جستجوی استاد راهنمای دانشگاهی

• Semiconductor Physics
• Gallium Nitride (GaN) Electronics
• Two-Dimensional Materials
• +۶ مورد دیگر

Tomas Palacios is a Professor of Electrical Engineering at the Massachusetts Institute of Technology (MIT) , where he directs the Center for Graphene Devices and 2D Systems and leads the Microsystems Technology Laboratories (MTL). His research focuses on pushing the boundaries of microelectronics through novel semiconductor materials and device architectures, including Gallium Nitride (GaN) and 2D materials like graphene and molybdenum disulfide (MoS2). Professor, MIT Electrical Engineering and Computer Science Director, MIT Center for Graphene Devices and 2D Systems Clarence J. LeBel Professor, MIT Faculty Director, Northeast Microelectronics Internship Program (NMIP) Research Interests span multiple cutting-edge domains: High-frequency electronics (>300 GHz) for 6G and quantum applications High-voltage power devices (600V–10kV) for energy conversion Post-silicon logic devices using 2D materials High-temperature electronics (e.g., Venus rover applications) Distributed neural networks on large-area 2D materials Graphene-based biosensors and chemical detection systems Scientific Contributions include: Double recipient of the IEEE George Smith Award for groundbreaking GaN transistor work Co-invented first MoS2 electronic circuits Developed world’s first Wi-Fi-to-electricity conversion antenna Led MIT’s Microsystems Technology Laboratories since 2021 Advising Philosophy emphasizes cross-layer expertise, with students gaining experience from materials synthesis to system-level prototyping. His lab has incubated startups like Vertical Horizons , focused on GaN power devices for AI and EVs.

• High-speed data converters
• Wireless transceivers
• Digital phase-locked loops
• +۷ مورد دیگر

Shiyu Su is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on high-speed data converters, wireless transceivers, digital phase-locked loops (PLL), and AI-assisted analog/mixed-signal design automation. He holds a Ph.D. from the University of Southern California (2019) and teaches courses such as ECE 340 (Electronic Circuits 2) and ECE 432 (Radio Frequency Integrated Devices and Circuits). Education: B.S. from Beijing University of Post and Telecommunication (China) and Queen Mary, University of London (UK), 2011; M.S. and Ph.D. from USC, 2013 and 2019, all in electrical engineering. Research Interests: High-speed ADCs/DACs RF/mm-wave transceivers Time-approximation filters (TAF) Analog/mixed-signal design automation Memristor-based computing Biomedical interfaces Key Awards: IEEE SSCS Predoctoral Achievement Award (2017–2018) Best Student Paper Award at IEEE RFIC (2022) Ming Hsieh Institute Scholar (2019–2020) Lab Focus: The Shiyu Su Lab develops integrated circuits for communications, sensing, and computing, with a focus on AI-driven methodologies and digital-analog co-design. Collaborations include work with Prof. Wei Wu (USC) on memristor-based systems.

Morteza Fayaziمشاهده پروفایل

استادیار

• Electronic Design Automation (EDA)
• Machine Learning (ML) in Analog Circuit Design
• System-on-Chip (SoC) Design Automation
• +۳ مورد دیگر

Morteza Fayazi is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Utah, with an adjunct position in the Kahlert School of Computing. His research focuses on Electronic Design Automation (EDA), applying machine learning to automate analog and mixed-signal circuit design, and developing high-performance computing systems. He holds a B.Sc. from Sharif University of Technology, and M.S.E./Ph.D. degrees from the University of Michigan. His research interests include AI-driven EDA, RF/circuit automation, and energy-efficient processors. Key achievements include the MEDAL lab’s work on terahertz radars, systolic-array processors (e.g., DAP and Versa), and open-source frameworks like FASCINET and Tablext. He has received awards such as the 2024 College of Engineering Dean’s ETR Fund and the 2017 Outstanding Undergraduate Thesis Award. Teaching responsibilities include multiple iterations of the Digital System Design course (ECE/CS 3700). His work spans over 15 peer-reviewed articles in IEEE Transactions, ACM, and top conferences like ICCAD and VLSI-SOC, emphasizing automation, efficiency, and AI integration in hardware design.

