جست‌وجوی استاد و پژوهشگر

Giacomo Indiveriمشاهده پروفایل

استاد

• Neuroscience
• Computer Science
• Machine Learning
• +۶ مورد دیگر

Giacomo Indiveri is a dual Professor at the Faculty of Science of the University of Zurich and the Department of Information Technology and Electrical Engineering of ETH Zurich . He serves as the Director of the Institute of Neuroinformatics at both institutions. Indiveri holds an M.Sc. in Electrical Engineering (1992) from the University of Genoa and a Ph.D. in Computer Science (2004) from the same university. Primary Affiliation: University of Zurich (Faculty of Science, Institute of Neuroinformatics) Secondary Affiliation: ETH Zurich (Department of Information Technology and Electrical Engineering) Indiveri's research bridges neuroscience , computer science , and machine learning to develop neuromorphic cognitive systems . His work focuses on spike-based learning , recurrent neural networks , and analog/digital circuit design for real-time sensory-motor systems . He integrates emerging memory technologies into fault-tolerant event-based architectures, enabling brain-inspired computing paradigms in applications like robotics and medical monitoring. His recent publications emphasize neuromorphic hardware for epileptic seizure detection , spiking neural networks in robotic painting , and scalable processors with on-chip learning . These works explore biologically plausible neurons , delay lines , and memory arrays for temporal processing, with applications in healthcare , edge computing , and adaptive control . Scientific Awards & Recognitions: 2021 IEEE Biomedical Circuits and Systems Best Paper Award Senior Member of IEEE Society ERC Fellow with three European Research Council grants Indiveri's group at the Institute of Neuroinformatics develops event-based systems for real-world validation of brain-inspired computing. His work includes multi-core processors , feedback optimizers , and dynamic routing architectures , supported by grants for advancing neuromorphic technologies .

• Reconfigurable Computing
• FPGA Architectures
• Computer Security
• +۶ مورد دیگر

André DeHon is the Oliver C. Boileau Jr. and Nan Eleze Boileau Professor of Electrical Engineering at the University of Pennsylvania, affiliated with Electrical and Systems Engineering (ESE) and Computer and Information Science (CIS). He chairs the Computer Engineering (CMPE) program and directs the CyberSavvy Security Center. His research focuses on reconfigurable computing, FPGA architectures, computer security, and energy-efficient hardware design. He holds a Ph.D. and M.S. from MIT and a B.S. from MIT's Lincoln School. Research interests include reconfigurable computing, FPGA interconnect, hardware security, and fault-tolerant systems. Notable achievements include the SEVER & PROTECT DARPA award and IEEE/ACM Fellowships. Recent work addresses fast FPGA compilation (HiPR, PLD), security through compartmentalization (μSCOPE, SCALPEL), and partial reconfiguration techniques. Teaching includes courses on hardware security, system-on-chip architecture, and digital audio basics. Over 200 publications span FPGA design, network-on-chip optimization, and molecular-scale computing. His labs (Implementation of Computation Group) explore physical implementation of computations through hardware-software co-design.

Dmitri Strukovمشاهده پروفایل

استاد

• Solid-State Nanoionics
• Emerging Electronics Devices and Circuits
• Non-Volatile Memories
• +۵ مورد دیگر

Dmitri Strukov is a Professor at the University of California, Santa Barbara in the Department of Electrical and Computer Engineering. His work spans material science, electrical engineering, and computer science, focusing on novel computing paradigms using emerging memory devices. Education: PhD in Electrical and Computer Engineering from SUNY Stony Brook, MS in Applied Physics and Mathematics from Moscow Institute of Physics and Technology. Research Interests include neuromorphic computing , non-volatile memory applications , and mixed-signal circuits for machine learning and hardware security. His group develops memristive crossbar arrays and 3D NAND flash for energy-efficient systems. Scientific Leadership features Fellow of IEEE and Distinguished Lecturer roles. His work has been recognized with best paper awards at ASPLOS’19 and Computing Frontiers’13. Students: Mentored PhD graduates in neurocomputing, security, and memristor design including Z. Fahimi, S. Larimian, M.R. Mahmoodi, and X. Guo. Grants: Funded by AFOSR, ARO, DARPA, NSF, and industry leaders like Google and Samsung. Labs: Utilizes UCSB’s nanofabrication center and advanced tools for memristor characterization.

