جست‌وجوی استاد و پژوهشگر

• Embedded Systems
• AI Algorithms
• FPGA/VHDL Design
• +۵ مورد دیگر

Jürgen Wassner is a Professor of Edge Computing and Co-Head of the Competence Center for Intelligent Sensors and Networks at the Lucerne School of Engineering and Architecture (HSLU T&A). He holds a master's degree from Technical University of Dresden and a PhD from ETH Zurich. His career spans industry roles in Silicon Valley Group Inc. and telecommunication R&D before joining academia in 2007. His research focuses on embedded systems, AI at the edge, FPGA/VHDL design, real-time systems, and powerline communication . He leads projects such as 'Visual-Servoing Testbed with AI-Hardware in the Loop' and 'Low-Cost High-Performance Intelligent Camera for Space Debris Mitigation,' collaborating with companies like Diehl Aerospace. Recent publications emphasize wire fault detection using powerline communication, AI-based odor classification systems, and hardware acceleration for CNNs. His work bridges theoretical research with practical applications in avionics, rail freight, and space debris mitigation. Wassner advises Master of Science in Engineering students and has been recognized for his media engagement including a feature in the Luzerner Zeitung. He teaches Digital Design (FPGA, VHDL) and Digital Signal Processing , emphasizing hands-on implementation of cutting-edge systems.

Tommaso Dorigoمشاهده پروفایل

استاد

• Particle Physics
• High Energy Physics
• Statistics
• +۴ مورد دیگر

Tommaso Dorigo is a Professor at the University of Padova, affiliated with the Department of Physics and Astronomy 'G. Galilei'. He serves as First Researcher at INFN-Padova and contributes to international collaborations including CMS, CDF, MODE, DarkMachines, and SWGO. His roles span research, teaching, and leadership in interdisciplinary initiatives. 2022-2025: President of USERN Organization 2020-Present: Coordinator of MODE Collaboration 2014-2019: Scientific Coordinator of AMVA4NewPhysics ETN 2016-2020: Board member of INFN CSN1 Research Interests: His work bridges Particle Physics (Higgs boson physics, top quark studies, new physics searches) and Statistics (parameter estimation, frequentist methods, nuisance parameters). In Computer Science , he develops machine learning tools for detector optimization, anomaly detection, and differentiable programming. Recent articles focus on end-to-end detector design, extended Higgs models, and systematic uncertainty-aware neural networks. Scientific Contributions: He has authored over 1600 publications (H-index 223) and pioneered algorithms like MuScleFit, INVERSE BAGGING, and INFERNO. His outreach includes a popular science blog with 15M+ visits and books like Anomaly! Collider Physics and the Quest for New Phenomena at Fermilab . Grants: Marie Curie ITN grants (AMVA4NewPhysics 2015; INSIGHTS 2017) Editorial: Editor for Elsevier journals Reviews in Physics and Physics Open Advising: Supervised 44 undergraduate/masters students and 11 PhD students Labs/Teams: Member of CMS experiment (CERN), former CDF (Fermilab), and leader of MODE collaboration

Giorgio Cristianoمشاهده پروفایل

پژوهشگر

• Circuit Design
• Low-Power Electronics
• Biomedical Electronics
• +۶ مورد دیگر

Giorgio Cristiano is a Post-Doctoral Researcher at ETH Zürich in the Department of Information Technology and Electrical Engineering , affiliated with the Integrated Systems Laboratory . His work focuses on advanced circuit design for Internet of Things (IoT) applications and In-Memory Computing , with a strong emphasis on low-power and CMOS-compatible solutions. His research spans key areas such as: Temperature-stable RC oscillators for IoT nodes High-efficiency DC-DC converters using electromagnetically coupled oscillators Neural recording interface circuits with miniaturized resistors MEMS oscillators for ultra-low power consumption The trends in his publications highlight innovations in energy efficiency (e.g., 1.5pJ/Cycle oscillators), noise reduction (0.4 NEF amplifiers), and biomedical electronics integration. His work often addresses miniaturization and power optimization for wearable and implantable devices. Key institutions involved in his research include: ETH Zürich (primary affiliation) Integrated Systems Laboratory (research group) Collaborations with experts in biomedical engineering and neural networks

