جست‌وجوی استاد و پژوهشگر

Jason K. Eshraghianمشاهده پروفایل

استادیار

• Neuromorphic Computing
• Spiking Neural Networks
• Memory Circuits
• +۴ مورد دیگر

Jason K. Eshraghian is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Cruz, within the Baskin School of Engineering. He holds a Ph.D. in Electrical and Electronic Engineering from The University of Western Australia and completed his postdoctoral training at the University of Michigan from 2019 to 2022. His research centers on neuromorphic computing , spiking neural networks , and memory circuits , with a strong emphasis on hardware-software co-design for energy-efficient AI. He is the creator of snnTorch , a popular open-source Python library for training and simulating spiking neural networks, widely used in both academia and industry. His recent work reflects a deep integration of circuit design, machine learning, and neuroscience. The research trends indicate a focus on low-power, event-driven computing paradigms, particularly through VLSI and neuromorphic hardware implementations. His publications span top-tier conferences and journals in circuits, AI hardware, and electronic systems. Scientific Awards: 2023 IEEE Transactions on Circuits and Systems Darlington Best Paper Award 2019 IEEE Very Large Scale Integration Systems Best Paper Award Best Paper Award at the 2019 IEEE Artificial Intelligence Circuits and Systems Conference Best Live Demonstration Award at the 2020 IEEE International Conference on Electronics Circuits and Systems Fulbright Fellowship (Australian-American Fulbright Commission) Forrest Research Fellowship (Forrest Research Foundation) Endeavour Research Fellowship (Australian Government) He has been recognized with multiple competitive fellowships and best paper/demonstration awards, reflecting both the quality and impact of his research. While specific grants are not listed, his fellowship support indicates substantial research funding. He has advised students in the areas of neuromorphic systems and AI circuits, though no names are publicly listed in the provided text. He serves professionally as the Secretary of the Neural Systems and Applications Technical Committee and as an Associate Editor for APL Machine Learning , contributing to the advancement of interdisciplinary research in machine learning and physical systems.

Jens Lienigمشاهده پروفایل

استاد

• Electronic Design Automation
• Electromigration
• 3D Integrated Circuit Design
• +۵ مورد دیگر

Jens Lienig has been a Professor at Technische Universität Dresden since 2002, where he directs the Chair of Development and Design of Precision Engineering and Electronics. His research spans Electronic Design Automation (EDA), electromigration analysis, 3D IC design, constraint-driven methodologies, and precision device development. He holds memberships in IEEE, VDE/VDI GMM, and technical committees, and has led conferences like ISPD 2021 as General Chair. Research interests focus on: Reliability Engineering : Electromigration-aware IC design, thermal/stress modeling in interconnects. Advanced Design Automation : 3D physical design algorithms, analog layout generators, constraint propagation. Precision Devices : MEMS sensors, peristaltic pumps, SAW motors, pyroelectric detectors. Recent articles (2019–2025) emphasize electromigration robustness, aerosol sensor signal processing, and open-source EDA tools. Over 15 doctoral students have completed under his supervision, including dissertations on electromigration, MEMS, and infrared sensors.

Peter Matherمشاهده پروفایل

مدرس ارشد

• Signal Processing
• Electronics Engineering
• Renewable Energy Systems
• +۶ مورد دیگر

Dr. Peter Mather is a Senior Lecturer in the Department of Engineering at the School of Computing and Engineering, University of Huddersfield. He leads the Complex Pathway program and is affiliated with the Centre for Efficiency and Performance Engineering and the Secure Societies Institute. His research spans analogue/digital electronics, sensor networks, and sustainable technology. PhD in 'Performance optimisation of VLSI circuits' (University of Huddersfield, 1995) MEng/BEng Electronics Course Leader since 2003 Research focuses on non-linear ADC development , partial discharge sensor networks , weapon detection , renewable energy systems , and optical coding via FPGA . His work contributes to UN SDGs for sustainable energy and security technologies. Recent publications analyze WLAN architectures, chaotic ADCs, and radiometric localization techniques. Scientific contributions include: 15+ publications in 2021 (3) and 2020 (2) with Scopus citations Expertise in wireless sensor networks, pulse position modulation, and visible light communication KTP award for radiation detection innovation (2018) He supervises PhD students in signal measurement and FPGA-based optical coding schemes, leveraging expertise in VHDL implementation and Sigma-Delta ADCs.

