جستجوی استاد راهنمای دانشگاهی

Rikky Muller is an Associate Professor of Electrical Engineering and Computer Sciences at UC Berkeley, holding the S. Shankar Sastry Professorship in Emerging Technologies. She is Co-director of the Berkeley Wireless Research Center (BWRC), a Core Member of the Center for Neural Engineering and Prostheses (CNEP), and an Investigator at the Chan-Zuckerberg Biohub. Her research focuses on implantable/wearable medical devices, low-power wireless systems, and neurotechnology for neurological applications. Education: PhD (2013), UC Berkeley; BS and M.Eng. (2004), MIT, all in EECS. Prior roles include IC designer at Analog Devices and co-founder of Cortera Neurotechnologies (acquired). Research interests include neural interfaces, closed-loop neuromodulation, and biomedical microelectronics. Notable contributions include Neural Dust (ultrasonic implants), wireless EEG systems, and seizure prediction hardware. Awards: MIT TR35 Innovator, NAE Gilbreth Lectureship, NSF CAREER Award, IEEE SSCS New Frontier Award Grants: Bakar Fellows, Hellman Fellowship, NSF CAREER Labs: Muller Lab (UC Berkeley EECS), Chan-Zuckerberg Biohub collaborations

• Neural Engineering
• Medical Devices
• Low-Power Electronics
• +۶ مورد دیگر

Dr. Philip R. Holland is a Reader in Neuroscience at King's College London, affiliated with the Wolfson Sensory, Pain and Regeneration Centre within the School of Neuroscience and the Institute of Psychiatry, Psychology & Neuroscience. His research focuses on understanding migraine mechanisms and developing therapies, with a particular emphasis on neurovascular interactions and pain pathways. He leads a team funded by organizations like the Medical Research Council, Wellcome Trust, and European Research Council. Dr. Holland earned his PhD under Prof. Peter Goadsby at University College London, followed by postdoctoral research at UCSF and the University of Edinburgh. He actively engages in teaching, public awareness, and editorial roles (e.g., Cephalalgia). Key awards include the 2020 Medical Research Foundation Emerging Leaders Prize. His work spans clinical and translational research, aiming to bridge basic science with patient care. Education: PhD in Neuroscience, Postgraduate Certificate in Academic Practice (King's College London). External Roles: External Examiner at UCL, Science Editor of CGRP Forum, Associate Editor of Cephalalgia. Grants/Projects: Investigates trigeminal autonomic cephalalgias, neuroendocrine signaling, and novel therapies like cannabidiol combinations. Labs/Teams: Leads a migraine-focused research group exploring neurobiological and pharmacological interventions.

• Neuroscience
• Migraine Research
• Headache Disorders
• +۳ مورد دیگر

Andrea Costamagna is a researcher affiliated with the École Polytechnique Fédérale de Lausanne (EPFL), working within the School of Computer and Communication Sciences and the Department of Communication Systems. His research focuses on logic synthesis, digital circuit design, and the intersection of machine learning with hardware implementation. His work includes optimizing digital circuits using techniques like resynthesis, resubstitution, and decomposition, with applications in FPGA design and low-power systems. Recent publications explore symmetry-based synthesis, glitch-aware power minimization, and the use of resistive switching devices in machine learning hardware. His research also extends to quantum physics modeling with deep learning.

• Logic Synthesis
• Digital Circuit Design
• Machine Learning
• +۳ مورد دیگر

Weiwen Jiang is a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at George Mason University (GMU), affiliated with the College of Engineering and Computing (CEC). He leads the JQub lab, focusing on hardware/software co-design for computing systems, spanning classical (FPGAs, ASICs) and quantum computing applications in AI-driven fields like medical imaging and geophysics. Prior to GMU, he held a postdoctoral position at the University of Notre Dame and earned his PhD in Computer Science from Chongqing University with a joint PhD in Electrical and Computer Engineering from the University of Pittsburgh. His research emphasizes quantum computing, AI accelerators, and domain-specific computing. Notable achievements include the 2025 NSF CAREER Award, ACM Sigda Meritorious Service Award (2024), and IEEE QuantumWeek Best Paper Award (2023). His work is funded by NSF, DoE, ARO, Meta, and Leidos. He co-chaired IEEE QuantumWeek (2023–2025) and created workshops like StableQ at ESWEEK 2023. Key contributions include developing frameworks like QuPAD for quantum learning and JQub's AI-driven geophysical and medical imaging tools. His lab graduated Dr. Yi Sheng (now at University of South Florida) and Dr. Zhepeng Wang (Amazon Applied Scientist). Current research explores quantum machine learning, noise mitigation, and fairness in AI for edge devices.

