جست‌وجوی استاد و پژوهشگر

Paola Arlottaمشاهده پروفایل

استاد

• Neuroscience
• Developmental Biology
• Stem Cell Biology
• +۳ مورد دیگر

Paola Arlotta is the Golub Family Professor and Chair of the Department of Stem Cell and Regenerative Biology at Harvard University. She is a principal faculty member at the Harvard Stem Cell Institute, an Institute Member at the Broad Institute, and an Associate Member of the Stanley Center for Psychiatric Research. Her career spans groundbreaking work in cortical development and regenerative neuroscience. Education: M.S. in Biochemistry from the University of Trieste, Italy Ph.D. in Molecular Biology from the University of Portsmouth, UK Postdoctoral training in Neuroscience at Harvard Medical School Dr. Arlotta’s research focuses on defining molecular pathways that govern the differentiation of neural progenitors into cortical projection neurons, with a special interest in corticospinal neurons linked to ALS and spinal cord injury. Her lab bridges developmental neuroscience with stem cell engineering to study human-specific cortical development using 3D organoid models, aiming to uncover mechanisms of neurodevelopmental diseases. Scientific Contributions: 2024: Discovery of individual susceptibility to neurotoxicity in brain chimeroids 2024: Microglia’s role in fetal brain inflammation response 2022: Autism risk genes affect asynchronous neuron class development 2019: Reproducible generation of human cortical diversity in organoids Scientific Awards: Elected to the National Academy of Medicine for pioneering brain organoid research Her lab employs advanced techniques like single-cell RNA sequencing, FIN-seq for frozen tissue analysis, and in utero electroporation. She also explores neuronal reprogramming and myelin dynamics across axons, contributing to understanding cortical circuit assembly and repair.

• High-Performance Computing (HPC)
• Computational Fluid Dynamics
• Quantum Computing
• +۳ مورد دیگر

Stefano Markidis is a leading researcher in High-Performance Computing (HPC) and quantum computing. His work focuses on developing advanced simulation frameworks, such as the Neko framework for computational fluid dynamics, and optimizing algorithms for heterogeneous architectures. He collaborates extensively with institutions and researchers globally, contributing to fields like plasma physics, quantum systems, and machine learning applications. His research emphasizes scalability, performance optimization, and the integration of cutting-edge technologies like GPU acceleration and quantum computing. Key research interests include extreme-scale simulations, quantum algorithms, and in-situ data analysis techniques. He has published over 200 articles, with recent work addressing challenges in NISQ systems, tensor network simulations, and CUDA-based performance enhancements. His contributions span theoretical and applied domains, bridging computational methods with real-world applications in fusion energy, materials science, and space exploration. Notable collaborations include projects with Philipp Schlatter, Niclas Jansson, and the NISQ application development community. Markidis also explores hybrid frameworks combining classical and quantum computing, aiming to leverage emerging hardware for scientific breakthroughs.

• High-performance computing
• Modelling of Acoustic Wave devices
• Embedded system design
• +۳ مورد دیگر

Dr. Glenn Matthews is a Senior Lecturer in the School of Engineering at RMIT University, specialising in Electrical and Computer Engineering. He holds positions in both academic and research capacities, including Principal Investigator roles at CSIRO and Smart Services CRC. His teaching responsibilities include coordinating undergraduate courses such as Introduction to Engineering Computing and Engineering Design modules. Dr. Matthews' research focuses on high-performance computing, acoustic wave device modeling using Finite Element Method (FEM), and embedded system design. Notable projects include developing FEM software for SAW device analysis and investigating asynchronous computing architectures for high-throughput systems. He has supervised numerous research projects spanning machine learning applications in clinical analysis, gas sensing technologies, and neuromorphic learning. His work integrates hardware-software co-design principles, with contributions to radar SLAM systems, mercury vapor sensors, and neural network frameworks like SwiftSpike. Dr. Matthews collaborates with industry partners through ARC Linkage Grants and maintains affiliations with IEEE and DSP/Embedded Systems groups. His research outputs include over 20 peer-reviewed articles, with impactful contributions to sensor technology, circuit design, and biomedical applications.