Di Zhuمشاهده پروفایل

استاد

• Integrated Quantum Photonics
• Superconducting Detectors
• Nonlinear Optics
• +۳ مورد دیگر

Di Zhu is a Presidential Young Professor in the Department of Materials Science and Engineering at the National University of Singapore (NUS). He holds a B.Eng. from Nanyang Technological University and M.Sc./Ph.D. from MIT, both in Electrical Engineering. His postdoctoral research at Harvard focused on lithium niobate integrated photonics and superconducting detectors. He previously worked as a research scientist and PI at A*STAR's Institute of Materials Research and Engineering (IMRE). Research Interests : Integrated quantum photonics, superconducting detectors, nonlinear optics, and nanofabrication. His group develops scalable quantum photonic devices using lithium niobate and superconducting materials, emphasizing applications in quantum computing, communication, and sensing. Awards : National Research Foundation (NRF) Fellowship Harvard Quantum Initiative (HQI) Postdoctoral Fellowship MIT Jin-Au Kong Thesis Award Advising & Recruitment : Actively recruiting postdocs, PhD students, and interns in areas like integrated photonics, quantum optics, and superconducting detectors. Positions include work on thin-film lithium niobate, quantum simulation, and microwave-optical transduction. Group website: dizhulab.org .

Naresh R. Shanbhagمشاهده پروفایل

استاد

• Energy-efficient computing
• Machine learning hardware
• In-memory computing
• +۷ مورد دیگر

Naresh R. Shanbhag is the Jack Kilby Professor in the Department of Electrical and Computer Engineering and the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. He serves as Director of the Systems on Nanoscale Information fabriCs (SONIC) Center and held the D.J. Gandhi Distinguished Visiting Professorship at IIT Mumbai from 2015-2020. Previously, he was a visiting faculty member at National Taiwan University (2007) and Stanford University (2014). Dr. Shanbhag received his doctorate from the University of Minnesota (1993) in Electrical Engineering. From 1993 to 1995, he worked at AT&T Bell Laboratories as the lead chip architect for AT&T's 51.84 Mb/s transceiver chips over twisted-pair wiring for Asynchronous Transfer Mode (ATM)-LAN and very high-speed digital subscriber line (VDSL) chip-sets. His research focuses on the design of energy-efficient machine learning, communications, and signal processing systems on resource-constrained embedded platforms. He explores fundamental trade-offs between energy efficiency, latency and accuracy of decision-making systems implemented in nanoscale technologies, with applications to computer vision, biomedicine, automatic target recognition, and imaging. His work spans four primary focus areas: Resource-efficient Machine Learning for the Edge, In-memory Computing (IMC), Energy-efficient High Data Rate Communications, and Shannon-inspired Statistical Error Compensation (SEC). Analysis of his recent publications reveals a strong emphasis on in-memory computing architectures (SRAM, MRAM, RRAM) for machine learning acceleration. His work consistently addresses energy-accuracy trade-offs, with increasing attention to security aspects of hardware implementations and applications to MIMO signal processing and edge AI systems. His research demonstrates a progression from theoretical foundations to practical silicon implementations. 2024 Semiconductor Research Corporation Innovation Award 2018 Semiconductor Industry Association/Semiconductor Research Corporation University Researcher Award 2018 IEEE International Symposium on Circuits and Systems Best Paper Award 2006 IEEE Fellow 1996 National Science Foundation CAREER Award Professor Shanbhag has mentored over 50 graduate students who now work at leading technology companies including Qualcomm, Amazon, Nvidia, Intel, and Apple. His research has been generously supported by the National Science Foundation, DARPA, AFRL, Semiconductor Research Corporation, Texas Instruments, Sandia National Laboratories, and industry partners including IBM, GlobalFoundries, and Intel Corporation. He led the Alternative Computational Models research theme (2006-2012) and was the founding Director of the SONIC Center (2013-2017), a 5-year multi-university center funded by DARPA and SRC. Currently, he leads research themes in the SRC and DARPA funded JUMP 2.0 Program's Center for Co-Design of Cognitive Systems and the Center for Ubiquitous Connectivity, and in the NSF IUCRC Center for Advanced Semiconductor Chips with Accelerated Performance (ASAP). As Director of the Systems on Nanoscale Information fabriCs (SONIC) Center, Professor Shanbhag leads a multidisciplinary team exploring novel computing paradigms for the nanoscale era. His group has benchmarked an extensive collection of in-memory computing and digital accelerator IC designs, maintaining a publicly available IMC benchmarking repository of metrics extracted from published IC prototypes. His research philosophy integrates concepts from information theory, statistical signal processing, detection and estimation, VLSI architectures, and digital and analog integrated circuits to develop energy-efficient systems from algorithms to silicon implementations.