Andrea Morandiمشاهده پروفایل

مدرس

• Quantum Electronics
• Nonlinear Optics
• Photonic Computing
• +۳ مورد دیگر

Dr. Andrea Morandi is a Lecturer in the Department of Physics at ETH Zürich, affiliated with the Institut für Quantenelektronik. His research focuses on quantum electronics, nonlinear optics, and photonic computing, with a particular emphasis on nanomaterials for photonic devices. His work explores applications in biofabrication, quantum photonics, and scalable optical systems. Key research interests include structured light projection, nonlinear photonic computing platforms, and the development of disordered media for novel optical phenomena. His contributions span theoretical and experimental studies in lithium niobate microstructures, GaAs nanowires, and nanoparticle assemblies, advancing the field of quantum optics and integrated photonics. Publications highlight advancements in parametric down-conversion, multiple scattering models, and photonic networks. Morandi collaborates on projects addressing biofabrication and neuromorphic computing, leveraging interdisciplinary approaches to solve complex optical challenges.

Mathieu Luisierمشاهده پروفایل

استاد

• Computational Nanoelectronics
• Device Physics
• Quantum Transport
• +۷ مورد دیگر

Prof. Mathieu Luisier is a Full Professor of Computational Nanoelectronics at ETH Zurich's Department of Information Technology and Electrical Engineering. He earned his PhD in 2007 from ETH Zurich, followed by postdoctoral research there and a role as Research Assistant Professor at Purdue University (2008–2011). His research focuses on nanoscale device modeling, including nanowire transistors, memristors, and 2D semiconductors, with a strong emphasis on quantum transport and high-performance computing. ERC Starting Grant (2013) SNSF Advanced Grant (2022) ACM Gordon Bell Prize (2019) His work integrates advanced simulation techniques like GW approximations and parallel algorithms to address challenges in nanoelectronics. He teaches courses on digital circuits and integrated systems, and leads research groups exploring next-generation devices for applications in quantum computing and neuromorphic systems.

• Materials Science
• Renewable Energy
• Inorganic Chemistry
• +۵ مورد دیگر

Dr. Sergey Tsarev is a researcher at the Laboratory of Inorganic Chemistry (LAC) at ETH Zürich, focusing on functional inorganic materials for photovoltaic and environmental applications. His work spans perovskite solar cells, uranium remediation, and advanced material stability studies. Key Research Themes: Stability engineering in perovskite photovoltaics, interface management in solar devices, and redox chemistry in uranium reduction processes. Recent Publications: His 2025–2020 studies highlight innovations in CMOS-compatible photodetectors, mixed-halide perovskite degradation mechanisms, and sustainable electrode materials. Technical Expertise: Specializes in thin-film deposition, surface passivation, and redox-active material synthesis.

Alexandre Sébastien Julien Levisseمشاهده پروفایل

مدرس

• Computer Architecture
• VLSI Design
• Low-Power Electronics
• +۴ مورد دیگر

Alexandre Sébastien Julien Levisse is a Lecturer at the Institute of Electrical Engineering within EPFL's School of Engineering, with additional roles as System Specialist in PAT/SEL departments and Scientist in IEM. His work centers on energy-efficient hardware architectures for edge computing and AI applications. Research focuses on: Computer Architecture & VLSI Design Low-Power Electronics for edge devices Emerging Memory Technologies (RRAM, OxRAM) Neuromorphic & Approximate Computing In-Memory/ Near-Memory Computing Edge AI Hardware Acceleration His 2022-2025 publications reveal strong emphasis on specialized edge AI hardware, including near-DRAM architectures (SideDRAM), RISC-V microcontrollers for healthcare (HEEPOcrates), and overflow-free memory systems. Key innovations involve hardware-software co-design for energy efficiency, variable precision computation, and novel memory hierarchies targeting wearable sensors and edge inference. Levisse teaches Fundamentals of VLSI Design and Lab in Advanced VLSI Design at EPFL. He actively contributes to digital education as a member of EPFL's Centre for Digital Education (CCE), developing curricula for next-generation hardware engineers.