Wen-Ben Joneمشاهده پروفایل

دانشیار

• VLSI system design
• low-power VLSI systems
• many-core micro-processor design
• +۳ مورد دیگر

Wen-Ben Jone is an Associate Professor at the University of Cincinnati 's Department of Electrical Engineering & Computing Systems. He previously held positions as Assistant/Associate Professor at New Mexico Institute of Mining and Technology and Visiting Associate/Full Professor at National Chung-Cheng University, Taiwan. His research focuses on VLSI system design, low-power circuits, and fault-tolerant testing methodologies. He has advised over 70 graduate students and authored/co-authored numerous papers in top-tier journals and conferences. Education : PhD: Case Western Reserve University (Computer Engineering, 1987) MS: National Chao-Tung University (Computer Engineering, 1981) BS: National Chao-Tung University (Computer Science, 1979) Research Interests : Reliable VLSI design and testing Low-power and fault-tolerant circuits Many-core processor architectures Parallel computing and debugging tools Awards : 2003 IEEE Donald G. Fink Prize Paper Award 2008 Best Paper Award (International Symposium on Low-Power Electronics) 2012 Best Paper Award (VLSI Design, Automation & Test) Grants : $390k NSF Grant (CCF-0541103) for cache optimization techniques His work emphasizes practical solutions in VLSI testing and reliability, with a focus on low-power strategies and resilient system design.

Kristofer Reyesمشاهده پروفایل

دانشیار

• Applied Mathematics
• Computational Chemistry
• Materials Science
• +۶ مورد دیگر

Kristofer Reyes is an Associate Professor in the Department of Materials Design and Innovation at the University at Buffalo (School of Engineering and Applied Sciences). His research focuses on computational and statistical methods applied to materials science, particularly in developing machine learning frameworks for small-data regimes. He leads the Computational and Statistical Material Science (CSMS) Lab, which emphasizes Bayesian models, reinforcement learning, and fusion of physics-based knowledge. Education: PhD in Applied and Interdisciplinary Mathematics, University of Michigan, 2013 BS in Computer Science and Mathematics, Purdue University, 2004 Research Interests: Reyes' work bridges computation, mathematics, and materials science. Key areas include: - Autonomous experimentation systems (e.g., self-driving fluidic labs) - Bayesian optimization and decision-making under uncertainty - Machine learning for nanomaterials synthesis (e.g., perovskite nanocrystals) - Integration of physics-informed models in AI workflows - High-cost experimental design optimization Recent Achievements: SMARTDOPE paper awarded 'Best in Advanced 2023' Developed AlphaFlow for autonomous chemical synthesis Pioneered 'self-driving labs' for materials discovery Labs & Teams: CSMS Lab (134 Bell Hall) focuses on problem-fluent models for materials research. Current projects include quantum circuit optimization, bio-chemical pathway modeling, and sustainable nanomanufacturing. Collaborates with industry and national labs on AI-driven materials development.

• Electromagnetic Compatibility
• Electromagnetic Interference
• Signal Integrity
• +۳ مورد دیگر

Victoria Shao is a Teaching Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois Urbana-Champaign (UIUC). She specializes in electromagnetic compatibility (EMC), computational electromagnetics (CEM), and high-power microwave technology. Her work focuses on advancing numerical methods for transient electromagnetic analysis, stochastic modeling in complex enclosures, and the design of integrated electronic systems. Affiliations: Holonyak Micro and Nanotechnology Laboratory at UIUC Education: B.S. in Electrical Engineering (USTC, 2003), Ph.D. in Electromagnetics (Chinese Academy of Sciences, 2008) Prior positions: Researcher at ElectroScience Laboratory, Ohio State University (2009–2014) Research Interests: Dr. Shao’s work bridges computational methods with practical engineering challenges, emphasizing: Stochastic Green’s function approaches for statistical wave physics Multi-physics analysis of electronic systems Development of scalable algorithms for high-performance computing Nanotechnology integration for 3D RF components Her research has led to innovations in: Self-rolled-up membrane (S-RuM) nanotechnology for compact inductors Supercomputing-driven radio wave propagation models for urban environments Parallel-in-space-and-time electromagnetic simulation methods Awards: She has received multiple recognitions, including Best EMC Paper finalist awards (2022, 2023) and a Best Paper Award in IEEE Transactions (2017). Teaching and Contributions: Dr. Shao teaches core ECE courses such as ECE 110, ECE 210, and specialized EMC courses (ECE 498 YS3/YVS). She pioneers educational strategies using visualization tools and asynchronous learning to enhance STEM accessibility.