• Quantum Computing
• AI Accelerators
• Hardware-Software Co-Design
• +۳ مورد دیگر

Professor Ahmet Bindal is a faculty member in the Department of Computer Engineering at San José State University . He earned his B.S. in Electrical Engineering from Bogazici University, Turkey, followed by M.S. and Ph.D. degrees from the University of California, Los Angeles. Industry Experience : 20 years at IBM, Intel, Philips, and Cadence Design Systems. Current Research : Nano-scale electron devices, silicon nanowire transistors, robotics, and VLSI architecture. Research Trends : His work focuses on silicon nanowire transistors for VLSI, FPGA, and robotics. Key themes include low-power/high-speed integrated circuits , dynamic logic design , neuromorphic engineering , and advanced semiconductor processing . Patents and Publications : He holds four U.S. patents (three with IBM, one with Intel). His 30+ journal and conference publications span nanowire transistors, FPGA architecture, robotics, and semiconductor process modeling. Teaching Contributions : Developed an undergraduate System-on-Chip (SoC) course and a MOSFET design laboratory at SJSU. Books Authored : Fundamentals of Computer Architecture and Design (Springer, 2017). Electronics for Embedded Systems (Springer, 2017). Silicon Nanowire Transistors (Springer, 2017).

• Nano-scale Electron Devices
• Silicon Nanowire Transistors
• VLSI Architecture
• +۴ مورد دیگر

Farshad Moradi is a Professor at the Department of Electrical and Computer Engineering at Aarhus University, specializing in neuromorphic engineering, spintronics, and biomedical device design. His work focuses on integrating advanced materials and circuits for applications in neural interfaces, energy-efficient computing, and wireless biomedical systems. Research Interests include: Spintronic-based neuromorphic computing architectures Ultra-low power analog/mixed-signal integrated circuits Ultrasonically powered implantable medical devices Neural signal processing and seizure detection systems Wireless energy transfer and structural health monitoring Key Projects (2016-2026): SPICE: Spintronic-Photonic Integrated Circuit Platform PHOTON-NeuroCom: Photonic-assisted Neuromorphic Computing Neuro-Sense: Flexible bioinspired neuroprostheses CorroSense: Self-powered corrosion monitoring HERMES: Hybrid Enhanced Regenerative Medicine Systems Recent innovations include: Ultrasonically powered optogenetic implants Low-power neural amplifiers for deep-brain interfaces Spin-torque nano-oscillator-based neuromorphic hardware Energy harvesting systems for structural monitoring

• Neuromorphic Computing
• Spintronics
• Biomedical Engineering
• +۵ مورد دیگر

Kia Bazargan is an Associate Professor and the Leroy and Ruth Fingerson Co-op Professor at the University of Minnesota, College of Science and Engineering. He currently serves as Director of the Co-op Program and focuses on VLSI-CAD, FPGA physical design, and hybrid binary-unary computing. University: University of Minnesota School: College of Science and Engineering Department: Electrical and Computer Engineering His research emphasizes stochastic computing and unary computing, where numbers are encoded as streams of bits. He explores techniques to reduce hardware costs while maintaining efficiency, particularly for edge computing and neural network applications. Recent publications highlight his work on hybrid binary-unary computing, FPGA-based inference acceleration, and lossless compression of lookup tables. Grants from Cisco Systems and the National Science Foundation support his projects. Scientific Awards: PFI-TT Grant (2020-2024): Commercializing hybrid computing for modern applications Uniqomp NSF Grant (2020-2021) EAGER Grant (2015): Studying complex dynamical systems His lab (4-162 EE/CSci) investigates scalable computing paradigms to bridge the gap between ASICs and FPGAs in performance and energy efficiency.

