جستجوی استاد راهنمای دانشگاهی

Ahmedullah Aziz is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, within the Tickle College of Engineering. He earned his Ph.D. in Electrical and Computer Engineering from Purdue University (2019), an M.S. from Pennsylvania State University (2016), and a B.S. from Bangladesh University of Engineering & Technology (2013). His research focuses on mixed-signal VLSI circuits, non-volatile memory, and beyond-CMOS device design, emphasizing emerging technologies like ferroelectrics and spintronics. He leads the NorDIC Lab and has published over 60 articles in journals, conferences, and patents. Education: PhD, Electrical & Computer Engineering, Purdue University, 2019 MS, Electrical Engineering, Pennsylvania State University, 2016 BS, Electrical & Electronic Engineering, BUET, 2013 Research Interests: Aziz explores device-circuit-system co-design techniques, particularly in cryogenic neuromorphic systems, superconducting memory, and ferroelectric-based circuits. His work bridges material innovation with practical applications, aiming to advance energy-efficient and high-performance computing. Awards: EDAA Outstanding Dissertation Award (2019/2020) Outstanding Graduate Student Research Award (Purdue, 2019) Samsung 'Icon' Award (2013) Best Publication Awards (SRC-DARPA STARnet, 2015/2016) Advising & Grants: While specific grants are not detailed, his research has been supported by prestigious institutions. He has advised/co-advised projects in emerging technologies but no listed students. His work extends to reviewing IEEE journals, conference TPC roles, and editorial contributions. Labs & Teams: He directs the NorDIC Lab, focusing on next-generation computing and device innovation.

• Mixed-Signal VLSI Circuits
• Non-Volatile Memory
• Beyond CMOS Device Design
• +۴ مورد دیگر

Maurizio Zamboni is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he also serves as Student Ombudsman. His academic career spans over three decades with continuous teaching and research contributions in electronics and computing fields. Professor Zamboni's research interests focus on cutting-edge areas including CMOS integrated circuits, computer architecture, quantum computing, semiconductor devices, and VLSI design. His work particularly emphasizes emerging nanotechnologies for digital microelectronic architectures and the design of high-performance or low-consumption processing systems. He has developed expertise in circuit architectures for probabilistic computing, logic-in-memory computing, magnetic devices, and quantum architectures. His recent publications (2021-2025) reveal a strong trend toward quantum computing applications, in-memory processing architectures, and novel approaches to overcoming the memory wall problem. These works span both theoretical algorithm development and practical hardware implementations, with significant focus on quantum annealing, FPGA-based quantum emulation, and memory-mapped processing architectures. Professor Zamboni has been actively supervising PhD students working on quantum computing algorithms, hardware AI accelerators for automotive applications, and quantum-related optimization approaches. He leads research within the VLSILAB Group at DET, focusing on the intersection of nanoelectronics, quantum computing, and advanced computer architectures. His work bridges theoretical computer science with practical electronic design, creating novel solutions for next-generation computing challenges.

• CMOS integrated circuits
• Computer architecture
• Electrical and electronic engineering
• +۱۲ مورد دیگر

Marion K. Matters-Kammerer is a Full Professor of Electrical Engineering at Eindhoven University of Technology, leading research in terahertz (THz) and millimeter-wave systems. She holds positions in the Center for Wireless Technology, THz Electronics and Integration Lab, and RF Sensing & Communication Lab. Her expertise includes integrated circuits, antenna design, and power amplifier systems. She has led EU projects like 3DmicroTune and ULTRA, and co-authored over 70 journal/conference papers with 13 US patents. Education: MSc in Physics from École Normale Supérieure (Paris) and TU Berlin (1999), PhD in Physics from RWTH Aachen (2007). Past roles include Senior Scientist at Philips Research (1999–2011) and Guest Professor at RWTH Aachen (2009–2010). Research focuses on THz spectroscopy, mm-wave integrated circuits, and energy-efficient wireless systems. Key projects involve THz biosensing, 60 GHz sensor networks, and co-integration of photonics and electronics. Her work addresses UN SDGs like affordable and clean energy, and industry-academia collaboration via NXP Smart Mobility projects. Recent articles highlight advancements in mm-wave power amplifiers, waveguide integration, and radar signal processing. Grants include €2.5M for TeraIBs (2025–2028) and €1.8M for Future Wireless Interfaces (2024–2029). Labs include THz Electronics Lab and RF Sensing Team, advancing sensor and communication technologies.

