جستجوی استاد راهنمای دانشگاهی

Andras Kisمشاهده پروفایل

استاد

• 2D Materials
• Nanoscale Electronics
• Optoelectronics
• +۳ مورد دیگر

Andras Kis is a Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI) across multiple institutes including the Institute of Electrical Engineering (IEL), Institute of Materials Science (IMX), and teaching programs in Electrical Engineering (SEL-ENS). He leads the Laboratory of Nanoscale Electronics and Structures (LANES) and serves on the PhD program committee for Microsystems and Microelectronics. PhD, EPFL (2003) MS, Physics, University of Zagreb (1999) Baccalaureate, MIOC High School Research Focus: Pioneering work on 2D materials for electronic and optoelectronic devices, particularly transition metal dichalcogenides like MoS2 and PtSe2. His research spans: Transistor design with atomically thin semiconductors Excitonic devices and valleytronics Nanofluidics and ionic logic Optical properties of 2D heterostructures Scalable fabrication of 2D materials Defect engineering and doping techniques Scientific Impact: Based on analysis of 15 most recent publications, his work focuses on advancing 2D materials for next-generation electronics through innovations in: Van der Waals heterostructures Thermoelectric and optoelectronic applications Nanofabrication techniques Spintronic and quantum transport phenomena Memristive and neuromorphic devices Characterization of electronic and optical properties Awards & Recognition: Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Lotfi A. Zadeh Award for Emerging Technologies (2024) Highly Cited Researcher (Clarivate Analytics) Teaching & Academic Leadership: Currently teaching courses including Lab in Nanoelectronics , Physical Models for Micro and Nanosystems , and Semiconductor Devices II . He has supervised over 20 PhD students in his research group at EPFL. Laboratory & Collaborations: Directs the Laboratory of Nanoscale Electronics and Structures (LANES) which focuses on fundamental and applied research in 2D materials and nanoelectronic devices. His work bridges materials science, condensed matter physics, and microelectronics engineering.

Stefano Fusiمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Theoretical Neuroscience
• Neural Circuit Modeling
• +۲ مورد دیگر

Stefano Fusi is an Associate Professor of Neuroscience at Columbia University's Vagelos College of Physicians and Surgeons, with joint affiliations at the Mortimer B. Zuckerman Mind Brain Behavior Institute and Kavli Institute. His laboratory focuses on computational modeling of neural circuits and neuromorphic engineering. Education PhD in Physics, Hebrew University of Jerusalem (1999) BS in Physics, Sapienza University of Rome (1992) Research Focus Fusi investigates how biological complexity supports neural computation through three primary domains: theoretical analysis of neural circuit dynamics, representational geometry in learning systems, and hardware implementations of brain-inspired algorithms. His work bridges machine learning, neurophysiology, and theoretical physics, emphasizing high-dimensional representations and memory optimization. Recent publications demonstrate consistent focus on neural coding principles across hippocampus, prefrontal cortex, and sensory systems, with innovations in modeling working memory, stress responses, and cross-species computational paradigms. Collaborations & Labs Leads an interdisciplinary laboratory collaborating with Columbia experimental neuroscientists, MIT engineers, and Stanford computational researchers to validate theoretical models. Current projects include neuromorphic hardware development and neural decoding of emotional states.

• Integrated Photonics
• Optical Frequency Combs
• Silicon Photonics
• +۴ مورد دیگر

Minghao Qi is a Professor in the Department of Electrical and Computer Engineering at Purdue University's College of Engineering, West Lafayette. His research focuses on integrated photonics systems for optical communications, quantum information, and precision metrology applications. Professor Qi's work spans several critical photonics domains: Design and application of microresonator-based optical frequency combs (Kerr combs) Silicon and silicon nitride integrated photonic circuits Thin-film lithium niobate devices for nonlinear optics Quantum information processing using frequency-bin entangled photons Photonic neuromorphic computing with machine learning co-design Optical sensors and time-of-flight ranging systems Analysis of his 2022-2025 publications reveals three dominant research vectors: (1) Vernier microcombs for optical atomic clocks and RF stabilization, (2) Trident edge coupler architectures for octave-spanning nonlinear processes on lithium niobate, and (3) Physics-informed neural networks applied to photonic device design and signal processing. His recent work demonstrates strong convergence between integrated photonics, quantum technologies, and machine learning.