• VLSI-CAD
• FPGA Physical Design
• Reconfigurable Computing
• +۴ مورد دیگر

Prof. Dr.-Ing. Marc Reichenbach serves as the Chair of Integrated Systems at the Institute for Applied Microelectronics and Data Technology at the University of Rostock. His office is located at Albert-Einstein-Straße 26, 18059 Rostock, Room 102 (1st floor), with contact information including telephone (0381) 498 7270 and email marc.reichenbach@uni-rostock.de. Professor Reichenbach's research focuses on the intersection of hardware design and artificial intelligence, with particular expertise in memory technologies and computing architectures. His work spans several key areas: Development of specialized computer architectures for deep learning applications Advanced VLSI design and CPU architecture Emerging memory technologies, particularly RRAM (Resistive Random-Access Memory) FPGA-based acceleration systems Hardware implementations for neural networks and AI applications Analysis of Professor Reichenbach's recent publications (2023-2025) reveals a strong focus on memory computing technologies, particularly RRAM-based systems. His work demonstrates expertise across multiple dimensions of computer architecture including ASIC design, FPGA acceleration, and novel memory systems. The publications show a clear trajectory toward implementing AI and machine learning capabilities directly in hardware, with applications ranging from edge computing to satellite systems. A significant portion of his recent work addresses the challenges of implementing neural networks using emerging memory technologies, focusing on efficiency, reliability, and performance optimization. Professor Reichenbach teaches several advanced courses including: Computer architectures for deep learning applications Project seminar Embedded Systems Advanced VLSI Design (Advanced CPU Design) His research group appears to be actively engaged in several cutting-edge projects related to hardware acceleration for AI applications, memory computing, and embedded systems design. The group collaborates on projects involving digital twins for hardware systems, real-time operating systems for heterogeneous architectures, and specialized computing systems for various applications from medical devices to drone technology.

• Integrated Circuits
• Embedded Systems
• VLSI Design
• +۷ مورد دیگر

Jonathan Viventi is the Hawkins Family Associate Professor of Biomedical Engineering at Duke University, with additional appointments as Assistant Professor in Neurosurgery and Neurobiology, and as a Faculty Network Member of the Duke Institute for Brain Sciences. His research focuses on developing flexible, high-resolution neural interfaces for diagnosing and treating neurological disorders, particularly epilepsy, and advancing brain-machine interfaces. Education: Ph.D. in Engineering from the University of Pennsylvania (2010). Research Interests: Dr. Viventi's work centers on flexible electronics for high-resolution brain interfacing . Key areas include: Micro-electrocorticography (μECoG) arrays with thousands of channels Wireless, fully implantable neural prosthetics for speech restoration Real-time seizure detection and prediction systems Chronic biointegration of soft electronic materials Translational applications in epilepsy, stroke, and Parkinson's disease Scientific Awards: MIT Technology Review Innovators Under 35 (2014) Popular Science Brilliant 10 (2014) Grants & Funding: Dr. Viventi leads multiple NIH-funded projects including: A Wireless µECoG Prosthesis for Speech (2021-2026) Neuro-CROWN: Optimized Ultra-Flexible CMOS Electrode Arrays (2021-2025) Next-Generation Wireless Intracranial Arrays for Post-traumatic Epilepsy (2021-2025) Laboratory & Teams: His lab develops cutting-edge neural interface technologies, collaborating across engineering, neuroscience, and clinical departments at Duke to translate flexible electronics into therapeutic devices.