• Terahertz Technology
• Millimeter-Wave Systems
• Integrated Circuits Design
• +۳ مورد دیگر

Mikael Östling is a Professor at KTH Royal Institute of Technology, holding a position in the Division of Electronics and Embedded Systems within the School of Information and Communication Technology. He earned his MSc (1980) and PhD (1983) in engineering physics from Uppsala University. Since 1984, he has been a faculty member at KTH, serving as Deputy President (2017–2022), Dean of the School of ICT (2004–2012), and Head of the Department of Microelectronics and Information Technology (2000–2004). He has held visiting roles at Stanford University and the University of Florida. His research focuses on silicon/silicon germanium devices, wide bandgap semiconductors (e.g., silicon carbide), and high-power/high-frequency applications. He has authored over 600 papers, 10+ book chapters, and a textbook. Key achievements include co-founding TranSiC (2005), securing the ERC Advanced Investigator Grant (2009), and serving as Editor-in-Chief of IEEE Journal of Electron Devices Society (2016–2019). He is an IEEE and ECS Fellow. Östling has supervised 50 PhD theses and contributed to innovations like high-temperature silicon carbide circuits and graphene-based sensors. His work spans academic leadership, industry collaboration, and global research advisory roles in EU frameworks and the European Research Council.

• Silicon Devices
• Wide Bandgap Semiconductors
• High-Frequency Electronics
• +۳ مورد دیگر

Marco Vacca is an Associate Professor in the Department of Electronics and Telecommunications (DET) at Politecnico di Torino and a member of the Interdepartmental Center PIC4SeR - PoliTO Interdepartmental Centre for Service Robotics. His work bridges electronics, nanotechnology, and computing architecture with a focus on innovative solutions to the memory wall problem. His research spans Logic-in-memory computing, Machine learning hardware acceleration, and Nanocomputing with specific emphasis on circuit architectures for probabilistic computing, magnetic devices, hybrid technologies integration, and CAD tools for emerging technologies. Dr. Vacca leads research in RISC-V extensions, hardware accelerators for AI, and autonomous robot systems for agricultural applications through the VLSILAB research group. Recent publications reveal a strong trend toward solving fundamental computing challenges through nanoscale innovations, particularly in memory-centric architectures, molecular field-coupled computing, and novel transistor technologies. His work demonstrates how logic-in-memory approaches can overcome traditional von Neumann limitations while improving energy efficiency for AI workloads. Editorial board member of ELECTRONICS (2021-2023) Program committee member for Design, Automation and Test in Europe Conference (DATE) 2020-2021 Dr. Vacca supervises PhD student Alessandro Varaldi working on 'Hardware AI Accelerators for Automotive Applications' and has led significant research projects including 'Device for Storage and Processing Data and Related Method' (2020-2021) and 'Quantum Computing and Quantum Communication: State of the Art and Applications in the Telco Sector' (2020). His grant portfolio shows strong industry and competitive funding support. As a core member of the VLSILAB research group, Dr. Vacca contributes to advancing VLSI theory and design applications with particular focus on implementing Big Data, Machine Learning, and Neural Networks in specialized hardware architectures that push the boundaries of conventional computing.

• Logic-in-memory
• Machine learning
• Nanocomputing
• +۷ مورد دیگر

Dr. Xin Yi is a Research Fellow at Heriot-Watt University's School of Engineering & Physical Sciences, affiliated with the Institute of Photonics and Quantum Sciences. He holds a PhD in Electronic and Electrical Engineering from the University of Sheffield (2015–2020) and joined Heriot-Watt in 2020 as a Research Associate. His research focuses on developing next-generation quantum detectors, particularly avalanche photodiodes and single-photon avalanche diodes (SPADs) for short-wave infrared (SWIR) applications. Funded by the EPSRC, his work emphasizes semiconductor materials like AlAsSb, III-V compounds, and Ge-on-Si heterostructures to enhance detector performance in quantum technologies. Research interests include impact ionization mechanisms, semiconductor characterization, and device fabrication. Key achievements include designing low-noise Ge-on-Si SPADs with record sensitivity and high-gain avalanche photodiodes for SWIR detection. Yi has received the EPSRC Quantum Technology Career Development Fellowship (2022) and contributed to over 20 peer-reviewed publications. He collaborates internationally and actively presents at conferences, showcasing advancements in quantum detectors and optoelectronic materials. His work bridges theoretical modeling and experimental validation, targeting applications in quantum communication, sensing, and imaging. Grants and fellowships support his exploration of novel semiconductor materials and fabrication techniques to push the boundaries of SWIR detection beyond traditional silicon limitations.