Erik Brunvandمشاهده پروفایل

استاد

• Computer Architecture
• VLSI Systems
• Asynchronous Circuits
• +۳ مورد دیگر

Erik Brunvand is a Professor at the School of Computing , University of Utah, and holds an Adjunct Professor position in the Department of Electrical and Computer Engineering. He was a University Professor from 2014–2016 and is currently on leave at the National Science Foundation (CISE/CNS division) (Fall 2019–2021). His research focuses on computer architecture, VLSI systems, asynchronous circuits, and graphics processing, particularly GPU architectures for ray tracing. Teaching includes courses like Digital VLSI Design , Embedded Systems and Kinetic Art , and interdisciplinary classes like Making Noise: Sound Art and Digital Media . He has organized the ASYNC international symposium series and contributed to projects such as TRaX (ray tracing architecture) and ACK (asynchronous design framework). Grants include NSF awards for GPU architectures, ray tracing applications, and microengine-based control systems. His work spans hardware design, sustainable computing, and arts/technology collaborations, including kinetic art installations and educational initiatives like circuit bending.

José María Guerrero Rodríguezمشاهده پروفایل

استاد

• Electronics
• Sensor Design
• Space Instrumentation
• +۳ مورد دیگر

José María Guerrero Rodríguez serves as a Professor in the Department of Automation, Electronics, Architecture and Computer Networks Engineering at the University of Cadiz, Spain. His research is anchored within the TIC138 Electronic and Electromagnetic Design group under the PAIDI Areas for Information and Communication Technologies, focusing on advanced instrumentation systems for space and industrial applications. He completed his doctorate at the University of Cadiz in 2009 with the thesis A contribution to reconfigurability in intelligent instrumentation based on sensors and programmable devices , supervised by Dr. Diego Gómez Vela. His educational background forms the foundation for his expertise in sensor reconfigurability and programmable device integration. Guerrero Rodríguez's research spans Electronics, Embedded Systems, and Space Instrumentation, with significant contributions in magnetic measurement subsystems for CubeSats, low-frequency noise reduction in orbital environments, and neuromorphic sensor design. His work bridges theoretical electromagnetic modeling with practical embedded implementations, particularly in spiking neuron-based movement classification and optical flow algorithms for real-time tracking. Educational innovation is a secondary focus, evidenced by flipped classroom methodologies in analog electronics instruction. Analysis of his 2020-2024 publications reveals three dominant trends: (1) Space instrumentation for CubeSats emphasizing magnetic field measurement accuracy, (2) Novel sensor architectures using asynchronous vision and spiking neurons for flame detection and movement tracking, and (3) Educational technology integration in engineering pedagogy. These areas demonstrate consistent progression from fundamental sensor design to in-orbit validation. No scientific awards were documented in the provided source material. While the source references thesis supervision and funding sections, specific student names, grant details, or advising methodologies remain undisclosed. His research direction suggests ongoing collaboration with space technology initiatives, particularly in low-technology-readiness-level subsystem validation. Guerrero Rodríguez operates within the TIC138 research group, which specializes in electronic and electromagnetic design for aerospace applications. The group's work centers on advancing the technological maturity of measurement systems through CubeSat platforms, with recent focus on in-orbit demonstrators for magnetic field characterization in low-Earth orbit environments.

• Insect neuroethology
• Sensory systems in dipterans
• Flight control and stability
• +۳ مورد دیگر

Professor Jessica Fox is a faculty member in the Department of Biology at Case Western Reserve University, where she conducts cutting-edge research on insect sensory systems and flight control mechanisms. Her work bridges neuroscience, biomechanics, and ethology to unravel how flies process sensory information for navigation and behavior. Her research program focuses on: Neural encoding in dipteran sensory systems Integration of haltere mechanosensation and visual inputs Flight stability and gaze control mechanisms Evolutionary adaptations in insect sensory organs Neuromodulation of sensorimotor pathways Recent publications demonstrate a consistent emphasis on haltere function as a biological gyroscope, revealing how flies dynamically tune sensory processing during flight. Her experimental approaches combine tethered flight assays, optogenetics, high-speed videography, and neural recordings to dissect sensorimotor transformations across diverse dipteran species. Professor Fox leads the Fox Lab at Case Western Reserve University, which maintains active collaborations with neuroscience and engineering groups to develop bio-inspired robotics models based on insect flight principles. The lab emphasizes comparative studies across fly species to identify conserved and specialized neural mechanisms.