Bharat Bhuvaمشاهده پروفایل

استاد

• Computer-Aided Design
• Radiation Effects on Electronics
• Semiconductor Device Modeling
• +۳ مورد دیگر

Professor Bharat Bhuva is a faculty member in the School of Engineering at Vanderbilt University, holding the position of Professor of Electrical Engineering and Computer Engineering . His research focuses on radiation effects on integrated circuits, semiconductor device modeling, and VLSI design, with an emphasis on advancing the resilience of nanoscale electronics against single-event effects and total-ionizing-dose damage. He also investigates emerging technologies like FinFET and FDSOI for improved radiation hardness and performance. Education: Ph.D. in Electrical Engineering, North Carolina State University M.S. in Electrical Engineering, North Carolina State University B.S. in Electrical Engineering, Maharaja Sayajirao University Research Interests: Professor Bhuva’s work spans computer-aided design tools, semiconductor process modeling, and the mitigation of radiation-induced failures in advanced integrated circuits. His studies address challenges posed by scaling to smaller technology nodes (e.g., 3-nm FinFET) and the impact of environmental factors like temperature, bias conditions, and neutron exposure on circuit reliability. Key areas include multicell upsets, single-event upset (SEU) cross-section analysis, and the efficacy of radiation-hardened-by-design (RHBD) techniques. Awards & Recognition: None explicitly listed in the provided text. However, his extensive publications in top-tier journals like IEEE Transactions on Nuclear Science highlight his contributions to the field. Grants & Advising: Advises on projects related to advanced semiconductor technologies and radiation effects. His research has been supported by grants from institutions focusing on space electronics and nanotechnology. No specific grant details or student advisees are listed. Labs & Teams: Likely affiliated with Vanderbilt’s Cyber-physical Systems and Nano Science and Technology research neighborhoods, though specific lab names are not mentioned in the text.

Suman Dattaمشاهده پروفایل

استاد

• Semiconductor Devices
• Nanotechnology
• VLSI Systems
• +۷ مورد دیگر

Suman Datta is a Professor at the Georgia Institute of Technology , holding the Joseph M. Pettit Chair in Advanced Computing and Georgia Research Alliance Eminent Scholar titles. He has a joint appointment with the School of Materials Science and Engineering. Education : B.Tech in Electrical Engineering from IIT Kanpur; Ph.D. in Electrical and Computer Engineering from the University of Cincinnati. Prior Appointments : Stinson Endowed Chair Professor of Nanotechnology at University of Notre Dame (2015–2022); Professor at Penn State (2007–2015); Intel Corporation (1999–2007) in Advanced Transistor Group. Research Interests : His work focuses on high-performance heterogeneous computing using advanced CMOS and beyond-CMOS semiconductors. Key areas include ferroelectric field-effect transistors (FeFETs) , cryogenic computing , in-memory computing , and brain-inspired computing . He explores materials like ferroelectric gate stacks , insulator-to-metal phase transition oxides , and high-mobility oxides for next-generation compute architectures. Recent Article Trends : His group’s publications emphasize BEOL-compatible oxide transistors , negative capacitance , radiation-resilient devices , and machine learning-aided modeling . Subfields include low-voltage memory , 3D Ising machines , dynamic logic at cryogenic temperatures , and monolithic integration of power delivery systems. Scientific Awards : IEEE Fellow (2013) for contributions to transistor technologies NAI Fellow (2016) for societal impact via patents Intel Achievement Award (2003) for high-k/metal gate CMOS Intel Logic Technology Quality Award (2002) for Tri-gate transistors SEMI Award (2012) for high-k dielectrics Penn State Outstanding/ Premier Research Awards (2012, 2015) Advising & Grants : He has mentored students like Wriddhi Chakraborty , Khandker Akif Aabrar , and Sourav Dutta . His research is funded by SRC , DARPA , and NSF , including leadership of the ASCENT and EXCEL centers. Labs & Collaborations : Datta directs the STAR Lab at Georgia Tech, which specializes in atomistic modeling , nanofabrication , and compact model development . The lab collaborates with industry giants like Intel , Micron , and IBM through the ASCENT center.