Ismail Serdar Ozoguzمشاهده پروفایل

استاد

• Oscillator Engineering
• Current Mode Circuits
• Chaotic Oscillators
• +۷ مورد دیگر

Ismail Serdar Ozoguz is a Professor at Istanbul Technical University, Department of Electronics and Communication Engineering. With over 163 publications and 3020 citations, his work spans oscillator engineering, neural networks, and RF/wireless systems. Institution : Istanbul Technical University Department : Electronics and Communication Engineering Rank : Professor Research interests focus on oscillator engineering , current mode circuits , and chaotic oscillators . Recent work emphasizes neural network applications in filter optimization, antenna modeling, and stochastic computing. Scientific awards include: GEBIP Award (2002) Mustafa Parlar Foundation Research Incentive Award (2003) Research Incentive Award (2004) Projects highlight nonlinear optimization in GaN amplifiers, fractional-order neural networks, and spintronics for communication/memory systems. Collaborations span biomedical engineering, wireless networks, and AI-driven optimization.

Reza Sedaghatمشاهده پروفایل

استاد

• Optimization Problems
• VLSI Design
• Algorithms
• +۳ مورد دیگر

Dr. Reza Sedaghat is a Professor in the Department of Electrical, Computer, and Biomedical Engineering at Toronto Metropolitan University. He holds a PhD in Electrical Engineering from the University of Hannover (1999), an MASc (1994), and BSc (1992) from the University of Kassel. His research focuses on optimization problems, VLSI design, and cross-layer modeling of IoT systems. Professional Engineer (P.Eng) in Ontario IEEE Senior Member Reviewer for IEEE Transactions and Elsevier journals Research interests include: Single/Multi-objective optimization Quadratic assignment problems Security architecture for ciphers Design automation and FPGA systems Scientific contributions highlighted in articles from 2018-2019 demonstrate expertise in swarm computation, hardware security, and IoT optimization frameworks.

• VLSI Design
• Digital Arithmetic
• Analog IC Design
• +۵ مورد دیگر

Uğur ÇİNİ is an Associate Professor in the Department of Electronics Engineering at Uskudar University, where he has served as faculty since 2019. Previously, he worked as a research assistant at Boğaziçi University and Southern Methodist University, and gained industry experience as an R&D engineer at İsbak Inc. and Anka Mikroelektronik Inc. His educational background includes: Undergraduate Degree in Electronics and Communications Engineering from Yıldız Technical University (1999) Master's Degree in Electrical and Electronics Engineering from Boğaziçi University (2003) Doctorate in Electrical and Electronics Engineering from Boğaziçi University (2010) Dr. ÇİNİ's research spans VLSI Design, Digital Arithmetic, Analog IC Design, Circuit Design for Biomedicine, and Embedded Systems. He specializes in CMOS circuit design, biomedical instrumentation, and FPGA-based implementations, with recent projects focusing on energy harvesting converters and high-speed logic circuits for practical applications. His publication record (2017-2023) demonstrates expertise in analog/digital circuit design for biomedical instrumentation, display technologies, and reconfigurable systems. Key trends include low-power optimization, precision amplifier development, and current-mode circuit innovations addressing real-world engineering challenges in medical devices and display drivers. No scientific awards are listed in the available information. He has supervised graduate theses on energy harvesting converters (2024), source-coupled logic (2023), and FPGA implementations (2022). Administratively, he advises 100-150 students, served as Deputy Head of Department (2021-2024), and participates in Quality, Internship, Erasmus, and International Students committees. As laboratory responsible since 2020, he led the 2024 establishment of the Power Systems and Electrical Machines Laboratory, demonstrating hands-on leadership in educational infrastructure development.