• Microelectronics
• Image Sensors
• Bio-inspired Algorithms
• +۳ مورد دیگر

Juan Antonio Leñero Bardallo is a Professor at the University of Seville, Faculty of Physics, Department of Electronics and Electromagnetism. His research focuses on bio-inspired microelectronics, event-driven vision sensors, and CMOS integration techniques. Research Group: MICROELECTRÓNICA ANALÓGICA Y DE SEÑAL MIXTA Key Projects: SAMANTA2 (robotic vision), CAVIAR (event-based vision), VULCANO (event-driven imaging) His work spans asynchronous image sensors, thermography for medical diagnostics, stacked diodes for energy harvesting, and neuromorphic engineering. Recent publications highlight low-power sun sensors, self-powered imaging systems, and thermographic applications in dermatology. He has contributed to books on analog electronics and radiation detection. Patents include solar position sensors and electron energy detectors for scanning electron microscopy. His teaching subjects cover experimental techniques, integrated sensor design, and bio-inspired algorithms.

Hossein Saidiمشاهده پروفایل

استاد

• High Speed Switching Networks
• QoS Algorithms in Broadband Networks
• Internet Security
• +۴ مورد دیگر

Hossein Saidi is a Professor in the Department of Electrical and Computer Engineering at Isfahan University of Technology, Iran. His research spans High Speed Switching Networks, QoS Algorithms in Broadband Networks, Internet Security, Cryptography, Wireless Networks, Information Theory, and Coding. Research Interests: High Speed Switching Networks, QoS Algorithms, Internet Security, Cryptography, Wireless Networks, Information Theory, Coding Email: hsaidi@iut.ac.ir His recent publications focus on Software-Defined Networking (SDN), Blockchain Consensus, Wireless IoT, and Energy Management Systems. Key themes include network optimization, security protocols, distributed systems, and hardware design.

Christoph Lenzenمشاهده پروفایل

استاد

• Distributed Computing
• Clock Synchronization
• Randomized Load Balancing
• +۵ مورد دیگر

Christoph Lenzen is a Professor at CISPA Helmholtz Center for Information Security since July 2021. Previously, he served as a Group Leader at the Max Planck Institute for Informatics (2014-2021), and held postdoctoral positions at MIT CSAIL (2013-2014), Weizmann Institute (2012), and Hebrew University (2011). Research Interests Design and analysis of distributed algorithms Clock synchronization and adversarial fault tolerance Randomized and self-stabilizing systems Hardware algorithms for fault-tolerant systems Grants and Awards ERC Proof-of-Concept Grant (2021) ERC Starting Grant (2017-2022) ETH Zurich Medal for Outstanding Thesis (2011) Education Ph.D. in Computer Science (2011), ETH Zurich Diploma in Mathematics (2007), University of Bonn Teaching Clock Synchronization and Adversarial Fault Tolerance (2022 winter) How To Clock Your Computer (2022 summer) Theory of Distributed Systems (2019 winter, 2020 winter, 2018 winter, 2017 winter, 2016 winter, 2015 winter)

