جست‌وجوی استاد و پژوهشگر

• Bioelectronics
• Nanotechnology
• CMOS Technology
• +۱۲ مورد دیگر

Sandro Carrara is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he leads the Bio/CMOS Interfaces (BCI) laboratory. He is affiliated with the School of Engineering (STI), the Institute of Electrical Engineering (SCI-STI-SC), and the Integrated Systems Laboratory (LSI). His academic leadership spans teaching, doctoral supervision, and editorial roles in major journals including IEEE Sensors Journal and BioNanoScience. Education: Diploma in Electronics, National Technical Institute of Albenga, Italy Master in Physics, University of Genoa, Italy PhD in Biochemistry and Biophysics, University of Padua, Italy His research focuses on the integration of biological systems with CMOS technology, particularly in the development of nanoscale biosensors for health monitoring. Key areas include memristive biosensors, wearable and implantable sensors, electrochemical detection, and therapeutic drug monitoring. His work bridges electronics, nanotechnology, and biomedicine to enable point-of-care diagnostics and personalized medicine. His recent publications (2023–2025) show a strong trend toward sustainable printed electronics, machine learning for biosensing, in-memory computing for cancer diagnostics, and remote health monitoring. These works appear in high-impact journals such as IEEE Sensors Journal , Nanoscale , and Biosensors and Bioelectronics: X . Scientific Awards: IEEE Fellow (2015) IEEE Sensors Council Technical Achievement Award (2016) Distinguished Lecturer, IEEE Sensors Council (2017) Best Paper Award, IEEE MeMeA Symposium (2020) Multiple Gold and Bronze Leaf Prizes at PRIME and IEEE conferences Best Poster Awards at EMBEC and Nano-Tera meetings He actively advises PhD students and leads research projects involving CMOS-based biosensors, wireless implants, and smart sensor systems. His lab collaborates widely across disciplines and institutions, focusing on real-world applications in oncology, neurology, and environmental health. He has also contributed to the development of battery-free wearable devices, optical power transfer systems, and IoT-enabled telemedicine platforms. Laboratories and Teams: Bio/CMOS Interfaces (BCI) Laboratory, EPFL Integrated Systems Laboratory (LSI), EPFL Collaborations with IEEE Sensors Council and Circuits and Systems Society Editorial leadership in IEEE Sensors Journal and BioNanoScience

Gabriela Hugمشاهده پروفایل

استاد

• Electric Power Systems
• Sustainable Energy
• Control Systems
• +۳ مورد دیگر

Prof. Gabriela Hug is a Full Professor at ETH Zurich's Department of Information Technology and Electrical Engineering, serving as Deputy Head of the Department and Deputy Head of the Power Systems and High Voltage Lab. She leads the Energy Science Center (ESC) and holds adjunct roles at Carnegie Mellon University. Her research focuses on modeling, control, and optimization of electric power systems for sustainable energy transitions. Education: PhD in Information Technology and Electrical Engineering, ETH Zurich (2004–2008) MSc in Information Technology and Electrical Engineering, ETH Zurich (1999–2004) Research Interests: Her work addresses challenges in smart grid integration, renewable energy systems, and advanced control strategies. Key areas include vehicle-to-grid technologies, distribution network optimization, and energy storage system planning. She emphasizes data-driven approaches and collaborative frameworks for grid resilience and flexibility. Key Achievements: Recipient of the 2019 ALEA Award (ETH Zurich) NSF Career Award (2013) IEEE Outstanding Young Engineer Award (2013) Leadership & Roles: Co-Director, NCCR Automation (Swiss National Centre of Competence in Research) Board Chair, Energy Science Center (ESC) Adjunct Faculty, Carnegie Mellon University Labs & Teams: Power Systems Laboratory (ETH Zurich) Energy Science Center (multi-disciplinary research hub)

Giacomo Indiveriمشاهده پروفایل

استاد

• Neuroscience
• Computer Science
• Machine Learning
• +۶ مورد دیگر

Giacomo Indiveri is a dual Professor at the Faculty of Science of the University of Zurich and the Department of Information Technology and Electrical Engineering of ETH Zurich . He serves as the Director of the Institute of Neuroinformatics at both institutions. Indiveri holds an M.Sc. in Electrical Engineering (1992) from the University of Genoa and a Ph.D. in Computer Science (2004) from the same university. Primary Affiliation: University of Zurich (Faculty of Science, Institute of Neuroinformatics) Secondary Affiliation: ETH Zurich (Department of Information Technology and Electrical Engineering) Indiveri's research bridges neuroscience , computer science , and machine learning to develop neuromorphic cognitive systems . His work focuses on spike-based learning , recurrent neural networks , and analog/digital circuit design for real-time sensory-motor systems . He integrates emerging memory technologies into fault-tolerant event-based architectures, enabling brain-inspired computing paradigms in applications like robotics and medical monitoring. His recent publications emphasize neuromorphic hardware for epileptic seizure detection , spiking neural networks in robotic painting , and scalable processors with on-chip learning . These works explore biologically plausible neurons , delay lines , and memory arrays for temporal processing, with applications in healthcare , edge computing , and adaptive control . Scientific Awards & Recognitions: 2021 IEEE Biomedical Circuits and Systems Best Paper Award Senior Member of IEEE Society ERC Fellow with three European Research Council grants Indiveri's group at the Institute of Neuroinformatics develops event-based systems for real-world validation of brain-inspired computing. His work includes multi-core processors , feedback optimizers , and dynamic routing architectures , supported by grants for advancing neuromorphic technologies .