Adrian M. Ionescuمشاهده پروفایل

استاد

• Nanoelectronic devices
• Nanotechnology
• Steep-slope tunnel FETs
• +۷ مورد دیگر

Adrian M. Ionescu is a Full Professor at the Department of Electrical Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL). He directs the Nanoelectronic Devices Laboratory (Nanolab) and contributes to the Doctoral Program in Microsystems and Microelectronics. His research bridges nanoelectronics, quantum computing, and biomedical sensing. B.S./M.S. in Electronics, Politehnica University Bucharest Ph.D. in Microelectronics, Politehnica University Bucharest Ph.D. in Physics of Semiconductor Devices, INPG Grenoble Research spans energy-efficient nanoelectronics , steep-slope switches , quantum computing qubits , edge AI sensors , and lab-on-skin wearable systems . Key projects include ERC Advanced Grant Milli-Tech for millivolt technology, DIGIPREDICT for digital twins in healthcare, and Sinergia NeMO for memristors. Recent publications focus on 2025 VO 2 phase-change devices, 2024 graphene biosensors, and 2023 III-V tunnel FETs. Awards include the 2024 IEEE Cledo Brunetti Award , 2017 IEEE George Smith Award , and IBM Faculty Award (2013) . As EPFL doctoral program director, he has guided 10+ PhD students in biosensing, ferroelectric FETs, and neuromorphic systems.

Melika Payvandمشاهده پروفایل

استادیار

• Neuroinformatics
• Artificial Intelligence
• Neuromorphic Computing
• +۵ مورد دیگر

Melika Payvand is an Assistant Professor at the Institute of Neuroinformatics, University of Zurich and ETH Zurich, leading the Emerging Intelligent Substrates lab. She holds MSc and PhD degrees in Electrical and Computer Engineering from the University of California, Santa Barbara (2012 and 2016). Her research focuses on understanding natural intelligence and translating its principles into efficient artificial intelligence systems, particularly exploring hierarchical structures and memristive devices to reduce AI operational costs. She received the 2023 Swiss National Science Foundation Starting Grant and is actively involved in neuromorphic initiatives, including co-coordinating the NEUROTECH project and co-chairing the International Conference on Neuromorphic Systems (ICONS). Her work bridges neuroscience and engineering, emphasizing neuromorphic computing’s potential for scalable and energy-efficient AI. Key contributions include developing the Neurobench benchmarking framework and advancing 3D integration for neuromorphic systems. She also chairs the Neural Systems and Applications committee of the IEEE Circuits and Systems Society, reflecting her leadership in the field. Research interests span neuromorphic architectures, memristive technologies, and spiking neural networks. She has pioneered studies on temporal hierarchy, in-memory computing, and hardware-aware training methods. Her lab’s interdisciplinary approach integrates circuit design, machine learning, and neurobiology to create next-generation intelligent systems.

Philip Garnerمشاهده پروفایل

مدرس

• Speech Recognition
• Spiking Neural Networks
• Neuromorphic Computing
• +۷ مورد دیگر