• Computer Architecture
• Edge Artificial Intelligence
• Hardware Acceleration
• +۴ مورد دیگر

Pengbo Yu is a researcher at the Embedded Systems Laboratory (ESL) within the School of Engineering at École polytechnique fédérale de Lausanne (EPFL). His work focuses on developing energy-efficient hardware architectures for edge artificial intelligence applications, with particular emphasis on variable-precision computing techniques. His research interests span computer architecture, edge AI hardware acceleration, neural network quantization, memory systems, and low-power computing. Dr. Yu's work bridges the gap between algorithmic robustness in quantized neural networks and specialized hardware implementations that can dynamically adjust precision to maximize efficiency in resource-constrained environments. His recent publications demonstrate a strong focus on the SoftSIMD paradigm, Dynamic Bitwidth-Frequency Scaling techniques, and near-memory computing solutions that achieve significant energy savings (up to 67%) compared to state-of-the-art approaches. His work shows consistent output in top venues including IEEE Transactions on VLSI Systems and ACM Transactions on Embedded Computing Systems. Dr. Yu's research is supported by multiple funding agencies including EC H2020, H2020, and SNSF. He maintains active collaborations with researchers across Europe, including institutions like IMEC and National Technical University of Athens. His laboratory work centers around the Embedded Systems Laboratory at EPFL, where he develops and validates novel hardware architectures for energy-efficient AI acceleration. Current projects include silicon validation of his proposed architectures on open-source RISC-V platforms and integration of variable-precision computing techniques into memory systems.

Guy Evenمشاهده پروفایل

استاد

• Approximation Algorithms
• VLSI Design
• Computer Arithmetic
• +۲ مورد دیگر

Prof. Guy Even serves as a Professor in the School of Electrical Engineering at Tel Aviv University's Iby and Aladar Fleischman Faculty of Engineering. His research focuses on theoretical and applied aspects of computer engineering, with primary expertise in: Approximation algorithms for NP-complete problems in VLSI design Computer arithmetic systems Floating-point unit architecture Systolic array implementations Contact is available via email at guy@eng.tau.ac.il , phone (03-6407769), fax (03-6405027), and office location in Computer and Software Engineering room 202.

• RF/mm-Wave/THz Wireless Transceivers
• High-Speed SerDes
• PLLs/Frequency Synthesizers
• +۴ مورد دیگر

Xiaolong Liu serves as Assistant Professor at Southern University of Science and Technology's School of Microelectronics. His academic journey includes a Ph.D. from Hong Kong University of Science and Technology (2019), M.E. from Tsinghua University (2014), and B.E. from Beijing University of Aeronautics and Astronautics (2010). Prior to his current position, he worked as Staff Engineer at eTopus Technology in Silicon Valley (2019-2021) and completed a postdoc at HKUST. Ph.D. in Electronic and Computer Engineering, Hong Kong University of Science and Technology (2019) M.E. in Microelectronics, Tsinghua University (2014) B.E. in Electronic Engineering, Beijing University of Aeronautics and Astronautics (2010) Dr. Liu's research spans cutting-edge RF/mm-Wave/THz integrated circuit design, focusing on high-performance signal generators , ultra-wideband transceivers , and low-power frequency synthesis . His work addresses critical challenges in 5G/6G communications, terahertz spectroscopy, and high-speed wireline interfaces through innovative CMOS architectures. Technical emphases include varactor-less VCOs, harmonic enhancement techniques, and magnetic tuning mechanisms for millimeter-wave systems. His publication portfolio demonstrates consistent leadership in IEEE flagship journals/conferences (JSSC, TMTT, ISSCC, VLSI), with recent work advancing Class-F oscillators, sub-sampling PLLs, and sub-THz synthesizers. Notable trends include migration toward sub-THz frequencies (2023-2025) , multi-core oscillator architectures , and elimination of harmonic tuning for simplified design. IEEE VLSI Paper Technical Highlights (2019) IEEE CICC Invited Talk (2019) IEEE TVLSI 2023 Best Reviewer Award Top 4 Most Downloaded Paper in TCAS-II (July 2022) Dr. Liu actively mentors students through SUSTech's graduate programs, with advisees consistently earning university-level thesis awards and conference recognitions. His lab maintains strong industry ties through silicon validation and collaborates on cutting-edge tapeouts in 7nm/16nm nodes. Current projects focus on cryo-CMOS interfaces for quantum computing and ultra-wideband transceivers for 6G applications. His research group operates within SUSTech's state-of-the-art microelectronics facility, specializing in mm-Wave/THz characterization and high-speed SerDes validation. The team maintains partnerships with semiconductor foundries for advanced-node prototyping and collaborates with industry leaders on real-world implementation challenges.