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.

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 .

• Robotics
• Computer Vision
• Sensor Systems
• +۳ مورد دیگر

Dr. Olga Vysotska is a Researcher affiliated with the Professorship for Robotic Systems at ETH Zurich's Department of Mechanical and Process Engineering. Her work focuses on advancing robotic systems through research in sensor-based navigation, SLAM (Simultaneous Localization and Mapping), and autonomous systems. She holds a doctoral degree and is based in Zurich, Switzerland. Her email is olga.vysotska@inf.ethz.ch. Research Interests: Olga's research spans robotics, computer vision, and autonomous navigation. She specializes in LiDAR-based place recognition, SLAM algorithms, and cross-modal localization using 3D scene graphs. Her work addresses challenges such as environmental changes, sensor fusion, and data association in dynamic environments like agriculture and underground exploration. Key themes include robust localization, loop closure detection, and adaptive algorithms for real-world robotic applications. Publications Overview: Olga's recent work emphasizes diffusion-based LiDAR place recognition (2025), 4D spatial-temporal mapping for agricultural robots (2023), and SceneGraphLoc for cross-modal localization (2024). Her research trends highlight innovation in sensor integration, algorithmic robustness, and practical applications in challenging environments. Earlier contributions include exploration of catacombs with mobile robots (2013) and SLAM enhancements using public map data (2017). Grants & Advising: While specific grants or student advisement details are not listed, her active publication record suggests involvement in funded research projects. Her work often collaborates with industry and academic partners to advance robotic autonomy in complex scenarios. Labs/Teams: As part of the Robotic Systems Professorship, she likely contributes to ETH Zurich's robotics labs focused on SLAM, sensor systems, and autonomous navigation. Her projects may intersect with the Department's broader initiatives in mechanical and process engineering.

• Neuromorphic Engineering
• Neural Networks
• Edge Computing
• +۳ مورد دیگر

Shih-Chii Liu holds the rank of Privatdozent (Associate Professor) in the Department of Information Technology and Electrical Engineering at ETH Zürich. He is affiliated with the Institute of Neuroinformatics , a joint institute between the University of Zurich and ETH Zurich. His research focuses on neuromorphic engineering, bio-inspired neural hardware, and edge computing systems, emphasizing energy-efficient algorithms and sensor technologies. Key research areas include neuromorphic sensors for real-time data processing, sparsity-aware neural networks, and adaptive computing architectures for edge devices. His work spans applications such as speech enhancement, wearable health monitoring, and bio-inspired keyword spotting systems. He leads the Sensors Research Group, which develops neuromorphic systems integrating novel sensors, spiking neural networks, and low-power hardware accelerators. Recent projects include the DeltaKWS low-power keyword spotting IC, EFLOP computational cost metrics for spiking networks, and NeuroBench benchmarking frameworks for neuromorphic systems. His contributions emphasize bridging biological neural principles with practical engineering solutions for IoT and embedded systems. Liu teaches courses such as Neuromorphic Engineering I and collaborates on cross-disciplinary projects involving neuroprosthetics, smart wearables, and multimodal sensor fusion. His work is characterized by hardware-software co-design approaches to tackle challenges in real-time, low-latency, and energy-constrained computing environments.

Francesca Rodinoمشاهده پروفایل

پژوهشگر ارشد

• Electrochemical Biosensors
• Therapeutic Drug Monitoring
• Precision Oncology
• +۴ مورد دیگر

Francesca Rodino is a Doctoral Assistant and Research Fellow at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering and the Electrical and Microengineering Institute (IEM). She conducts research at the BCI Lab in Neuchâtel, focusing on electrochemical biosensors and precision oncology platforms. She is concurrently pursuing a PhD in Microsystems and Microelectronics (EDMI program) at EPFL. Education: B.Sc. in Biomedical Engineering, Politecnico di Torino (2019) M.Sc. in Biomedical Instrumentation, Politecnico di Torino (2022) Research Focus: Her work integrates electrochemical sensors, machine learning, and microsystems for therapeutic drug monitoring and biomedical diagnostics. Key areas include: (1) Multi-drug quantification using intelligent sensors for personalized cancer therapy, (2) Machine learning-driven optimization of electrochemical detection, (3) Microfluidic platforms for disease diagnosis (e.g., malaria), and (4) Wearable systems for neural prosthetics. Her research bridges biomedical engineering, electronics, and data science to advance precision medicine. Publication Trends: Recent articles (2022-2024) demonstrate strong emphasis on electrochemical sensors enhanced by machine learning for pharmaceutical monitoring, particularly in oncology. Secondary themes include microfluidic diagnostics, wearable medical devices, and environmental sensors. Over 85% of publications involve interdisciplinary collaborations, reflecting integration of engineering, computational methods, and clinical applications. Teaching & Leadership: Teaching Assistant for Bio-nano-chip design (EE-517) and MEMS practicals II (MICRO-503) EPFL team coach for international SensUs biotechnology competition