• Quantum Technology
• Photonics
• Semiconductor Materials
• +۳ مورد دیگر

Vijaykrishnan Narayanan is a Professor at the College of Engineering , Pennsylvania State University, with affiliations in both Computer Science & Engineering and Electrical Engineering departments. He co-directs the Microsystems Design Lab and leads the Architecture, Benchmarking, and Circuits Thrust at the DARPA/SRC LEAST Center. Education : Bachelors (1993) from University of Madras; Ph.D. (1998) from University of South Florida His research focuses on Power Aware Computing , Computer Architecture , Embedded Systems , and Emerging Device Integration . Recent work explores steep-slope devices for energy efficiency, nonvolatile processors for ambient energy harvesting, and neuromorphic architectures using hybrid VO₂-MOSFET oscillators. Key article trends span post-CMOS technologies (tunnel FETs, VO₂ devices), low-power design , and bio-inspired signal processing . Scientific Awards : IEEE Fellow, ACM Fellow, IEEE Transactions on VLSI Best Paper, IEEE Micro Best Paper Patents : Dynamically-configurable hardware architecture for audience analytics

• Power Aware Computing
• Computer Architecture
• Embedded Systems
• +۴ مورد دیگر

Eric R. Fossum is the John H. Krehbiel Sr. Professor for Emerging Technologies at the Thayer School of Engineering at Dartmouth College. He serves as Vice Provost for Entrepreneurship and Technology Transfer and Director of Dartmouth's PhD Innovation Program. As one of the world's leading experts in solid-state image sensors, he invented the CMOS active pixel sensor technology that revolutionized digital imaging in smartphones, medical devices, and automotive systems. His work has earned him numerous accolades, including the National Medal of Technology and Innovation (2025) and the Queen Elizabeth Prize (2017). His research interests focus on: Solid-state image sensors (CCDs, CMOS active pixel sensors, Quanta Image Sensors) Advanced imaging systems and on-chip processing New applications for image sensors in medicine, security, and space Dr. Fossum's recent publications demonstrate significant advancements in: Photon-counting sensors for low-light applications High-speed imaging for microscopy and radiography Backside-illuminated and sub-diffraction-limit pixel designs Quantum random number generation using sensor technology Infrared spectral extension of CMOS sensors His scientific awards include: National Medal of Technology and Innovation (2025) Queen Elizabeth Prize for Engineering (2017) IEEE Andrew S. Grove Award (2009) Induction into National Inventors Hall of Fame (2011) Emmy Award for Technology & Engineering (2021) Doctor of Science, Honoris Causa from Trinity College (2014) As an entrepreneurial leader, Dr. Fossum has: Co-founded Gigajot Technology with former PhD students Previously led Photobit and Siimpel Corporations Active participant in technology transfer initiatives at Dartmouth Founder and Past President of the International Image Sensor Society

• Solid-State Image Sensors
• CMOS Active Pixel Sensors
• Quanta Image Sensors
• +۴ مورد دیگر

Huamin Li is an Associate Professor in the Department of Electrical Engineering at the School of Engineering and Applied Sciences, University at Buffalo, specializing in nano-scale electronics and optoelectronics based on low-dimensional materials. His research bridges fundamental material science with practical device applications for next-generation computing and energy systems. Education: PhD in Nano Science and Nano Technology, Sungkyunkwan University (2013) MS in Mechanical Engineering, Sungkyunkwan University (2010) BS in Physics, Shandong Normal University (2007) Dr. Li's research focuses on 2D materials for transistor engineering , optoelectronic devices , and energy applications . His team pioneers atom-thin transistors operating at half the voltage of conventional semiconductors (as highlighted in IEEE IEDM 2020 coverage by major tech media), steep-slope devices for beyond-CMOS electronics, and nanohybrid systems for batteries and hydrogen evolution. Key innovations include metal-semiconductor interface engineering and ferroelectric gating in 2D transistors. His publication trends reveal three dominant trajectories: (1) fundamental 2D device physics with emphasis on charge transport anisotropy, (2) energy applications through nanohybrid catalysts and battery materials, and (3) neuromorphic computing via synaptic transistors. Recent work increasingly integrates machine learning for materials discovery. Scientific Awards: Chinese Government Award for outstanding self-financed students abroad (2012) Dr. Li leads the Emerging Nanoelectronics Research Group, which has filed five US and Korean patents with Samsung Electronics Co., Ltd. His team secures collaborative grants spanning semiconductor physics, energy storage, and neuromorphic systems. He actively mentors graduate students and collaborates with interdisciplinary groups in physics, chemistry, and material science. The Emerging Nanoelectronics Research Group maintains strong industry partnerships and focuses on translating fundamental 2D material discoveries into practical electronic and energy applications through its highly collaborative environment.