Tobi Delbruckمشاهده پروفایل

استاد

• Neuromorphic Engineering
• Event-Based Vision Systems
• Silicon Retinas
• +۶ مورد دیگر

Tobi Delbruck is a titular professor of physics and electrical engineering at ETH Zurich, where he leads the Sensors Group at the Institute for Neuroinformatics (INI) in Zurich, Switzerland. He collaborates closely with Shih-Chii Liu and Giacomo Indiveri as part of the 'hardware groups' at INI. Delbruck has also served as visiting faculty at Caltech and is a Fellow of the IEEE. His work focuses on bio-inspired and neuromorphic event-based sensory processing systems. Professor Delbruck's research spans multiple areas of neuromorphic engineering, with particular emphasis on event-based vision systems and low-power analog VLSI circuits. His work has significantly advanced the field of Dynamic Vision Sensors (DVS), which mimic the human retina's response to changes in brightness rather than capturing full frames. This approach enables extremely low-latency vision processing with minimal power consumption, making it ideal for high-speed applications and robotics. His research has applications in robotics, autonomous systems, and low-power embedded vision. Delbruck is an active contributor to the neuromorphic engineering community, co-organizing the annual Telluride Workshop on Neuromorphic Engineering and serving in leadership roles with IEEE. He has authored numerous influential publications and co-authored books including "Event-Based Neuromorphic Systems" and "Analog VLSI: Circuits and Principles." His jAER (Java Address-Event Representation) project provides open-source tools for real-time event-based sensory processing. Analysis of his recent publications shows a clear trend toward integrating event-based vision with deep learning techniques and applying these systems to practical robotics problems. His scientific achievements have been recognized with multiple awards including: IEEE Fellow Winner of Best Live Demonstration award at ISCAS 2012 Honorable Mention Award from Sensory Systems Technical Committee at ISCAS 2012 Overall Best Student Paper Award and Best Paper Award from Sensory Systems Technical Committee at ISCAS 2010 Winner of the 2006 ISSCC Jan Van Vessem Outstanding European Paper Award Professor Delbruck actively mentors students and has supervised numerous PhD and Master's theses in the areas of neuromorphic engineering and event-based vision systems. His group has secured significant research funding from various sources to support their innovative work in bio-inspired sensory processing. He teaches courses on "Electronics for Physicists II (Digital)" and "Neuromorphic Engineering," helping to train the next generation of researchers in this field. The Sensors Group at INI, which Delbruck leads, operates state-of-the-art facilities for designing and testing neuromorphic vision systems. The group maintains close collaborations with researchers worldwide and has developed several important open-source resources including the jAER project and bias generator design kits. Their work continues to push the boundaries of what's possible with event-based sensory processing, with applications ranging from high-speed robotics to low-power embedded vision systems.

Tosiron Adegbijaمشاهده پروفایل

دانشیار

• Computer Architecture
• Embedded Systems Design
• Low-Power Embedded Systems
• +۱۴ مورد دیگر

Tosiron Adegbija is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Arizona, where he serves as Director of Graduate Studies and Thomas R. Brown Endowed Fellow. He is a member of the Graduate Faculty and actively contributes to research and teaching in computer architecture and embedded systems. Education: PhD in Electrical and Computer Engineering, University of Florida, 2015 MS in Electrical and Computer Engineering, University of Florida, 2011 BS in Electrical Engineering, University of Ilorin, Nigeria, 2005 His research centers on energy-efficient computing with a focus on bio-inspired computer architecture , including spiking neural network (SNN) accelerators and in-memory computing. He also explores domain-specific architectures , adaptable memory systems , and microprocessor optimizations for IoT . His work leverages novel memory technologies like STT-RAM to enhance performance and reduce energy consumption in embedded and resource-constrained systems. Recent publications highlight trends in hybrid SNN acceleration, domain-specific accelerator generation, and system-level design space exploration. His research is increasingly focused on neuromorphic computing, automated hardware design, and ultra-efficient architectures using emerging materials like antiferromagnetic tunnel junctions. Scientific Awards: National Science Foundation (NSF) CAREER Award (2019) Elected IEEE Senior Member (2020) Best Paper Award at IEEE ISVLSI (2014) Teaching Award, University of Arizona (2018) ACM GLSVLSI Travel Award (2015) He advises numerous graduate and undergraduate students, many of whom have pursued careers at institutions like Pacific Northwest National Labs, Micron Technology, and Amazon. He has secured significant funding, including a $1.9M NSF FuSE2 grant for energy-efficient computing. His lab collaborates with UA Physics, CMU, and UNL. He has also developed educational tools for Chipyard and RISC-V, supporting hands-on learning in computer architecture. Labs and Research Teams: Leads a research group focused on bio-inspired and domain-specific computing, fostering innovation in energy-efficient hardware. The lab emphasizes hardware/software co-design, neuromorphic engineering, and real-world deployment in IoT and biomedical applications.