• Digital Signal Processing
• Image Processing
• Computer Vision
• +۲ مورد دیگر

Dimitrios Kosmopoulos serves as Professor in the Computer Engineering and Informatics Department at the University of Patras, Greece, with extensive experience across multiple academic institutions including National Technical University of Athens (NTUA), Rutgers University, and University of Texas at Arlington. His research bridges theoretical computer science with practical applications in accessibility, agriculture, and cultural heritage preservation. Education: B.Eng. in Electrical and Computer Engineering, National Technical University of Athens (1997) PhD in Electrical and Computer Engineering, National Technical University of Athens (2002) Professor Kosmopoulos' research integrates computer vision, machine learning, and signal processing to solve real-world problems. His primary focus areas include sign language recognition systems for museum accessibility, precision agriculture applications for crop monitoring and disease detection, and digital restoration of ancient scripts like Mycenaean Linear B. His methodological innovations frequently involve geometric analysis, time-series modeling, and multimodal data fusion techniques that advance both theoretical frameworks and practical implementations. Analysis of his recent publications (2023-2025) reveals three dominant research thrusts: accessibility technologies for deaf communities (particularly museum navigation systems), agricultural automation using computer vision (olive grading, tomato disease detection), and computational archaeology (Linear B tablet restoration). His work consistently employs cutting-edge approaches including geometric knowledge distillation, coupled learning architectures, and 3D motion analysis, demonstrating strong interdisciplinary connections between computer science, agriculture, and humanities. No scientific awards were documented in the provided source materials. While specific advising details and grant information were not explicitly stated, his leadership in projects like HealthSign (sign language healthcare systems) and MuseLearn (museum accessibility platforms) indicates substantial research funding and collaborative supervision activities spanning computer vision, robotics, and assistive technology domains. Professor Kosmopoulos operates within the Division of Hardware and Computer Architecture at the University of Patras, collaborating with the Computer Technology and Architecture Laboratory, VLSI Microelectronics Laboratory, Signals and Telecommunications Laboratory, and Computer Communications Networks Laboratory. His current research integrates these facilities to develop systems like the SignGuide project for museum tours and frameworks for early pest detection in greenhouse crops, emphasizing practical implementations of machine learning in constrained environments.

• Computer Hardware and Architecture
• VLSI Design

Rajat Moona is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur). Professor Moona's research interests focus on Computer Hardware and Architecture and VLSI Design . His work contributes to the advancement of computer systems design and semiconductor technology, with applications in high-performance computing and embedded systems. His research likely spans theoretical foundations and practical implementations in processor architecture, circuit design, and system optimization. He received his PhD from the Indian Institute of Science (IISc) Bangalore, one of India's premier research institutions. His office is located in room CS 221 at IIT Kanpur, where he can be reached at phone number 0512-259-7652/7638 or via email at moona@iitk.ac.in.

• Algorithms
• Parallel Processing
• VLSI
• +۲ مورد دیگر

Sanjeev Saxena serves as Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur, where he has established himself as a prominent researcher in algorithm design and parallel computing. His research spans five key domains: Algorithms - specializing in efficient computational methods and theoretical foundations Parallel Processing - developing architectures for multi-processor computation VLSI - exploring algorithm-hardware integration for circuit design Data Structures - innovating in information organization techniques Heuristics - creating practical solutions for complex computational problems Professor Saxena's publication timeline reveals a consistent research trajectory focused on computational efficiency, with early work on VLSI parallel algorithms evolving into broader applications in data structures and scientific computing. His most recent publications demonstrate expertise in translating theoretical computer science into practical implementations for scientific and engineering applications. His educational contributions include authoring the textbook "Java for Scientists and Engineers" (2008), which bridges programming knowledge with scientific applications, reflecting his commitment to computer science education.