Kent Palmkvistمشاهده پروفایل

دانشیار

• Digital Electronics
• Mixed-Signal Electronics
• FPGA Design
• +۵ مورد دیگر

Kent Palmkvist is an Associate Professor at Linköping University, affiliated with the Department of Electrical Engineering (ISY) and the Division of Electronics and Computer Engineering (ELDA). His work bridges research and education in digital, analog, and mixed-signal electronics, with a focus on programmable systems and processor design. Research Interests: Digital and mixed-signal circuit design FPGA-based high-performance computing Asynchronous (GALS) system architectures Low-power and energy-efficient design techniques Calibration and testing of high-resolution ADCs Hardware implementation of signal processing algorithms His recent publications highlight expertise in large-scale FFT implementations on FPGAs and innovative design flows for asynchronous systems, indicating a strong focus on hardware efficiency and scalability. Scientific Contributions: Pioneered design methodologies for integrating asynchronous modules using conventional synchronous tools Developed high-throughput FFT architectures capable of processing 1 million points on a single FPGA Advanced calibration techniques for flash ADCs using histogram methods Advising and Grants: While no formal students or grant details are listed in the provided text, his collaborative publications suggest active engagement in research teams and potential supervision of graduate students. His work likely involves industry and research collaborations, given the applied nature of his research and ISY’s emphasis on industrial partnerships. Labs and Teams: Kent Palmkvist is a key member of the Division of Electronics and Computer Engineering (ELDA), where he contributes to research in advanced electronic systems. The division conducts cutting-edge work in both analog and digital domains, supporting a collaborative environment for innovation in electronics and computing.

Luciano Lavagnoمشاهده پروفایل

استاد

• Asynchronous Circuit Design
• Embedded Systems
• Logic Synthesis
• +۴ مورد دیگر

Luciano Lavagno is a prominent academic in computer science and engineering, specializing in asynchronous circuit design, logic synthesis, and embedded systems. He has collaborated extensively with researchers like Alberto Sangiovanni-Vincentelli, Joaquim Cortadella, and Alex Yakovlev. Key contributions: Hazard-free asynchronous circuits, STG manipulation, FPGA synthesis frameworks Research focus: Formal verification, design methodologies, hardware-software co-design His publications from 1991–2025 demonstrate sustained innovation in asynchronous control logic, embedded system validation, and machine learning hardware acceleration. Notable works include SIS (sequential synthesis) and Petrify (asynchronous controller tool). While his 2018 DiracDeltaNet work extended into neural network optimization, his core expertise remains rooted in formal methods for circuit design.

Vincent Leungمشاهده پروفایل

دانشیار

• RF/mixed-signal ICs
• Ultra-low-power IoT circuits and systems
• ICs for neurotechnology and biomedical applications
• +۷ مورد دیگر

Dr. Vincent Leung is an Associate Professor in the Department of Electrical and Computer Engineering at Baylor University, College of Engineering. He leads the Bio-Electronics and RFIC (BEaR) Lab and maintains active research in neurotechnology and RF/mm-Wave ICs. He also holds concurrent appointments as a Faculty Research Engineer at the Naval Surface Warfare Center (Crane, IN) and as a Visiting Associate Professor at Brown University (Providence, RI). PhD, Electrical and Computer Engineering, University of California, San Diego (2004) M.Eng., Electrical Engineering, McGill University (1997) B.Eng. (Honors), Electrical Engineering, McGill University (1995) Dr. Leung's research focuses on cutting-edge integrated circuit design for biomedical and wireless applications. His work spans RF/mixed-signal ICs , ultra-low-power IoT systems , neural interfaces , and wireless communication electronics for both commercial and military use. He has extensive industry experience from Analog Devices, IBM, Silicon Labs, and Qualcomm, where he led RFIC development for 3G/4G smartphones. His recent publications show a strong trend toward distributed implantable systems and wireless neural interfaces , with high-impact work in Nature Communications and Nature Electronics . These studies emphasize asynchronous wireless networks , energy-efficient power transfer , and machine learning-enhanced circuit design , reflecting a convergence of biomedical engineering, low-power electronics, and AI-driven hardware innovation. Dr. Leung has taught graduate courses in Analog VLSI and RFICs at Columbia University and UCSD. He has co-authored over 50 technical papers and holds 13 U.S. patents. His lab is actively engaged in federally relevant research, particularly through collaboration with the Naval Surface Warfare Center, indicating significant grant and defense-related funding. He mentors students through the BEaR Lab and contributes to interdisciplinary neurotechnology initiatives. The BEaR Lab (Bio-Electronics and RFIC Lab) at Baylor University, led by Dr. Leung, focuses on developing advanced integrated circuits for biomedical and wireless applications. The lab specializes in low-power, high-performance RF and mixed-signal ICs for neurotechnology, IoT, and defense systems, fostering innovation in implantable and distributed sensor networks.