Ranjan Singhمشاهده پروفایل

استاد

• Terahertz (THz) Photonics
• Metamaterials
• 6G Communications
• +۶ مورد دیگر

Ranjan Singh is a Professor at the Division of Physics, Nanyang Technological University (NTU) Singapore, specializing in terahertz photonics and metamaterials. He holds an elected fellowship from OPTICA (OSA) for pioneering work in ultrafast terahertz photonics, active metamaterials, and sensors. His research focuses on hybrid THz-electronic-photonic technologies for 6G communications, topological photonics, spintronics, quantum materials, and high-Tc superconductors. Education: B.Eng. in Telecommunications (Bangalore University, 2001); M.Tech in Photonics (Cochin University, 2004); Ph.D. in Photonics (Oklahoma State University, 2009). Postdoctoral research at Los Alamos National Laboratory (2009–2013). Research emphasizes on-chip THz topological photonics for next-gen communication systems, with notable achievements including a $7M grant for TERACOMM (on-chip THz topological photonics). His work integrates AI-driven beamforming, reconfigurable metasurfaces, and phase-change materials for adaptive THz systems. Key awards include the 2020 Web of Science 'Top 1% Highly Cited Researcher' distinction. His lab, TeraX Labs (founded 2013), develops cutting-edge technologies like THz brain-computer interfaces, quantum emitters, and spintronic sensors. Over $12M in competitive grants has fueled innovations in THz integrated circuits, tunable optical coatings, and ultra-sensitive biosensors. Advancing 6G/XG wireless, Singh's team designs topological beamformers, intelligent reflecting surfaces (IRS), and terahertz metamaterials for multi-link systems. His work bridges theoretical physics and applied engineering, with a focus on energy-efficient, reconfigurable photonic systems.

Burak Ozdoganlarمشاهده پروفایل

استاد

• Manufacturing Processes
• Biomedical Engineering
• Materials Science
• +۷ مورد دیگر

Burak Ozdoganlar is a Ver Planck Endowed Chair Professor of Mechanical Engineering at Carnegie Mellon University (CMU) and Associate Director of the Engineering Research Accelerator. He holds courtesy faculty positions in Biomedical Engineering and Materials Science and Engineering. Ozdoganlar earned his Ph.D. in Mechanical Engineering from the University of Michigan (1999), M.S. degrees from Ohio State University (1993, 1995), and a B.S. in Aeronautical Engineering from Istanbul Technical University (1991). Ph.D., Mechanical Engineering, University of Michigan (1999) MS, Mechanical Engineering, Ohio State University (1995) MS, Aeronautical and Astronautical Engineering, Ohio State University (1993) BS, Aeronautical Engineering, Istanbul Technical University (1991) Ozdoganlar’s research focuses on multi-scale manufacturing processes (macro/micro/nano), precision engineering , structural dynamics , and modal testing , with applications in biomedical device fabrication , microneedle arrays , soft electronics , and 3D ice printing for vascular networks. His work bridges computational modeling with experimental validation. Recent scientific awards include the 2023 AIMBE College of Fellows induction, ASME Fellow (2019), and NSF CAREER Award (2006). He served as interim CTO of the Advanced Robotics for Manufacturing (ARM) Institute and chaired the ASME-MED Manufacturing Equipment Technical Committee. Ozdoganlar leads projects in scalable manufacturing for implantable medical devices , bioelectric medicine , and wearable robotics . His lab develops 3D ice-printed vascular templates for tissue engineering and liquid metal circuits for soft electronics, funded by institutions like the Manufacturing Futures Institute and ARPA-H.

