جستجوی استاد راهنمای دانشگاهی

Edoardo Charbon is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Engineering, where he leads the Advanced Quantum Architecture Lab (AQUA). He also serves on the School Council STI and is Co-Director of STI-SSIQ Administration. Previously, he was a full professor and chair at Delft University of Technology from 2008 to 2016. Charbon received his Elektrotechnik Diploma from ETH Zurich, M.S. from UC San Diego, and Ph.D. from UC Berkeley, all in electrical engineering. His career spans industry experience at Cadence Design Systems and Canesta Inc. before joining EPFL in 2002. His research focuses on ultra high-speed and 3D optical sensors, with applications in LiDAR, FLIM (Fluorescence Lifetime Imaging Microscopy), PET (Positron Emission Tomography), FCS (Fluorescence Correlation Spectroscopy), and NIROT (Near-Infrared Optical Tomography). He has pioneered deep-submicron CMOS SPAD technology, which is now mass-produced and used in smartphones, telemeters, and medical diagnostics. His recent work bridges cryo-CMOS circuits for quantum computing with advanced optical sensing techniques. Analysis of his recent publications reveals a strong trend toward integrating quantum technologies with practical imaging applications. His work spans from fundamental device development (SPAD sensors, cryo-CMOS circuits) to applied systems (LiDAR engines, medical imaging devices), with increasing integration of machine learning techniques for real-time processing. 2023 IISS Pioneering Achievement Award Fellow of the IEEE Distinguished visiting scholar, W. M. Keck Institute for Space at Caltech Fellow, Kavli Institute of Nanoscience Delft Distinguished lecturer, IEEE Photonics Society Professor Charbon has authored or co-authored over 500 papers and two books, and holds 27 patents. His research has been supported by collaborations with organizations including Bosch, X-Fab, Texas Instruments, Maxim, Sony, Agilent, and the Carlyle Group. He has driven significant innovation in CMOS SPAD technology, which is now commercially deployed in various applications. He leads the Advanced Quantum Architecture Lab (AQUA) at EPFL, which focuses on the development of advanced sensor systems combining quantum technologies with conventional electronics. The lab has been instrumental in creating SPAD-based imaging systems that push the boundaries of time-resolved optical detection.

• Ultra High-Speed Optical Sensors
• 3D Optical Sensors
• LiDAR
• +۱۰ مورد دیگر

Christian Enz is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he serves as Director of the Institute of Microengineering and Head of the Integrated Circuits Laboratory. With M.S. and Ph.D. degrees in electrical engineering from EPFL (1984 and 1989), he has established himself as a leading researcher in low-power analog circuit design and semiconductor device modeling. His research interests focus on very low-power analog and RF IC design , semiconductor device modeling , and increasingly on cryogenic electronics for quantum computing applications . Professor Enz is particularly known for his work on FDSOI MOSFET behavior at cryogenic temperatures, developing comprehensive models that address challenges in subthreshold swing saturation, threshold voltage shifts, and self-heating effects. As a Life Fellow of IEEE with 282 publications and over 7,400 citations, Professor Enz has made significant contributions to the field. His recent work demonstrates how the $G_{m}/I_{D}$ design methodology remains effective in advanced technology nodes and can be extended to cryogenic temperature operation. His research bridges fundamental semiconductor physics with practical circuit design considerations for quantum computing interfaces. Life Fellow, IEEE Director of the Institute of Microengineering, EPFL Head of the Integrated Circuits Laboratory 282 publications with 7,400+ citations Specialist in cryogenic CMOS for quantum computing Professor Enz's work on cryogenic electronics addresses critical challenges for quantum computing scalability. By developing accurate models for transistor behavior at temperatures as low as 3.3K, his research enables the design of specialized control electronics that can operate inside dilution refrigerators, potentially solving major wiring constraints that currently limit quantum computer scaling. His laboratory continues to advance the understanding of semiconductor device physics at cryogenic temperatures while developing practical circuit design methodologies for this emerging application domain.