Philip Garner is a Lecturer at the Laboratory for Intelligent Data Analysis and Processing (LIDIAP), part of the School of Engineering (STI) at École Polytechnique Fédérale de Lausanne (EPFL). He is affiliated with the Institute of Electrical Engineering (IEM) and conducts research in intelligent data analysis, with a focus on biologically inspired neural models for speech and cognitive processing. Despite holding a 'Guest' status, he actively supervises PhD students and co-directs doctoral research, indicating a significant academic role. His research interests lie at the intersection of neuroscience and machine learning, particularly in spiking neural networks , speech recognition , neuromorphic computing , and deep learning architectures . He investigates how biologically plausible models can replicate brain-like computation for efficient information processing. His work often explores temporal dynamics, recurrence, memory mechanisms, and neural oscillations in artificial systems. The publications associated with his advisees and research group reflect a strong trend in developing energy-efficient, brain-inspired computing models for sequential data processing. These works frequently involve surrogate gradient learning, Bayesian recurrent units, and analysis of cross-frequency coupling in neural networks, contributing to both cognitive science and practical applications in speech technology. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: Philip Garner supervises multiple doctoral students, including Abdennadher Yesmine, Chen Haolin, Coppieters De Gibson Louise Clothilde, He Mutian, and has co-supervised several completed theses such as those of Bittar Alexandre, Honnet Pierre-Edouard, Schnell Bastian, Taghizadeh Mohammadjavad, and Tong Sibo. His advising role is central to the LIDIAP lab’s research output in neural computation. While specific grants are not listed, his involvement in cutting-edge AI and neuroscience research suggests active participation in funded projects. Labs and Teams: He is based at the IDIAP Research Institute, closely affiliated with EPFL’s LIDIAP laboratory, which specializes in intelligent data analysis and processing. The lab fosters interdisciplinary research in machine learning, signal processing, and cognitive modeling, often in collaboration with neuroscience and engineering groups.

Andrei Atanovمشاهده پروفایل

پژوهشگر

• Computer Vision
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Andrei Atanov is a Researcher at the Laboratoire d'intelligence et d'apprentissage visuels (VILAB) within the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL) . His research focuses on advanced topics in artificial intelligence, computer vision, and machine learning, with particular emphasis on multimodal learning, vision-language models, and robust generalization. He is affiliated with the Department of Computer Science and contributes to projects exploring innovative solutions for vision tasks using computationally designed sensors and diffusion models. His work often bridges theoretical advancements with practical applications in robotics and generative systems. Key research areas include developing large vision-language models, optimizing vision algorithms for low-sensor environments, and enhancing model robustness through diversification strategies. His publications span topics from 3D data augmentation to uncertainty estimation in deep learning, reflecting a broad yet technically deep expertise in AI fundamentals and applications.

• Embedded Systems
• Internet of Things (IoT)
• Smart Mobility
• +۶ مورد دیگر

Vannel Fabien is a Full Professor at the Haute école du paysage, d'ingénierie et d'architecture de Genève (HEPIA), part of the HES-SO University of Applied Sciences and Arts. He is affiliated with the Technical and IT School and the Department of Computer Science and Communication Systems. His research focuses on embedded systems, IoT, FPGA-based architectures, neuromorphic computing, and quantum communication technologies. Education: PhD in Bio-inspired Computing (2007), École Polytechnique Fédérale de Lausanne (EPFL), supervised by Daniel Mange Research Interests: Development of self-organizing neuromorphic hardware architectures (SOMA project) High-performance FPGA-based platforms for IoT security and random number generation Cellular computing inspired by biological systems 3D Network-on-Chip (NoC) architectures and dynamic resource allocation Quantum key distribution (QKD) systems for secure communication His work combines hardware design with bio-inspired algorithms, aiming to create adaptive, energy-efficient computing systems. Recent projects include SCALPsim (a 3D NoC modeling tool) and FPGA-based validation platforms for TRNGs. Grants & Projects: Principal investigator for SOMA (2018-2021, SNSF-funded CHF 461,238) Co-applicant for iNUIT-2014 ArchSensor (2014-2015, HES-SO-funded CHF 220,000) Contributor to heterogeneous computing platforms (AcceleRation, 2013-2014) Labs & Teams: Lead researcher in the SOMA team at HES-SO, collaborating with institutions like Université de Nice and INRIA.