Aydin Babakhaniمشاهده پروفایل

استاد

• Terahertz (THz) Technology
• Wireless Sensors
• Medical Implants
• +۵ مورد دیگر

Aydin Babakhani is a Professor in the Department of Electrical and Computer Engineering at the University of California, Los Angeles (UCLA), affiliated with the College of Life Sciences. He directs the Integrated Sensors Laboratory (ISL), which focuses on the design and implementation of integrated sensors and systems. His research spans high-speed wireless communication, terahertz technology, medical implants, radar systems, and industrial monitoring solutions. Research Interests: Prof. Babakhani's work integrates silicon-based technologies with applications across multiple domains. Key areas include: Silicon mm-Wave/THz transceivers and on-chip antennas for communication and sensing Wirelessly powered medical implants for biopotential monitoring and neural stimulation THz radar systems for micrometer-resolution imaging and vibration detection Energy harvesting solutions for batteryless sensors in industrial and biomedical applications CMOS-based optoelectronic systems and photonic computing accelerators His recent publications (2021-2025) demonstrate a strong emphasis on terahertz systems, wireless power transfer, and miniaturized medical electronics. Over 80% of his latest articles involve silicon-integrated solutions for biomedical implants or THz sensing, with emerging focus on AI-accelerated photonic computing and multi-Gbps wireless links.

Andre DeHonمشاهده پروفایل

استاد

• Reconfigurable Computing
• FPGA Architecture
• Interconnect Design
• +۶ مورد دیگر

André DeHon is the Oliver C. Boileau Jr. and Nan Eleze Boileau Professor of Electrical Engineering at the University of Pennsylvania, with affiliations in the Electrical and Systems Engineering (ESE) and Computer and Information Science (CIS) departments. He founded the Penn Computer Engineering (CMPE) program and directs the DARPA-sponsored CyberSavvy Security Center. His research spans reconfigurable computing, FPGA architecture, interconnect design, hardware security, and energy efficiency, with a focus on adapting to fabrication imperfections and runtime variability. His work explores programmable substrates (e.g., CMOS VLSI, molecular electronics) and algorithmic mappings to create resilient, efficient systems. Current projects include runtime feedback mechanisms (REFINE), partial reconfiguration (ExHiPR), and security frameworks like SCALPEL and μSCOPE. Recent publications highlight advancements in FPGA compilation (PLD, HiPR), security (SCALPEL, μSCOPE), and interconnect optimization (Asymmetry in NoC). These studies intersect computer architecture, security, and embedded systems. Scientific awards and recognitions: 2023 IEEE Fellow 2020 IEEE Mary Kenneth Keller Teaching Award 2018 ACM Fellow TCFPGA Hall of Fame (2019) Best Paper at ICFPT 2015 Academic leadership: He chairs the ACM/SIGDA Technical Committee on FPGAs and Reconfigurable Computing, previously held faculty roles at Caltech (1999–2006), and was a postdoc at UC Berkeley (1996–1999). Education includes MIT SB (1990), SM (1993), and PhD (1996) in Electrical Engineering and Computer Science.

Zhonghai Luمشاهده پروفایل

استاد

• Computer Architecture
• Embedded Systems
• Network-on-Chip (NoC)
• +۷ مورد دیگر