• Very low-power analog circuit design
• RF IC design
• Semiconductor device modeling
• +۴ مورد دیگر

Dr. Yiran Chen is the John Cocke Distinguished Professor at Duke University's Department of Electrical and Computer Engineering, leading the NSF AI Institute for Edge Computing (Athena) and the Duke Center for Computational Evolutionary Intelligence (DCEI). A global leader in neuromorphic computing, emerging memory systems, and edge AI, he holds prestigious roles including IEEE Fellow and Editor-in-Chief of IEEE Transactions on Circuits and Systems for AI. His research spans machine learning accelerators, security-hardened hardware, and co-design of EDA tools with LLMs. With over 700 publications and 96 patents, he has been awarded 15 paper awards and 17 nominations, including rare Technical Achievement Awards from IEEE societies. He advises over 60 PhD students and 4 postdocs, many of whom hold academic positions worldwide. His work bridges academia and industry, contributing to startups and venture capital through his board roles. Education: B.S. (Tsinghua, 1998) → M.S. (Tsinghua, 2001) → Ph.D. (Purdue, 2005). Career path: Assistant/Associate Professor at University of Pittsburgh (2010–2014) → Duke since 2014. Awards include the ACM SIGDA Outstanding New Faculty Award (2014), NSF CAREER Award (2013), and the Stansell Family Distinguished Research Award (2022). Research focuses on innovations in: (1) Non-volatile memory architectures for AI acceleration, (2) Hardware-software co-design for edge computing, (3) Security in neuromorphic systems, and (4) Large-scale ML for EDA. His group pioneered ReRAM-based accelerators like ReBNN and MARC, and introduced novel edge AI frameworks like Ecco and Prosperity. These works address scalability, energy efficiency, and real-time performance challenges. Key initiatives include the NSF IUCRC for Alternative Sustainable & Intelligent Computing (ASIC), advancing sustainable computing through novel materials and architectures. His leadership in standard-setting bodies like the IEEE Circuits and Systems Society ensures cutting-edge research translates into industry practices. Grants: Lead PIs for multiple NSF AI Institutes and industry partnerships. Labs: Directs the Athena Institute and DCEI, fostering collaboration between academia and industry. Current projects include quantum computing placement algorithms (QPlacer), federated learning frameworks (FedGPT), and neuro-symbolic architectures.

• Emerging memory and storage technologies
• Embedded systems
• Cyber-Physical Systems (CPS)
• +۵ مورد دیگر

Alexander Zaslavsky is a Professor of Engineering and Physics at Brown University, where he has been a faculty member since 1994. He received his Ph.D. in electrical engineering from Princeton University in 1991 and completed postdoctoral work at IBM Research. His research spans semiconductor device physics with focus on novel device concepts that could supplement silicon transistor technology. He maintains active collaborations with institutions in France and has served as editor of Solid State Electronics since 2003. PhD in Electrical Engineering, Princeton University (1991) MS in Electrical Engineering, Princeton University (1988) BA, Harvard University (1986) Professor Zaslavsky's research focuses on developing alternative semiconductor devices that could supplement conventional silicon technology. His work spans five main areas: (1) quantum transport in silicon-based nanostructures and resonant tunneling; (2) tunneling-based semiconductor devices in silicon-on-insulator and germanium-on-insulator technology; (3) thin film transistors based on conducting oxides and iodides; (4) flexible metallic interconnects for flexible electronics; and (5) probabilistic computing implemented in silicon technology. His research bridges fundamental physics with practical device applications, particularly in low-power electronics and novel sensing mechanisms. Analysis of Professor Zaslavsky's recent publications reveals a strong focus on cryogenic electronics for quantum computing interfaces, novel memory architectures, and germanium-based photodetectors. His work increasingly intersects with quantum computing needs, particularly in developing cryo-CMOS circuitry and memory solutions. There's also continued emphasis on sharp-switching devices for ultra-low power applications and exploration of alternative materials like copper iodide for transparent electronics. The research demonstrates a strategic evolution from fundamental device physics toward applications in emerging computing paradigms. Alfred P. Sloan Fellowship (1995) Office of Naval Research Young Investigator Award (1995) National Science Foundation Career Award (1997) Editor of Solid State Electronics international journal (2003-present) Visiting Senior Chair of Excellence at Nanosciences Foundation, Grenoble (2009-2012) Professor Zaslavsky has mentored numerous students whose alumni have gone on to semiconductor companies (Micron, Applied Materials, GlobalFoundries, Synopsys), government labs (NIST, CNRS, Paul Scherrer Institute), and major industrial companies (EMC, Apple). His research has been supported by extensive funding including: Alfred P. Sloan Foundation ($30,000, 1995-1999); Office of Naval Research Young Investigator award ($265,750, 1995-1998); multiple NSF grants totaling over $1.5 million; Semiconductor Research Corporation subcontract ($95,000, 1998-2002); and Air Force Office of Scientific Research MURI award (sharing $350,000 annually, 2000-2005). Professor Zaslavsky leads an active research laboratory at Brown University focused on semiconductor device physics and engineering. Current projects include Cryo-CMOS and magnetic sensing (with Xiao lab at Brown, Tufts, NIST-Gaithersburg, CoolCAD Electronics, and MIT-Lincoln Laboratory); and Germanium quantum dot photodetectors (with Pacifici lab at Brown). The lab has previously worked on nitride hot electron and tunneling transistors, amorphous indium-zinc-oxide devices, tunneling devices in SOI, noise-immune CMOS design, Si and SiGe nanowire tunneling transistors, carbon nanotube devices, and flexible metal interconnects. The lab emphasizes comprehensive training from device fabrication to characterization and modeling.