Aaron Theanمشاهده پروفایل

استاد

• Semiconductor Technology
• Advanced Electronics
• Nanoelectronics
• +۶ مورد دیگر

Prof Aaron Thean is the Deputy President (Academic Affairs) and Provost at the National University of Singapore (NUS). Formerly, he served as Dean of the College of Design and Engineering at NUS and held senior roles at IMEC (Belgium) as Vice President of Logic Technologies and Director of Logic Devices Research. His expertise spans advanced semiconductor device technologies, including FinFETs, nanowire FETs, III-V/Ge channels, and emerging beyond-CMOS architectures. He holds degrees from the University of Illinois Urbana-Champaign (B.Sc., M.Sc., Ph.D. in Electrical Engineering) and has published over 300 papers with 50+ patents. His awards include the Gregory Stillman Award (2001) and Compound Semiconductor Innovation Award (2014). Research interests focus on semiconductor innovation, device-process co-optimization (DTCO), and monolithic 3D integration. Notable contributions include industry-first Gate-First HKMG technologies, advanced strained silicon platforms, and neuromorphic computing hardware. His work bridges academia and industry through collaborations with Qualcomm, IBM, and foundry partners. Current initiatives emphasize energy-efficient computing and wearable sensor systems. Prof Thean’s leadership spans NUS-wide academic strategy and global research partnerships. His technical legacy includes foundational advancements in transistor scaling, low-power CMOS design, and AI-driven failure analysis methodologies.

• Materials Engineering
• Electrical Engineering
• Nanotechnology
• +۳ مورد دیگر

Raisul Islam is an Assistant Professor of Materials Engineering at Purdue University, with a courtesy appointment in Electrical and Computer Engineering. His research focuses on advanced materials for energy technologies, semiconductor devices, and nanoscale memory systems. He holds affiliations with the College of Engineering and is actively involved in interdisciplinary collaborations. His work emphasizes the development of novel materials and device architectures for applications in solar energy, resistive memory, and neuromorphic computing. Key areas include photovoltaic cell optimization, phase-change memory innovation, and the integration of nanotechnology with electronics. Notable research trends from his publications (2020–2023) highlight advancements in tandem solar cell efficiency, thermal management in resistive memory, and multilevel switching mechanisms in ferroelectric tunnel junctions. His work bridges fundamental materials science with practical device engineering, addressing both performance and scalability challenges. Dr. Islam’s lab focuses on experimental and computational materials characterization, with a focus on thin films, nanoscale interfaces, and energy-efficient electronics. His contributions span academic journals and industry collaborations, targeting next-generation energy and computing technologies.

• Machine Learning in Electronics
• Electrostatic Discharge (ESD) Protection
• Circuit Reliability
• +۳ مورد دیگر

Elyse Rosenbaum is the Melvin and Anne Louise Hassebrock Professor in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. She also serves as the Acting Associate Dean for Research at the Grainger College of Engineering. She is the director of the NSF-supported Center for Advanced Electronics through Machine Learning (CAEML), a collaboration between the University of Illinois, North Carolina State University, and Penn State University. Education: Ph.D. in Electrical Engineering, University of California, Berkeley, 1992 M.S. in Electrical Engineering, Stanford University B.S. in Electrical Engineering, Cornell University (with distinction) Research Interests: Her research focuses on machine learning applications in electronics, ESD-robust high-speed I/O circuit design, compact modeling, behavioral modeling of circuits, and CDM-ESD protection for advanced packaging technologies. Scientific Awards: IEEE Fellow for contributions to electrostatic discharge reliability of integrated circuits Best Student Paper Award, IEDM Outstanding and Best Paper Awards, EOS/ESD Symposium Technical Excellence Award, SRC NSF CAREER Award IBM Faculty Award ESD Association’s Industry Pioneer Recognition Award Advising and Grants: She supervises graduate and undergraduate researchers, primarily focusing on those with strong academic records and relevant experience. Her work is supported by NSF and other prominent organizations. Labs and Teams: She leads the CAEML center, which aims to apply machine learning to optimize microelectronic circuits and systems, enhancing design automation and reliability.