• Neural Engineering
• Brain-Computer Interfaces
• Flexible Electronics
• +۴ مورد دیگر

Glenn Gulak is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto's Faculty of Applied Science and Engineering. He holds the Canada Research Chair in Signal Processing Microsystems and the Edward S. Rogers Sr. Chair in Engineering. A Senior IEEE Member and Professional Engineer in Ontario, he received his Ph.D. from the University of Manitoba. His research spans: Digital Communication Systems: VLSI implementations of MIMO detectors, lattice reduction algorithms, and homomorphic encryption accelerators Lab-on-Chip Microsystems: CMOS biosensors for rapid pathogen detection and integrated fluorescence imaging Recent publications (2019-2025) demonstrate a dominant focus on privacy-enhancing technologies, with 73% concentrated in cryptographic hardware and homomorphic encryption. This reflects industry-aligned work on confidential computing and secure data processing. Awards & Honors: IEEE Millennium Medal (2001) Canada Research Chair in Signal Processing Systems (Tier 1, 2005-2012) Edward S. Rogers Sr. Chair (2005-2010) RBC Research Prize L. Lau Chair (1999-2004) Teaching Award (1999) He has supervised 44+ graduate students (PhD/MASc) with thesis topics spanning VLSI communication systems, CMOS biosensors, and cryptographic accelerators. Notable industry collaboration includes serving as CTO of a semiconductor startup (2001-2003). His lab develops hardware for quantum cryptography and secure medical computation.

• Homomorphic Encryption
• Quantum Cryptography
• CMOS Biosensors
• +۴ مورد دیگر

Daniele Guido Allegri is a Professor at the University of Applied Sciences and Arts of Southern Switzerland (SUPSI), affiliated with the Department of Innovative Technologies (DTI) and the Institute of Systems and Applied Electronics (ISEA). He became a professor in 2021 and serves as the director of ISEA since August 2023. His roles include leading the "Digital Electronics, Microelectronics, and Bioelectronics" scientific area since 2019. Allegri's research spans biomedical electronics, microelectronics, and embedded systems. Key projects include the development of radiation-hardened PLL ASICs (Cadagno, Quarnei), a Cardio Pulmonary Rescue Support System, and signal processing solutions for myopathy diagnosis and renal dialysis monitoring. He teaches courses on machine learning, analog/digital electronics, and embedded systems design. His publications focus on CMOS multifrequency impedance analyzers for biomedical applications (2018), real-time hydration monitoring via bioimpedance (2016-2017), and the European Solar Telescope (2021), which integrates advanced technologies for solar physics. These works reflect interdisciplinary expertise in circuit design, medical devices, and astrophysical instrumentation. Allegri's current affiliations include the Department of Innovative Technologies and ISEA at SUPSI. He has worked extensively on integrated circuits for biomedical applications, signal processing, and radiation-hardened electronics for space systems.

• Biomedical Engineering
• Microelectronics
• Embedded Systems
• +۵ مورد دیگر

Professor Earl T. Campbell is a Professor of Quantum Computation at the School of Mathematical and Physical Sciences, University of Sheffield, and serves as VP of Quantum Science at Riverlane. His research focuses on practical quantum technologies with capabilities beyond classical physics, particularly in fault-tolerant quantum computing. His educational background includes: Physics & Philosophy MSc (2001-2005, Bristol University) Quantum computing PhD (2005-2008, Oxford University) Professor Campbell's research centers on the central question 'What are the optimal blue-prints for large-scale, reliable quantum technologies?' His work spans architectures for fault-tolerant quantum computing, topological error correcting codes, magic states, gate synthesis, and Majorana fermions. His team designs protocols and software to operate future quantum computers reliably despite noise and decoherence, including development of error correction codes, magic state factories (which determine quantum computer processing speed), and algorithm compilation into machine-level commands. His recent publications demonstrate a strong focus on practical aspects of quantum error correction, with significant contributions to surface codes, homological product codes, and efficient decoding algorithms. His work bridges theoretical quantum information science with practical implementation challenges, aiming to reduce resource requirements for fault-tolerant quantum computing. His notable scientific achievements include: Royal Commission of Great Exhibition of 1851 fellowship (2008-2010) EPSRC early career Research Fellow (2015-present) Professor Campbell supervises PhD student Luke Heyfron and collaborates with postdoc Mark Howard. He has received significant grant funding including an EPSRC early career fellow project 'Towards fault-tolerant quantum computing with minimal resources' (EP/M024261/1, £675,867) and Royal Commission fellowship funding (~£100,000). He is an active member of the EPSRC Peer Review College and the Institute of Physics QQQ group Committee, and has organized the FTQT2016 workshop in Benasque, Spain.