Benjamin C.K. Teeمشاهده پروفایل

دانشیار

• Flexible Electronics
• Self-Healing Materials
• Electronic Skin (E-Skin)
• +۴ مورد دیگر

Dr. Benjamin C.K. Tee is an Associate Professor at the National University of Singapore (NUS), affiliated with the College of Engineering and the Department of Materials Science and Engineering. He leads the Sensors.AI Labs, focusing on transforming materials science, mechanics, and biology into cutting-edge technologies for robotics and healthcare in the AI era. His research explores novel materials and fabrication techniques to develop flexible, stretchable electronic sensors. These innovations enable applications in human-machine interfaces, biomedical devices, and AI-driven robotic systems. Key areas include self-healing materials, large-scale tactile sensing, and wireless health monitoring. His work has garnered international acclaim, including the James Dyson Foundation Prize (International Winner, 2021), MIT TR35 Innovator (2015), and recognition as a World Economic Forum Young Scientist (2019). His inventions have been commercialized through co-founded startups Privi Medical (acquired in 2021) and Hannah Life Technologies. Scientific Awards: National Research Foundation Fellowship (2017) MIT TR35 Innovator (Global) (2015) World Economic Forum Young Scientist (2019) James Dyson Foundation Prize - International Winner (2021) IES Prestigious Engineering Award (2020) Stanford University Top 2% Scientists (2021)

Elisa Donatiمشاهده پروفایل

پژوهشگر

• Neuromorphic Engineering
• Biomedical Signal Processing
• Wearable Healthcare Technologies
• +۵ مورد دیگر

Dr. Elisa Donati is a researcher and independent group leader at the Institute of Neuroinformatics , affiliated with both the University of Zurich and the Swiss Federal Institute of Technology Zurich . Her work bridges neuromorphic engineering, biomedical signal processing, and wearable healthcare technologies, with a focus on creating brain-inspired systems for neuroprosthetics and rehabilitation. Affiliation: Institute of Neuroinformatics, University of Zurich & ETH Zurich Email: elisa@ini.uzh.ch Elisa’s research emphasizes developing neuromorphic signal processing strategies for wearable and embedded systems, enabling real-time closed-loop interactions with the nervous system. She specializes in translating neuroscience insights into energy-efficient technologies for digital health applications, including neuroprosthetics and personalized biomedical devices using neuromorphic hardware. Her recent publications (2024–2025) highlight advancements in gesture recognition via EMG and event-based systems, neuromorphic heart rate monitoring , and spiking neural network architectures . These works span biomedical signal processing, low-power computing, and adaptive algorithms, reflecting her commitment to robust, real-time, and brain-inspired solutions for healthcare. Elisa’s contributions to neuromorphic computing are evident in her exploration of heterogeneous population encoding , event-driven processing , and ultra-low-power microcontrollers . Her projects often integrate wearable systems with neuroscience, aiming to improve prosthetic control and rehabilitation technologies .

Lan Weiمشاهده پروفایل

دانشیار

• Nanoelectronic devices
• Cryogenic CMOS electronics
• GaN-based devices and circuits
• +۵ مورد دیگر

Lan Wei is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada. She leads the Waterloo Emerging Integrated Systems Group, focusing on device-circuit co-optimization, cryogenic CMOS for quantum computing, and emerging technologies like GaN, RRAM, and low-dimensional materials. Her work bridges nanoelectronics and system-level applications, with notable contributions to the MIT Virtual Source GaN HEMT (MVSG) compact model, an industry-standard tool. Education: B.S. in Microelectronics and Economics, Peking University (2005) M.S. and Ph.D. in Electrical Engineering, Stanford University (2007, 2010) Research Interests: Nanoelectronic devices Cryogenic CMOS for quantum computing GaN-based circuits and systems RRAM-based neuromorphic computing Device-circuit interactive design Publications reflect her expertise in GaN modeling, quantum computing hardware, and RRAM applications. Recent work emphasizes scalable quantum control circuits and error-resilient neural networks using emerging technologies. Awards include the 2019 Ontario Early Researcher Award and the 2020 UWaterloo President's Excellence Award in Research. She has served on technical committees for IEDM, DATE, and ICCAD, and contributed to the ITRS roadmap. Teaching includes courses like ECE 240 (Electronic Circuits) and ECE 730 (Solid State Devices). Her group actively seeks graduate students with interest in integrated systems and nanoelectronics.