• Semiconductor Devices
• Nanoelectronics
• Quantum Transport
• +۶ مورد دیگر

D'ANIELLO FEDERICO is a Fixed-term Researcher at the University of Milan-Bicocca, affiliated with the Department of Physics 'Giuseppe Occhialini'. His work focuses on advanced electronics and integrated circuits design, particularly for quantum computing and automotive networks. Email: federico.daniello@unimib.it His research spans FinFET technology , low-noise amplifier (LNA) design , and single-event upset characterization in nanoscale transistors. Recent studies include applications in cryo-CMOS systems and high-speed automotive transceivers . Key trends in his publications involve semiconductor device modeling , quantum hardware optimization , and robust communication protocols for automotive environments.

• Electronics
• Integrated Circuits Design
• Quantum Computing
• +۳ مورد دیگر

Yifei Zhang is an Assistant Professor in the Department of Computer Science at Northeastern University's School of Computer Science and Engineering, with extensive research collaborations including the University of Hong Kong (notably with Irwin King). Active since 2009, Zhang has produced 257 publications through 2025, demonstrating sustained research productivity across artificial intelligence domains. Zhang's research spans Artificial Intelligence , Machine Learning , and Computer Vision , with recent focus on federated learning systems, multimodal AI, and security applications. The work shows strong technical depth in developing novel algorithms for personalized learning, anomaly detection, and efficient model training. Recent publications reveal increasing specialization in privacy-preserving machine learning and cross-modal understanding, particularly for Chinese language and cultural contexts. Publication trends indicate growing influence in AI conferences (CVPR, ACL, NeurIPS), with 61 publications in 2024 alone. The research demonstrates practical applications in cybersecurity, education technology, and urban planning, while maintaining theoretical rigor in model architecture and optimization techniques. Zhang frequently collaborates with Neng Gao and Shuang Song on security-related AI projects. Zhang serves on program committees for major AI conferences and has contributed to workshop organization including FL@FM-TheWebConf'25: International Workshop on Federated Foundation Models for the Web. The research has attracted significant attention in the AI community, particularly in federated learning and multimodal systems.

• Artificial Intelligence
• Machine Learning
• Federated Learning
• +۳ مورد دیگر

Kaustav Banerjee is a Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara (UCSB). He is a globally recognized leader in nanoelectronics, specializing in 2D materials such as graphene and van der Waals heterostructures. His research focuses on energy-efficient electronics, photonics, bioelectronics, and 3D integrated circuits. Banerjee holds visiting/adjunct professorships at institutions including Tokyo Institute of Technology, Universität der Bundeswehr München, and Shanghai Jiao Tong University. Banerjee earned his PhD in Electrical Engineering and Computer Sciences from the University of California, Berkeley. His work has led to commercialized innovations in nanoscale interconnects and 3D ICs, including the groundbreaking Kinetic Inductor overcoming Faraday's 200-year-old inductance density limit. His research interests emphasize strain engineering in 2D FETs, quantum computing interconnects, and cryogenic CMOS integration. Notable contributions include high-performance monolayer 2D stacked nanosheet FETs and advancements in ferroelectric FET-based memory systems. Banerjee has been honored with prestigious awards, including the IEEE Kiyo Tomiyasu Award, Friedrich Wilhelm Bessel Research Award, and recognition as a Highly Cited Researcher by Clarivate Analytics. He advises students who have won multiple awards, including the UCSB Lancaster Dissertation Award and IEEE Electron Devices Society PhD Fellowships. His interdisciplinary work spans collaborations with industry and academia, addressing challenges in next-generation electronics, quantum computing, and biomedical applications.