Alexandros Emborasمشاهده پروفایل

مدرس

• Memristive Devices
• Nanophotonics
• Plasmonics
• +۳ مورد دیگر

PD Dr. Alexandros Emboras is a senior scientist and lecturer at ETH Zurich's Department of Information Technology and Electrical Engineering, leading the center for Single Atom Electronics and Photonics funded by Werner Siemens Stiftung. His research focuses on memristive devices, neuromorphic engineering, and nanoscale photonics. He holds a PhD from CEA-LETI Grenoble (2012) and postdoctoral experience at Hebrew University (2013). Education: PhD in Electrical Engineering, CEA-LETI Grenoble (2012) Postdoctoral Research, Hebrew University of Jerusalem (2013) His research explores atomic-scale memristors, plasmonic devices, and their applications in neuromorphic computing and high-speed communications. Key contributions include photonic-electronic hybrid systems, resistive switching mechanisms in complex oxides, and energy-efficient neuromorphic architectures. Recent work emphasizes memristive photon sources and bio-inspired electronic systems leveraging oxide dynamics. Publications span advanced topics like gate-enabled memristive switches, inkjet-printed phase change memories, and in-situ reinforcement learning with analog memristors. His work bridges nanotechnology and practical applications in computing and communication systems. Labs/Teams: Coordinates the Werner Siemens Stiftung-funded center for Single Atom Electronics and Photonics at ETH Zurich.

Andrea Censiمشاهده پروفایل

مدرس

• Autonomous Driving
• Robotics
• Control Systems
• +۳ مورد دیگر

Dr. Andrea Censi is a Lecturer at the Department of Mechanical and Process Engineering, ETH Zurich. His research focuses on robotics, autonomous driving, and control systems with interdisciplinary applications in game theory and urban mobility. Key projects include karma economies for resource allocation and co-design frameworks for embodied intelligence. Research interests span: Autonomous motion planning and decision making Trustworthy AI for socio-technical systems Karma-based congestion management Co-design of robotic control systems Event-based vision and neuromorphic sensing Formal methods for autonomous vehicle safety Selected research trends from publications include: karma economies for fair resource allocation (2024-2025), co-design of perception and decision-making systems (2025), dynamic population games (2024), and safety margin analysis for autonomous vehicles (2023). He teaches 151-0323-00L Hands-on Self-Driving Cars with Duckietown , an accessible education platform for autonomy research.

• Quantum Computing
• Nanoscience
• Nanotechnology
• +۷ مورد دیگر

Heike Riel is an IBM Fellow and the Head of Science of Quantum and Information Technology at IBM Research. She also holds the Rudolf Diesel Industry Fellowship at the Institute for Advanced Study (TUM-IAS), Technical University of Munich (TUM). Her work focuses on advancing quantum computing, nanoscale electronics, and neuromorphic devices through materials science innovations. She earned a PhD in Physics from the University of Bayreuth (2003) for research on organic light-emitting diodes (OLEDs) at IBM Research, following an MBA from Henley Business School (2010) and an internship at Hewlett-Packard Research Lab. Her career at IBM began in 1998, progressing to leadership roles in nanowire and quantum device research. Her research spans semiconducting nanowires, hybrid quantum systems, and spintronic devices, with recent publications emphasizing quantum dots, Josephson junctions, and epitaxial growth techniques. She has authored over 140 peer-reviewed papers and filed more than 50 patents, reflecting her technical impact. Scientific honors include: 2013 IBM Fellow (IBM's highest technical distinction) 2017 David Adler Lectureship Award (Materials Physics) 2020 American Physical Society (APS) Fellow 2015 Honorary Doctorate from Lund University 2012 SVIN Innovation Award Heike serves on advisory boards for Forschungszentrum Jülich and the National Metrology Institute of Germany (PTB), while leading quantum research initiatives across Europe. She is a life member of the Schweizerischen Akademie der Technischen Wissenschaften (SATW) and the German National Academy of Sciences Leopoldina.