Zhonghai Lu is a Professor of Electronic Systems Design (specializing in Dependable and Autonomous Systems) at KTH Royal Institute of Technology, part of the Department of Electrical Engineering in the School of Electrical Engineering and Computer Science (EECS). He serves as Program Director for KTH's Embedded Systems master's program and Director of Studies at the Division of Electronics and Embedded Systems. His research focuses on Network-on-Chip (NoC), computer architecture, embedded systems, and Prognostics and Health Management (PHM) of power electronics. He leads a research group exploring in-network processing and embedded intelligence, transforming passive networks into active computational frameworks. Lu holds a BSc from Beijing Normal University (1989), MSc and PhD from KTH (2002, 2007), and an MBA in Innovation and Growth from the University of Turku (2012). He has authored over 240 scientific papers, including journal articles and peer-reviewed conferences, with notable recognitions such as Best Paper Awards at NOCS’2015 and EU HiPEAC, and a Featured Paper in IEEE Transactions on Computers (2020). He serves as Associate Editor for ACM Transactions on Architecture and Code Optimization (TACO) and has chaired major conferences like HiPEAC’2017 and NOCS’2018. His research group’s recent work includes integrating AI into hardware acceleration, fault-tolerant neural networks, and RUL estimation for power electronics using recurrent neural networks. Lu has secured grants from the Swedish Research Council and Intel Corporation and developed courses like IL2230 (Hardware Architectures for Deep Learning) and IL2233 (Embedded Intelligence), pioneering embedded AI education at KTH. Education: BSc (Beijing Normal University), MSc/PhD (KTH), MBA (University of Turku) Awards: Best Paper Awards (NOCS, EU HiPEAC), Swedish Research Council Grants, Intel Research Gifts Labs/Teams: Research Group on In-Network Processing and Embedded Intelligence

Hiren Patelمشاهده پروفایل

استاد

• Real-Time Embedded Systems
• Computer Architecture
• Hardware for Machine Learning/AI
• +۹ مورد دیگر

Dr. Hiren Patel is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. He holds a Doctorate in Computer Engineering from Virginia Tech and previously worked as a postdoctoral fellow at UC Berkeley under Edward A. Lee. His research focuses on real-time embedded systems, computer architecture, machine learning hardware, and cybersecurity. He teaches courses like ECE 150 (Programming), ECE 320/429 (Computer Architecture), and ECE 327 (Digital Systems). Research Interests: Cyber-physical systems and hybrid architectures Hardware/software co-design methodologies Predictable cache coherence protocols IoT and edge computing systems Security in embedded and real-time systems Recent work emphasizes cache coherence solutions for safety-critical systems and GPU acceleration strategies. His publications address challenges in multicore predictability, FPGA bandwidth optimization, and autonomous robotics orchestration. No specific awards are listed, though his extensive publication record indicates significant contributions to embedded systems research. He currently oversees graduate student applications focusing on his core research areas.

Anantha Chandrakasanمشاهده پروفایل

استاد

• Energy-Efficient Circuits
• Integrated Systems
• AI Hardware Security
• +۳ مورد دیگر

Anantha Chandrakasan is the Vannevar Bush Professor of Electrical Engineering and Computer Science at MIT, serving as Dean of the MIT School of Engineering and Chief Innovation and Strategy Officer. His research focuses on energy-efficient integrated circuits, medical devices, and AI hardware security. He leads the MIT Energy-Efficient Circuits and Systems Group, developing systems for biomedical applications, wireless communication, and quantum computing. He holds appointments at MIT's Microsystems Technology Laboratories and has contributed to collaborations like the MIT-Takeda Program in AI-driven healthcare and a partnership with GlobalFoundries for energy-efficient AI chips. His work spans implantable drug delivery systems, conformable ultrasound patches, and secure edge computing architectures. Chandrakasan's innovations include ultra-low-power circuits for IoT devices, cryptographic processors for post-quantum security, and AI accelerators for edge applications. He emphasizes interdisciplinary research bridging electrical engineering with biomedical and quantum fields, supported by leadership roles in MIT's strategic initiatives. His contributions to energy-efficient computing have led to advancements in wearable health monitors, batteryless sensors, and secure communication protocols for medical devices. Ongoing projects include THz integrated systems and AI-enhanced analog circuit design optimization.