• Microelectronics
• Nanotechnology
• RF Engineering
• +۳ مورد دیگر

Prof. Dr. Amelie Hagelauer holds a professorship in Micro- and Nanosystem Technology at the TUM School of Computation, Information and Technology, Technical University of Munich. Her work focuses on advanced electronics and systems integration across quantum computing hardware, resistive memory technologies, and high-frequency RF systems. She has contributed to innovations in superconducting qubit readout architectures, multi-level RRAM designs, and 3D-integrated CMOS-compatible quantum devices. Research interests span quantum hardware design, nanoelectronic devices, RF front-end systems, and emerging memory technologies. Her work emphasizes practical implementation challenges such as low-power operation, high-voltage handling in RF switches, and wafer-scale fabrication processes. Recent projects include D-band radar systems, energy-efficient 60 GHz transceivers, and antenna tuning solutions for 5G applications. Publications from 2023-2025 showcase advancements in resistive switching device characterization, mitigation of TLS losses in superconducting qubits, and reconfigurable AI accelerators using RRAM-based digital twins. Her work bridges theoretical device physics with practical integrated circuit design, addressing scalability and reliability in next-gen electronics. Awards and grants: None explicitly listed in provided texts. Active collaborations include EU-funded projects on quantum computing platforms and TUM's Electronic Photonic Integration initiatives. Leads research teams in microsystem technology with emphasis on cross-disciplinary approaches combining CMOS processes, MEMS, and quantum engineering.

• Information-Theoretic Security
• Quantum Communication
• Wireless Communication Networks
• +۹ مورد دیگر

Moritz Wiese is a Researcher at the Chair of Theoretical Information Technology within the Department of Electrical and Computer Engineering at Technische Universität München (TUM) . His work focuses on information-theoretic security, quantum communication, and wireless networks, with significant contributions to interference modeling and secure coding schemes. Research Interests : Information-Theoretic Security, Quantum Wiretap Channels, MIMO Systems, 5G/6G Technologies, Physical Layer Security, and Network Coding. Key Grants : Involved in DFG-funded projects (Gottfried Wilhelm Leibniz Prize, UKoloS) and BMBF initiatives (6G-life, QuaDiQua). Collaborations : Worked with Prof. Holger Boche, Christian Deppe, and Rami Ezzine on secure communication and randomness generation. Labs : Active in the ACES Lab and 6G-life research hub, focusing on joint communication/sensing and neuromorphic computing. Publications : Over 20 papers on secure estimation, wiretap channels, and quantum secrecy, including top-tier journals like IEEE Transactions on Information Theory and Journal of Mathematical Physics .

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.

• Memristive Systems
• Neuromorphic Engineering
• Photonics
• +۳ مورد دیگر

Elias Passerini is a Researcher at the Institute of Electromagnetic Fields (IEF), ETH Zürich, part of the Department of Information Technology and Electrical Engineering. His work focuses on memristive devices and their applications in neuromorphic computing, photonics, and nanoelectronics. He completed his doctoral thesis on 'Memristors for Neuromorphic Computing' in 2025, exploring volatility control and synaptic response tuning. His research emphasizes atomic-scale memristive systems, three-terminal architectures, and material innovations like Sn alloying for improved device stability. Key contributions include developing versatile nanoscale memristive switches with gate tuning capabilities and demonstrating metamaterial graphene photodetectors with record-breaking bandwidth. Passerini collaborates with the Center for Single-Atom Electronics and Photonics, advancing low-power neuromorphic hardware and optoelectronic integration. His publications span conferences like MEMRISYS and journals such as ACS Nano and Light: Science & Applications .