• Nano-scale electronics
• Optoelectronics
• Low-dimensional materials
• +۳ مورد دیگر

Nikhil Shukla is an Associate Professor at the University of Virginia with a joint appointment in Electrical and Computer Engineering and Materials Science and Engineering. His work bridges emerging hardware technologies with computational paradigms for energy-efficient systems. Education: Ph.D. in Electrical Engineering (University of Notre Dame, 2017), BS in Electronics and Telecommunications (University of Mumbai, 2010) His research focuses on emerging solid-state devices for non-Boolean computing, energy-efficient data storage , and integration of novel materials to redefine computing architectures. Key efforts include co-designing devices, circuits, and system-level solutions for Ising machines and dynamical systems solving combinatorial optimization problems. The 15 most recent articles highlight trends in oscillator-based Ising machines for optimization, ferroelectric and phase-transition materials, and hardware acceleration for NP-hard problems like Max-Cut and MaxSAT. Topics span from device physics (e.g., hafnium oxide endurance) to circuit-level implementations (FPGA accelerators, CMOS-compatible designs). Scientific Awards: IEEE TMSCS Best Paper Award (2017), STARnet LEAST Center Best Publication Awards (2015–2017), J.N. TATA and J.R.D TATA Scholarships (2011) Shukla's work at the Computing Hardware Research Lab emphasizes cross-disciplinary approaches, leveraging synchronized oscillators and correlated materials to push beyond CMOS-era limitations.

• Emerging Devices and Circuits
• Energy-Efficient Computing
• Ferroelectric Materials
• +۵ مورد دیگر

Christopher Ayala is a Professor at Yokohama National University's Institute of Advanced Sciences, where he directs research in the Quantum Information Research Center. His work focuses on energy-efficient superconductor computing architectures, particularly adiabatic quantum-flux-parametrons (AQFPs) for next-generation computing systems. Dr. Ayala's group develops superconducting processors, memory systems, and control architectures for quantum computing applications. Research areas include: Adiabatic superconductor microprocessors Fully homomorphic encryption hardware Quantum computing control systems Superconductor logic families Cryogenic computing architectures His team pioneered the world's first adiabatic superconductor microprocessor, recognized by IEEE Spectrum and Superconductor Week. Dr. Ayala received the Best Young Scientist Paper Award at the European Solid-state Device Research Conference for his work on nanoelectromechanical switches.

• Superconductor Electronics
• Adiabatic Computing
• Quantum Computing
• +۲ مورد دیگر

Supriyo Datta is the Thomas Duncan Distinguished Professor of Electrical and Computer Engineering at Purdue University, affiliated with the School of Electrical and Computer Engineering. His work bridges physics and computing, focusing on nanoscale devices and quantum phenomena. He pioneered spintronics and proposed spin transistors, foundational to modern spin-based electronics. His research on negative capacitance aims to extend Moore’s Law, while recent work explores probabilistic computing via p-bits, addressing complex problems at room temperature. Research Interests: Probabilistic Computing Spintronics and Quantum Transport Nanoelectronics and Device Simulation Unconventional Computing Architectures He authored seminal books like Quantum Transport: Atom to Transistor , which underpin semiconductor device modeling. His NEGF formalism is industry-standard for nanotransistor design. Datta’s contributions earned him NAE membership and global recognition in physics and engineering. Awards: Elected to the National Academy of Engineering (NAE) His group has advised over 50 PhD students, advancing fields from molecular electronics to autonomous probabilistic hardware. Current projects include p-bit-based Ising machines and spin-inspired quantum emulation systems.