• Advanced Electronics Cooling
• Phase-Change Transport Phenomena
• Additive Manufacturing
• +۷ مورد دیگر

Justin A. Weibel is a Professor of Mechanical Engineering at Purdue University, affiliated with the School of Mechanical Engineering. He directs the Cooling Technologies Research Center (CTRC), a National Science Foundation Industry/University Cooperative Research Center. His research focuses on advanced electronics cooling, phase-change transport, additive manufacturing for thermal components, and machine-learning-driven design optimization. He has led projects funded by DARPA, ONR, ARPA-E, and industry partners, advancing cooling solutions for high-power electronics and energy systems. Research interests span thermal management, heat transfer, micro/nano-scale engineering, and sustainable energy. Key contributions include topology optimization for heat sinks, two-phase flow modeling, and embedded cooling systems for electric motors. His work integrates computational methods with experimental validation. Grants & Programs: DARPA TGP/ICECool, ONR NEPTUNE, ARPA-E ASCEND/COOLERCHIPS, SRC CHIRP Labs: Cooling Technologies Research Center (CTRC) Future Work: Expanding additive manufacturing applications, improving thermal efficiency in electrified transport, and advancing AI-driven thermal system design. Awards: Fellow of ASME (2023) Outstanding Faculty Mentor (2022) Multiple best paper awards from IEEE ITherm, ASME, and SEMI-THERM conferences

Stefan Maierمشاهده پروفایل

استاد

• Nanophotonics
• Plasmonics
• Metasurfaces
• +۵ مورد دیگر

Professor Stefan Maier holds the position of Head of School in Physics and Astronomy at Monash University. Previously, he served as the Lee Lucas Chair in Experimental Physics at Imperial College London (2007–2018) and built a new chair at Ludwig-Maximilians-Universität München (2019–2022). His research focuses on nanophotonics, plasmonics, and metasurface engineering, with emphasis on optical trapping, nonlinear optics, and novel photonic devices. Education: Bachelor’s degree in Physics, Technical University of Munich M.Sc. and Ph.D. in Applied Physics, California Institute of Technology (Caltech) Research Interests: Development of metamaterials and metasurfaces for light manipulation Applications of nanophotonics in sensing, imaging, and quantum technologies Optical trapping and plasmonic catalysis Nonlinear optical phenomena in nanostructured materials Articles Trends: Recent work emphasizes bound states in the continuum (BICs), 3D nanoprinted optical platforms, and active metasurfaces with tunable properties. Key themes include hybrid nanophotonics, ultra-high-Q resonators, and plasmonic nanomaterials for energy applications. Awards: ISI Highly Cited Researcher (2017–present) Grants/Projects: Chief Investigator in the All-on-chip twisted light modulator project (2022–2025) Leadership in Monash’s nanophotonics research team Labs/Teams: Directs a multidisciplinary lab at Monash focused on integrating 3D nanofabrication with optical physics, including collaborations in metafiber development and plasmonic biosensing.

José F. Martínezمشاهده پروفایل

استاد

• Computer Architecture
• Microprocessor Design
• Multiprocessor and Multicore Architectures
• +۵ مورد دیگر

José F. Martínez holds the Lee Teng-hui Professorship of Engineering at Cornell University's College of Engineering, where he leads research in computer architecture and systems. His roles include Vice Chair of ACM SIGARCH, IEEE Fellow, and past leadership roles in ISCA, MICRO, and IEEE Computer Society journals. He has received prestigious awards such as the NSF CAREER Award, IBM/Qualcomm Faculty Awards, and multiple teaching accolades including Tau Beta Pi Professor of the Year (2011). Education: Licenciado en Informática de Sistemas (1996), Universidad Politécnica de Valencia M.S. (1999) and Ph.D. (2002) in Computer Science, University of Illinois at Urbana-Champaign His research focuses on computer architecture , including microprocessors, multiprocessors, memory subsystems, embedded systems, and processing-in-memory (PIM) innovations. He co-leads the DARPA/SRC ACE Center for Evolvable Computing and NSF's CROPPS Center, and previously co-founded Cornell's Institute for Digital Agriculture (CIDA). His work bridges hardware-software co-design and sustainable computing. Key Contributions: Advancing energy-efficient multiprocessor architectures Developing PIM frameworks like PUMICE and Membrane Market-based resource allocation systems (e.g., XChange, ReBudget) His advising spans over 15 graduate students and has guided Merrill Presidential Scholars. Current research explores evolvable computing paradigms and AI hardware acceleration, reflecting his dual focus on foundational architecture and applied systems innovation.