (2004) from the University of South Carolina-Columbia and Fayoum University. Her research focuses on computer vision, deep learning, and image processing, with emphasis on generative models, multi-label classification, and aerial imagery analysis. She contributes to energy market forecasting, UAV-based detection, and cybersecurity for IoT systems. Affiliated with the Chain Technology Center (TEC), her work bridges theoretical advancements and real-world applications. Education: PhD - University of South Carolina-Columbia (2023) MS - Fayoum University (2012) BS - Fayoum University (2004) Research Interests: Dr. Abdelfattah's work spans computer vision, deep learning, and machine learning. She develops generative adversarial networks (GANs) for power-line segmentation in aerial images and unsupervised learning frameworks like CDUL for multi-label classification. She also explores prompt engineering, Bayesian optimization for energy forecasting, and privacy-preserving authentication in IoT/drone systems. Her earlier contributions include power-gating techniques in CMOS circuits and network-on-chip (NoC) designs under process variation. Publications Overview: Her recent works (2020–2025) emphasize computer vision, energy systems, and cybersecurity. Key themes include GAN-based image segmentation, CLIP-driven learning, and UAV applications. Earlier research (2011–2015) focused on low-power NoC architectures and semiconductor circuit optimization. Grants & Advising: Details about grants and student advising are not explicitly listed in available texts. Labs/Teams: Affiliated with the Chain Technology Center (TEC), though specific lab/team details are not provided.

ALESSANDRO PEZZOTTAمشاهده پروفایل

پژوهشگر

• Radiation-hard electronics
• Mixed-signal ASICs
• CMOS technology
• +۳ مورد دیگر

Alessandro Pezzotta is a Researcher at the Department of Physics 'Giuseppe Occhialini' (University of Milan-Bicocca), specializing in Radiation-hard electronics and Mixed-signal ASICs for particle detectors. His work focuses on CMOS technology reliability under extreme radiation, Triple-GEM detector readout systems , and low-power analog circuit design . Key research areas: Radiation effects on nanoscale CMOS, detector front-end electronics, high-frequency analog filters Notable projects: GEMINI ASIC development, HL-LHC radiation tolerance studies, MEMS accelerometer readout circuits Collaborations: CERN, INFN, IEEE conferences His recent publications demonstrate expertise in high-dose radiation tolerance (up to 1 Grad), low-power sensor interfaces (90μW consumption), and radiation-stable filter architectures (up to 33MHz bandwidth). He has contributed to multiple conference proceedings and peer-reviewed journal articles on detector electronics and CMOS scaling challenges.

• Information Theory
• Coding Theory
• Communication Systems
• +۸ مورد دیگر

Ragnar Thobaben is a Professor in Communication Theory at the Division of Information Science and Engineering, part of the School of Electrical Engineering and Computer Science (EECS) at KTH Royal Institute of Technology. He has held this position since December 2006 and is affiliated with the CERCES Center for Resilient Critical Infrastructures. His research focuses on information and coding theory, with applications to secure communication systems, machine learning generalization, and DNA-based data storage. He has also contributed to data-driven decision tools for critical care medicine, such as in sepsis management. Education: Ragnar earned a Dipl.-Ing. (M.Sc.) in Electrical Engineering from Christian Albrechts University, Kiel, Germany in 2001, followed by a Dr.-Ing. (Ph.D.) in Electrical Engineering in 2007. His academic journey is complemented by extensive editorial roles, including Editor for IEEE Transactions on Communications (2016–2020) and IEEE Transactions on Information Forensics and Security (2020–2023). He has also served as Technical Program Committee member for major IEEE conferences like GLOBECOM, ICC, and PIMRC, and held organizational roles such as Publicity Chair for the 2011 IEEE Swedish Communication Technologies Workshop and Local-Arrangement Chair for the 2019 IEEE Information Theory Workshop. Research Interests: His work bridges theoretical and applied domains, emphasizing robustness and reliability in communication systems. Key topics include physical-layer security for critical infrastructures, information-theoretic PAC-Bayes bounds in machine learning, and microwave engineering innovations like glide symmetry in antenna design. He also explores interdisciplinary applications, such as data-driven tools for ICU patient monitoring and secure wireless power transfer. Advising & Grants: Thobaben has advised multiple PhD students, including current co-supervision of Martin Lindström (machine learning) and collaborations with Karolinska Institute on medical informatics projects (Anna Sundelin and Navid Korah Soltani under main supervisor Johan Mårtensson). His prior advisees span topics from generalization theory to secure relaying in cognitive networks. His recent publications (2024–2022) highlight advancements in PAC-Bayes bounds, sepsis clinical studies, and antenna engineering.

Soumitra R. Joyمشاهده پروفایل

استادیار

• Electromagnetic Metamaterials
• VLSI
• High-speed Interconnect Design
• +۳ مورد دیگر

Dr. Soumitra R. Joy is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of North Carolina at Charlotte. His research focuses on electromagnetic metamaterials, high-speed interconnect design, and reliability analysis of solid-state devices. He holds a Ph.D. in Electrical Engineering from the University of Michigan (2020), an M.Sc. and B.Sc. from Bangladesh University of Engineering and Technology (2015 and 2012, respectively), and served as a Lecturer at BUET from 2012–2015. His work spans spoof plasmon interconnects, gallium nitride device modeling, and quantum mechanical simulations. Dr. Joy's research interests include developing novel interconnect technologies to overcome RC limitations, analyzing device reliability under extreme conditions, and advancing quantum mechanical models for semiconductor devices. His publications highlight contributions to plasmonic waveguides, PBTI in GaN transistors, and photodetector optimization using NEGF formalism. Current trends in his work emphasize high-speed communication solutions and next-generation semiconductor reliability frameworks. Though no scientific awards are listed, his work has been published in prestigious journals like IEEE Transactions on Communications and Physical Review B. His advising and grants section remains under development, with no listed advisees or funded projects at this time. He is affiliated with labs and teams focused on metamaterial applications and solid-state device innovation.