Rahul Sarpeshkarمشاهده پروفایل

استاد

• Analog synthetic biology
• Quantum circuit design
• Feedback control systems
• +۶ مورد دیگر

Rahul Sarpeshkar is a Professor of Engineering, Microbiology & Immunology, Physics, and Molecular & Systems Biology at Dartmouth College, holding the Thomas E. Kurtz Professorship and chairing the Neukom Computational Science Cluster. His research bridges analog circuits with quantum physics, synthetic biology, and ultra-low-power systems. BS in Electrical Engineering and Physics from MIT (1995) PhD in Computation and Neural Systems from Caltech (1998) His research focuses on analog synthetic biology , quantum circuit design , and bio-inspired supercomputing , emphasizing noise, thermodynamics, and energy efficiency. He develops cytomorphic chips to model biochemical networks and quantum-inspired circuits for spectrum analysis. Recent work integrates quantum and classical computation for biological simulations, drug cocktail formulation , and ATP energy measurement in living cells. Patents highlight innovations in quantum emulation and medical devices. Scientific awards include: Fellow, National Academy of Inventors (2018) IEEE Fellow (2018) NSF CAREER Award ONR Young Investigator Award Packard Fellow Award Junior Bose Teaching Award, MIT He leads a wet lab for synthetic microbial circuit implementation and a dry lab for quantum and nanoelectronics, mentoring a multidisciplinary team of physicists, bioengineers, and computer scientists.

Deji Akinwandeمشاهده پروفایل

استاد

• 2D Materials
• Nanotechnology
• Flexible Electronics
• +۷ مورد دیگر

Deji Akinwande is a Professor and holds the Cockrell Family Regents Chair in Engineering #8 at The University of Texas at Austin's Chandra Family Department of Electrical and Computer Engineering. He earned his PhD in Electrical Engineering from Stanford University (2009) and an MS in Applied Physics from Case Western Reserve University. His research focuses on 2D materials, nanotechnology, and flexible electronics, with breakthroughs in atomristors, graphene-based biosensors, and wearable electronic tattoos. Key achievements include pioneering work on silicene, being elevated to IEEE Fellow (2021), and receiving the PECASE Award (Obama administration). His lab, the Akinwande Nano Research Group, explores nanoelectronics, bioelectronics, and RF systems for societal applications like health monitoring and 6G communications. Education: PhD, Electrical Engineering, Stanford University, 2009 MS, Applied Physics, Case Western Reserve University Awards: 2021 IEEE Fellow APS Fellow (2017) PECASE Award Moore Inventor Fellowship His research spans neuromorphic computing, flexible sensors, and energy-efficient memory devices. Over 100+ publications highlight his work on graphene, MXenes, and 2D material applications. He co-authored a textbook on carbon nanotubes and graphene (Cambridge University Press, 2011) and serves as an IEEE Distinguished Lecturer and editor for Nature NPJ 2D Materials . Lab and Collaborations: The Akinwande Nano Lab develops scalable 2D electronics, wearable health monitors, and next-gen RF components. Recent grants include NSF CHIPS Act funding and DoD support for 6G switches and neuromorphic hardware.

Horacio Rostro Gonzálezمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Computational Neuroscience
• Neuromorphic Computing
• +۷ مورد دیگر

Horacio Rostro González is an Associate Professor in the Department of Industrial Engineering at IQS School of Engineering, Universitat Ramon Llull (URL), Barcelona, Spain. He is an active researcher with a strong international academic background and current affiliations in both research and teaching. Education: PhD in Control and Signal and Image Processing (2011, INRIA & University of Nice – Sophia Antipolis, France) Master’s in Electrical Engineering (2007, University of Guanajuato, Mexico) Electronic Engineer (2003, National Technological Institute of Mexico) His research interests lie at the intersection of Artificial Intelligence, Computational Neuroscience, Neuromorphic Computing, Embedded Systems, and Robotics. He applies advanced techniques in neural networks, machine learning, and control systems to solve complex engineering problems in robotics, biomedicine, and industrial design. His work emphasizes biomimetic approaches, such as spiking neural networks for robot locomotion and AI-driven analysis of physiological signals like ECG and facial expressions. The recent publications highlight a strong trend in interdisciplinary research, combining AI with photonics, robotics, cardiovascular diagnostics, and emotional recognition in children. His work spans from theoretical algorithm development to practical industrial applications, particularly in additive manufacturing and smart systems. Scientific Projects: Offshore Wind Farms: Data analysis using machine learning and power generation prediction (2023–2024) GEPI: Grup Enginyeria de Productes Industrials (2022–2025) He is actively involved in research grants and collaborative projects, with no mention of formal student advising in the provided text. He is a member of the GEPI (Industrial Products Engineering Group), which focuses on additive manufacturing, reverse engineering, and material characterization. His scientific output is robust, with consistent publication activity from 2005 to 2025, including numerous articles in indexed journals.