Luca Carloniمشاهده پروفایل

استاد

• Computer Science
• Embedded Systems
• Hardware Design
• +۶ مورد دیگر

Luca Carloni is a Professor of Computer Science and Department Chair at Columbia University's Columbia Engineering. He leads the System-Level Design Group, focusing on heterogeneous system-on-chip (SoC) architectures, networks-on-chip (NoC), and embedded systems. Carloni holds a Laurea Summa Cum Laude in Electronics Engineering from the University of Bologna and a PhD in Electrical Engineering and Computer Sciences from UC Berkeley. His work emphasizes specialized hardware design, energy-efficient computing, and FPGA-based prototyping. Research interests include system-level design methodologies for SoCs, embedded accelerators, and quantum computing hardware. He has pioneered frameworks like Embedded Scalable Platforms (ESP) and tools like MosaicSim for rapid SoC prototyping. Carloni has received numerous awards, including the NSF CAREER Award (2006), IEEE Fellow (2017), and multiple best paper awards at DATE and CloudCom conferences. He has served on editorial boards of IEEE Transactions on CAD and ACM Transactions on Embedded Computing , and chaired key conferences like EMSOFT and ESWeek. His research addresses challenges in heterogeneous architectures, power management, and the intersection of machine learning with embedded systems. Current projects explore quantum control systems, brain-computer interfaces, and energy-efficient datacenter computing.

• Neuromorphic Computing
• Memristor-Based Architectures
• Energy-Efficient AI Hardware
• +۷ مورد دیگر

Said Hamdioui serves as a full Professor in the Department of Computer Engineering within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His research focuses on cutting-edge hardware architectures for neuromorphic computing and energy-efficient AI acceleration, with particular emphasis on memristor-based systems, emerging memory technologies, and fault-tolerant designs for edge applications. His research interests span Neuromorphic Computing , Memristor-Based Architectures , and Energy-Efficient AI Hardware , addressing critical challenges in hardware security, computation-in-memory, and reliable edge AI deployment. Recent work demonstrates significant advancements in RRAM/FeFET testing methodologies, spiking neural network implementations, and spin wave computing alternatives to traditional CMOS. His publications reveal strong trends toward real-world deployment of brain-inspired hardware with practical constraints like power efficiency, testability, and security. Award highlights include: DATE'20 Best Paper Award DFT'21 Outstanding Student Paper ETS 2021 Best Paper Award LATS 2018 & 2022 Best Paper Awards Professor Hamdioui actively contributes to the research community through editorial roles at IEEE Transactions on VLSI Systems , IEEE Design & Test , and Journal of Electronic Testing from 2017-2018. His leadership in multi-partner projects like CONVOLVE and NEUROKIT2E demonstrates strong industry-academia collaboration for edge AI solutions. Current work shows increasing focus on practical deployment challenges including in-field fault monitoring, security vulnerabilities in neuromorphic systems, and realistic brain simulation frameworks.

Kaushik Nayakمشاهده پروفایل

دانشیار

• Semiconductor Devices
• Mesoscopic Electronics
• Nanoelectronics
• +۳ مورد دیگر

Kaushik Nayak is an Associate Professor in the Department of Electrical Engineering at the Indian Institute of Technology Hyderabad . His research spans semiconductor device physics, mesoscopic electronics, and electro-thermal effects in nanoscale transistors, with recent work on diamond MOSFETs, 2D material contacts, and thermal resistance in nano-sheet FETs. Ph.D., Indian Institute of Technology Bombay M. Tech., Microelectronics, IIT Bombay B.E., Electronics & Telecommunication, Utkal University He teaches advanced courses on semiconductor device modeling, mesoscopic electronics, and electromagnetic wave propagation. His publications focus on nanoelectronics, device variability, and high-temperature operations. Contact: knayak@ee.iith.ac.in .

• Hyperdimensional Computing
• Neuromorphic Hardware
• In-Memory Computing
• +۳ مورد دیگر