• Spintronics
• Quantum Computing
• Probabilistic Computing
• +۳ مورد دیگر

Hugh Greatorex serves as a Researcher at the University of Groningen within the Faculty of Science and Engineering, affiliated with the Bio-inspired Circuits & Systems research group. His work centers on neuromorphic hardware design, specializing in spiking neural networks and event-based processing systems that prioritize energy efficiency and real-world applicability in robotics and embedded AI. His research spans critical areas in neuromorphic engineering: Neuromorphic Engineering Spiking Neural Networks CMOS Circuit Design Memristive Computing Event-based Vision and Audio Processing Symbolic Computation in Neural Hardware Greatorex integrates circuit design with neural algorithms to solve power efficiency challenges, frequently exploring beyond-CMOS technologies like memristors and multi-timescale neural dynamics for practical implementations. Analysis of his 14 recent publications (2022-2025) reveals a cohesive trajectory toward hybrid neuromorphic processors combining CMOS with emerging devices. Key contributions include the TEXEL and Fused-MemBrain architectures for beyond-CMOS integration, alongside advancements in event-based sensory processing and symbolic operations within spiking hardware. This work consistently bridges neural computation with symbolic AI paradigms while emphasizing scalability and robustness. No scientific awards were documented in available sources. Information regarding student advisement and research grants was not provided in the source materials. As a core member of Groningen's Bio-inspired Circuits & Systems group, Greatorex contributes to internationally collaborative projects focused on biologically inspired electronic systems for intelligent processing, with applications spanning edge AI and neural computation modeling.

• Neuromorphic Engineering
• Spiking Neural Networks
• CMOS Circuit Design
• +۳ مورد دیگر

Raul Zamorano is a research-active academic at Northumbria University , Newcastle, United Kingdom. His work is centered on the intersection of optical wireless communication , sensor networks , and machine learning applications in both healthcare and agriculture. He is a key contributor to interdisciplinary projects that integrate 5G technologies , visible light communication (VLC) , and AI-driven diagnostics . Education: Raul holds a BA degree, as listed in his qualifications on the Northumbria staff profile. Research Interests: Optical wireless communication systems Hybrid RF-optical sensor networks AI applications in smart agriculture and medical diagnostics 5G-enabled digital twins Energy harvesting for IoT devices His recent work demonstrates a strong focus on real-world applications , such as remote COVID-19 detection, crop stress monitoring, and underground mining safety systems. These projects highlight his ability to translate complex theoretical models into practical, scalable technologies. Scientific Contributions: While no formal awards are listed, his prolific publication record in top-tier journals and conferences reflects significant academic impact. His collaborative work spans multiple sectors, including telecommunications, healthcare, agriculture, and environmental monitoring. Collaboration & Labs: Raul is actively involved in cross-disciplinary research teams, often working with co-authors from institutions across Europe and beyond. His affiliations suggest participation in both university-led and externally funded research initiatives, though specific lab or grant details are not disclosed in the provided text.

• Optical Wireless Communication
• Sensor Networks
• Machine Learning
• +۵ مورد دیگر

Huang Boyuan serves as an Associate Professor and Doctoral Supervisor in the Department of Materials Science and Engineering at Southern University of Science and Technology (SUSTech). His research group operates within the Guangdong Provincial Key Laboratory of Information Functional Oxide Materials and Devices, utilizing advanced facilities including AFM, PLD, ALD, CVD, SHG, semiconductor analyzers, and cleanroom lithography equipment. Education: Ph.D. in Mechanical Engineering, University of Washington (2016-2020) B.S. in Physics, Nanjing University (2012-2016) Huang's research focuses on developing cutting-edge characterization techniques, particularly artificial intelligence atomic force microscopy (AI-AFM) and mechanically gated transistors (MGT). His work bridges materials science, nanotechnology, and artificial intelligence to investigate nanoscale multi-field coupling mechanisms in semiconductor materials. The research group actively explores two-dimensional thin film materials, experimental mechanics, and energy material interfaces, with particular emphasis on data-driven approaches to material characterization. Huang's publication portfolio demonstrates consistent high-impact output across materials science and nanotechnology domains, with increasing emphasis on AI-integrated characterization methods. His recent work shows strong interdisciplinary connections between materials physics, machine learning, and semiconductor device engineering, reflecting the growing importance of data science in advanced material characterization. Scientific Recognition: R&D 100 Awards Finalist (2020) Shenzhen Natural Science Award (2021) Shenzhen Overseas High-level Talent (2020) National Excellent Self-financed Overseas Student Scholarship (2020) Featured in MIT Technology Review Huang has successfully secured funding for eight research projects, including the NSFC Original Exploration Plan project and Major Research Plan Integration Project. His research group actively mentors graduate students and postdoctoral fellows, with several students receiving prestigious awards and scholarships. The team maintains strong industry connections, with two authorized patents achieving technology transfer. The research group operates within state-of-the-art facilities at SUSTech, maintaining collaborative relationships with national research initiatives including the National Major Scientific Research Instrument Development Projects. Current recruitment efforts focus on doctoral candidates and research assistants specializing in two-dimensional thin film materials, experimental mechanics, and energy material interface studies.

• Semiconductor thin film materials and devices
• Material nano-characterization
• Electromechanical coupling characterization
• +۳ مورد دیگر