• Architectures for fault-tolerant quantum computing
• Topological error correcting codes
• Magic states
• +۵ مورد دیگر

Subramanian Iyer is a Distinguished Professor at the University of California, Los Angeles (UCLA), holding the Charles P. Reames Endowed Chair in Electrical Engineering with joint appointments in Electrical and Computer Engineering and Materials Science and Engineering. His laboratory focuses on cutting-edge semiconductor research. Primary research domains include: System Scaling Technology : Innovations in semiconductor miniaturization 3D Integration & Advanced Packaging : Techniques for vertical chip stacking and heterogeneous integration Memory Subsystems : Development of embedded DRAM and novel memory architectures Neuromorphic Computing : Hardware implementations of brain-inspired computing Publication analysis reveals three dominant themes across 35+ years of research: Semiconductor materials innovation (SiGe alloys, silicides, MBE growth) Memory technology evolution (embedded DRAM, eFUSE, low-latency designs) System integration advancements (3D packaging, TSV, heterogeneous integration) Significant honors include: IEEE Fellow (1995) and Daniel Noble Award (2012) National Academy of Inventors Fellow (2017) IBM Fellow (2010) with 30+ invention plateaus IMAPS Educator Award (2021) and Daniel C. Hughes Memorial Award (2020) He leads UCLA's NanoLab facility and has been featured in The New York Times and Wall Street Journal for pioneering chiplet technology. Current work focuses on megachip architectures and open-access semiconductor prototyping.

• System Scaling Technology
• Advanced Packaging
• 3D Integration
• +۲ مورد دیگر

Prof. Dr. Andre Schöning is a Full Professor (W3) at the Physics Institute of Heidelberg University since 2009, specializing in experimental particle physics. He serves as Co-Spokesperson of the Mu3e Collaboration and leads research in detector development and high-energy physics experiments. Research Interests: Search for the decay μ→eee with the Mu3e Experiment at PSI Development of High-Voltage Monolithic Active Pixel Sensors (HV-MAPS) Track trigger systems for ATLAS and future colliders Physics analysis with ATLAS and historical H1 experiment data Wireless data transmission technologies for particle detectors His recent publications demonstrate strong focus on detector technology development, particularly for muon experiments and high-rate tracking systems, alongside significant contributions to Standard Model physics measurements at the LHC. The research spans both hardware development and sophisticated data analysis techniques. Scientific Recognition: CERN Fellowship (1997-1999) University of Hamburg dissertation award (1997) Association of the Friends and Sponsors of DESY dissertation award (1997) Prof. Schöning has secured substantial research funding from DFG and BMBF from 2009-2025, including leadership of the DFG Research Unit on Lepton Flavor Violation with Mu3e. He maintains active collaborations including WADAPT, Mu3e, ATLAS, and the long-standing H1 collaboration. His research group operates within the High-Energy Physics division of Heidelberg's Physics Institute, working on cutting-edge detector systems for current and future particle physics experiments, with particular emphasis on precision measurements requiring novel detector technologies.

• Particle Physics
• High-Energy Physics
• Detector Development
• +۵ مورد دیگر

Shinji Kimura is a Professor at Waseda University's Faculty of Science and Engineering, specializing in VLSI design and electronic systems. He holds a Doctor of Engineering from Kyoto University and has been with Waseda since 2002, previously serving as Associate Professor at Nara Institute of Science and Technology (1993–2002) and Assistant Professor at Kobe University (1985–1993). Kimura's research spans low-power circuit design , approximate computing , FPGA optimization , video coding (HEVC) , and hardware acceleration for AI . His work focuses on energy-efficient architectures for applications like neural networks, computer vision, and ultra-high-definition video processing. Recent publications emphasize hardware-efficient multipliers, neural network compression, and 3D-stacked memory systems. Awards include the LSI IP Design Award (2000, 1999) and the Information Processing Society of Japan Encouragement Award (1993). He leads projects on HEVC encoding/decoding, non-volatile memory optimization, and 3D integrated circuits, with VLSI implementations achieving real-time 8K video processing.

• Electronic Design Automation
• VLSI Design
• Computer Systems
• +۷ مورد دیگر