Paul R. Genssler is a Dr.-Ing. researcher at the Chair of AI Processor Design (AI-Pro) within the Technical University of Munich (TUM), actively advancing hardware solutions for artificial intelligence under Prof. Hussam Amrouch. His work bridges computer engineering and emerging technologies, focusing on overcoming fundamental limitations in conventional computing architectures through brain-inspired paradigms. His research spans critical domains in next-generation computing: Hyperdimensional Computing for robust pattern recognition and bioinformatics applications Neuromorphic and In-Memory Computing architectures for energy efficiency Reliability engineering for emerging memory technologies (FeFET, etc.) Quantum computing support systems including cryogenic embedded electronics Machine learning-driven transistor aging prediction and mitigation Analysis of his 15 most recent publications (2023-2024) reveals a dominant trend toward hyperdimensional computing as a unifying framework for addressing reliability challenges in emerging technologies. His work consistently integrates in-memory computing techniques to bypass von Neumann bottlenecks while targeting real-world applications like genome matching and unsupervised learning. A significant portion focuses on error-resilient implementations for unreliable nanoscale devices, demonstrating exceptional cross-stack expertise from transistor physics to algorithm design. As a core member of TUM's AI Processor Design group affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI), Genssler collaborates extensively on projects spanning cryogenic quantum control systems, FPGA-based AI resilience, and monolithic 3D integration. The team operates at the intersection of semiconductor physics, computer architecture, and machine learning, with strong industry connections evident through publications at DATE, ASP-DAC, and ICCAD.

Guofu Niuمشاهده پروفایل

استاد

• Semiconductor Devices
• Compact Modeling
• RF Circuit Design
• +۳ مورد دیگر

Guofu Niu is a Professor in the Department of Electrical and Computer Engineering at Auburn University, holding the Ed and Peggy Reynolds Family endowed chair. His research specializes in semiconductor device physics, compact modeling of SiGe heterojunction bipolar transistors (HBTs), FinFETs, and cryogenic electronics for RF and power applications. Key research areas include RF linearity characterization, avalanche effects, thermal noise, and low-temperature device performance. He has developed advanced models (e.g., Mextram) for circuit simulation tools, enhancing the accuracy of semiconductor design workflows. Publications focus on nano-scale device reliability, tunneling currents, and optimization of RF amplifiers, with applications in 5G technology and extreme-environment electronics. Collaborative projects span industry and academia to advance semiconductor modeling frameworks.

Mustapha C.E. Yagoubمشاهده پروفایل

استاد

• RF/Microwave Circuit Design
• RFID Systems
• Antenna Design
• +۵ مورد دیگر

Mustapha C.E. Yagoub is a Full Professor at the School of Electrical Engineering and Computer Science, University of Ottawa, with over 500 publications in RF/microwave CAD, RFID systems, neural networks, and applied electromagnetics. He leads research in the ELEMENT Laboratory and RFM Research Group , focusing on wireless communication systems and nonlinear device modeling. PhD in Electronics (Institut National Polytechnique de Toulouse, 1994) Magister in Telecommunications (École Nationale Polytechnique d'Alger, 1987) Dipl.-Ing. in Electronics (École Nationale Polytechnique d'Alger, 1979) His research bridges Microwave Circuit Design with Artificial Intelligence , including applications in Energy Conservation and Telecommunication Systems . Key trends in his publications include hybrid modeling techniques combining Neural Networks with Computational Electromagnetics for optimizing Antenna Design and RF Components . He is a Senior Member of IEEE and licensed with the Professional Engineers of Ontario and Ordre des Ingénieurs du Québec . His lab teams focus on High-Tc Superconducting Devices and Directional Antenna Optimization for RFID networks.

• Nanotechnology
• Ferroelectric Materials
• 2D Materials
• +۳ مورد دیگر

Wenjuan Zhu is an Associate Professor in the Department of Electrical and Computer Engineering, Materials Science and Engineering, and the Micro and Nanotechnology Lab at the University of Illinois at Urbana-Champaign. She holds the W.J. "Jerry" Sanders III - Advanced Micro Devices Inc. Scholar distinction and serves as Associate Head for Graduate Programs. Her research focuses on nanotechnology, ferroelectric materials, and semiconductor devices, particularly in 2D materials and their applications in electronics and reconfigurable logic circuits. Key research areas include van der Waals heterostructures, ferroelectric transistors, and high-temperature electronics. She has received prestigious awards such as the DARPA Young Faculty Award (2020), IBM Faculty Award (2018), and NSF CAREER Award (2017). Her work bridges fundamental materials science with device engineering, advancing next-generation electronic systems. Notable contributions include non-volatile reconfigurable transistors, wafer-scale MoTe₂ growth, and ferroelectric field-effect transistors. Her research emphasizes scalable synthesis methods and industrial applicability of 2D materials. Collaborations span global institutions, reflecting her impact in nanoelectronics and materials innovation.