Kees Goossensمشاهده پروفایل

استاد

• Embedded Systems
• Real-Time Systems
• Networks-on-Chip
• +۳ مورد دیگر

Kees Goossens is Full Professor of Real-time Embedded Systems in the Electronic Systems group at Eindhoven University of Technology (TU/e). He leads the CompSOC Lab focused on predictable and composable embedded systems. His research spans composable virtualization, real-time systems, low-power design, and FPGA-based dynamic partial reconfiguration. Previously at NXP Semiconductors, he pioneered networks-on-chip research including the Aethereal NoC architecture. His research interests include: Composable and predictable embedded systems Real-time networks-on-chip (NoC) Memory management and controllers FPGA reconfiguration Hardware verification Low-power electronic design Publication analysis shows consistent focus on real-time systems, networks-on-chip, memory controllers, and embedded systems design, with recent expansion into machine learning applications for networking and error-correction coding. His work frequently addresses automotive and industrial control applications. Editorial contributions include: ACM TODAES editorial board (since 2009) Associate editor for Springer DAEM journal (since 2006) Guest editor for multiple NoC special issues He leads the CompSOC laboratory developing virtualized execution platforms for mixed-criticality systems. Current educational activities include courses on Systems-on-Chip, Embedded Systems, and Computer Architecture.

François-Raymond Boyerمشاهده پروفایل

دانشیار

• Computer Architecture
• VLSI Systems
• Microelectronics
• +۴ مورد دیگر

François-Raymond Boyer is an Associate Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He holds a B.Sc. and Ph.D. from Université de Montréal and teaches courses in programming and digital audio. His research spans: Computer architecture and VLSI systems Network processing and traffic management Digital audio signal processing Hardware acceleration and optimization He is affiliated with ReSMiQ (Strategic Cluster for Microsystems) and OICRM (Music Research Observatory). Recent publications focus on 5G network processing, modular programming frameworks, and high-speed traffic management architectures, primarily in IEEE Access and IEEE Transactions on VLSI Systems. Professor Boyer has supervised 3 PhD and 6 Master's students, with research topics including network architecture, audio processing, and hardware design. No scientific awards are mentioned in the available records.

• Machine Learning
• Artificial Intelligence
• Cognitive Neuroscience
• +۹ مورد دیگر

Dr. Adrian Rendon Nava is a Researcher at Robert Gordon University's School of Computing, Engineering & Technology, affiliated with the Robotics & Autonomous Systems Research Group and Environment, Energy & Sustainability research theme. His work bridges electronics engineering, machine learning, and industrial applications through active research projects and specialized teaching. His academic credentials include: Bachelor in Electronics Engineering with Computing Major (Autonomous Metropolitan University, 2000) MSc in Microelectronics (National Polytechnic Institute, 2005-2007) PhD in Communications and Electronics (National Polytechnic Institute, 2014) Dr. Rendon Nava's research centers on Machine Learning and AI applications for IoT and Industry 4.0 systems, with specialized expertise in Deep Learning and One-shot Learning for cognitive neuroscience. His technical foundation in Microelectronics VLSI Circuit Design and embedded systems enables practical implementations in robotics and autonomous systems. Current work focuses on developing a novel composite inspection probe prototype with integrated data-logging capabilities. His 2025 publication on Jabi Lake water quality demonstrates interdisciplinary collaboration, applying chemometric analysis to environmental monitoring while maintaining his core focus on electronics and AI-driven solutions. This reflects his approach of leveraging computational tools for real-world engineering challenges. Dr. Rendon Nava actively supervises PhD candidates and teaches core engineering modules including Mechatronics, Metrology, and Analogue Electronics. His supervision emphasizes practical electronics implementation and AI integration in industrial systems. Within the Robotics & Autonomous Systems Research Group, he contributes to projects advancing sensor technologies and autonomous inspection systems, particularly through his leadership in composite material assessment instrumentation development.