• Nanoelectronics
• 2D Materials
• Photonics
• +۵ مورد دیگر

Xiaolong Liu serves as Assistant Professor at Southern University of Science and Technology's School of Microelectronics. His academic journey includes a Ph.D. from Hong Kong University of Science and Technology (2019), M.E. from Tsinghua University (2014), and B.E. from Beijing University of Aeronautics and Astronautics (2010). Prior to his current position, he worked as Staff Engineer at eTopus Technology in Silicon Valley (2019-2021) and completed a postdoc at HKUST. Ph.D. in Electronic and Computer Engineering, Hong Kong University of Science and Technology (2019) M.E. in Microelectronics, Tsinghua University (2014) B.E. in Electronic Engineering, Beijing University of Aeronautics and Astronautics (2010) Dr. Liu's research spans cutting-edge RF/mm-Wave/THz integrated circuit design, focusing on high-performance signal generators , ultra-wideband transceivers , and low-power frequency synthesis . His work addresses critical challenges in 5G/6G communications, terahertz spectroscopy, and high-speed wireline interfaces through innovative CMOS architectures. Technical emphases include varactor-less VCOs, harmonic enhancement techniques, and magnetic tuning mechanisms for millimeter-wave systems. His publication portfolio demonstrates consistent leadership in IEEE flagship journals/conferences (JSSC, TMTT, ISSCC, VLSI), with recent work advancing Class-F oscillators, sub-sampling PLLs, and sub-THz synthesizers. Notable trends include migration toward sub-THz frequencies (2023-2025) , multi-core oscillator architectures , and elimination of harmonic tuning for simplified design. IEEE VLSI Paper Technical Highlights (2019) IEEE CICC Invited Talk (2019) IEEE TVLSI 2023 Best Reviewer Award Top 4 Most Downloaded Paper in TCAS-II (July 2022) Dr. Liu actively mentors students through SUSTech's graduate programs, with advisees consistently earning university-level thesis awards and conference recognitions. His lab maintains strong industry ties through silicon validation and collaborates on cutting-edge tapeouts in 7nm/16nm nodes. Current projects focus on cryo-CMOS interfaces for quantum computing and ultra-wideband transceivers for 6G applications. His research group operates within SUSTech's state-of-the-art microelectronics facility, specializing in mm-Wave/THz characterization and high-speed SerDes validation. The team maintains partnerships with semiconductor foundries for advanced-node prototyping and collaborates with industry leaders on real-world implementation challenges.

• RF/mm-Wave/THz Wireless Transceivers
• High-Speed SerDes
• PLLs/Frequency Synthesizers
• +۴ مورد دیگر

Maja Clare Cassidy is a Senior Lecturer, ARC DECRA Fellow, and Scientia Fellow at the University of New South Wales School of Physics. Her research develops quantum computing and sensor technologies, leading the QMD lab while teaching advanced quantum physics courses. Current roles: Senior Lecturer (UNSW), Lab Director, Course Instructor Previous roles: Principal Research Manager at Microsoft Quantum (5 years), Postdoctoral Fellow at TU Delft/QuTech Education: Bachelor of Electrical Engineering (Hons. 1), UNSW (2005) Master of Science in Applied Physics, Harvard University (2010) PhD in Applied Physics, Harvard University (2012) Her research focuses on quantum computing device fabrication , topological superconductivity , microwave quantum optics , and machine learning applications in quantum system development. Key trends in her publications include Majorana qubit stability, ballistic transport in nanowires, and cryogenic CMOS integration for scalable quantum systems. Scientific Awards: RG Menzies Scholarship to Harvard (2008) She supervises 10 current and former students across physics and material science disciplines. Her grants include UNSW Scientia Fellowship (2022-2026), ARC DECRA Fellowship (DE240100590), and multiple industry collaboration grants for quantum hardware development.

• condensed matter physics
• quantum physics
• quantum computing
• +۳ مورد دیگر