Oskari Ville Pakariمشاهده پروفایل

مدرس

• Nuclear Engineering
• Reactor Physics
• Radiation Detection
• +۳ مورد دیگر

Oskari Ville Pakari is a Lecturer at the School of Basic Sciences, École polytechnique fédérale de Lausanne (EPFL), affiliated with both the Institute of Physics (IPHYS) and the Swiss Plasma Center (SPH-ENS). He contributes to teaching and research, particularly in reactor physics and radiation detection. His research focuses on nuclear reactor diagnostics , gamma noise analysis , and neutron spectroscopy . He actively develops mixed reality visualization tools for radiation detection data and participates in the European CORTEX project for reactor monitoring. Selected publications highlight his work in gamma-ray imaging , neutron noise simulations , and detector system validation using advanced statistical methods like bootstrapping and Welch's technique. Teaching activities include courses on Radiation biology, protection, and applications Radiation and reactor experiments He advises PhD student Saliba Michel and collaborates with international institutions such as CEA, KIT, and LRS (Laboratory of Reactor Physics and Systems Behaviour) at EPFL.

Andreas Peter Burgمشاهده پروفایل

دانشیار

• Circuits and systems for telecommunications
• Silicon implementation of communication technologies
• Communication algorithms optimization
• +۵ مورد دیگر

Andreas Peter Burg is a Tenured Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL), where he leads the Telecommunications Circuits Laboratory (TCL) within the School of Engineering. He holds multiple academic and administrative roles at EPFL including Associate Professor in Teaching (SEL, EDMI, EDEE), Director of SEL Management, and Member of the Doctoral Program Committee for Electrical Engineering. Dr. Burg received his Dipl.-Ing. degree in 2000 and Dr. sc. techn. degree in 2006 from ETH Zurich. His academic career includes positions as SNF Assistant Professor at ETH Zurich (2009-2011) before joining EPFL in January 2011 as a Tenure Track Assistant Professor, where he was promoted to Tenured Associate Professor in June 2018. His research focuses on circuits and systems for telecommunications , with particular expertise in silicon implementation of communication technologies, communication algorithms optimization for hardware, low-power VLSI signal processing, and digital integrated circuits. His work bridges theoretical communication concepts with practical circuit implementations, addressing challenges in wireless and wired communication systems. His recent publications (2024-2025) demonstrate a strong focus on next-generation communication technologies including 6G systems, advanced error correction coding, wireless sensing applications, and ultra-low power circuit design. These works span multiple subfields from LDPC and polar code decoding to RF signal processing and machine learning applications in wireless systems. Willi Studer Award (2000) ETH Medal for diploma thesis (2000) ETH Medal for Ph.D. dissertation (2006) Swiss National Science Foundation Assistant Professorship grant (2008) Dr. Burg has been involved in the development of more than 25 ASICs throughout his career and co-founded Celestrius, an ETH spinoff in MIMO wireless communication. His laboratory work focuses on practical implementations of communication algorithms with emphasis on power efficiency and hardware optimization. Current research directions include 6G technologies, wireless sensing applications, and novel error correction techniques for next-generation communication systems.

Christoph Leitnerمشاهده پروفایل

پژوهشگر ارشد

• Convergent Technologies
• Ultrasonics
• Machine Learning
• +۳ مورد دیگر

Dr. Christoph Leitner is a Research Fellow at ETH Zurich's Integrated Systems Laboratory under Prof. Luca Benini, focusing on biomedical and IoT applications. His work integrates printed piezoelectric transducers and flexible electronics with energy-efficient systems. He holds a PhD in Biomedical Engineering from TU Graz (2022) and has collaborated with institutions like Sant'Anna School of Advanced Studies and KTH Stockholm. Notable achievements include the Josef Krainer Young Researcher Award and Motorik Scholarship. Leitner's research spans ultrasonics, machine learning, and wearable devices, with contributions to muscle-tendon dynamics and real-time biofeedback systems. Education: PhD in Biomedical Engineering, TU Graz (2022), Advisor: Prof. Christian Baumgartner Previous roles: University Assistant (2006–2011) and R&D Engineer at Virtual Vehicle GmbH Research Interests: Convergent technologies merging biomedical engineering and IoT Ultrasound-based monitoring for musculoskeletal systems Energy-efficient embedded systems for wearable applications Collaborations & Awards: Recipient of Josef Krainer Young Researcher Award (2023) and Motorik Scholarship (2018) Active collaborations with University of Zurich, Veterinary University of Vienna, and Queensland University of Technology Labs & Projects: Integrated Systems Laboratory at ETH Zurich Developed a patented ultrasound-transparent tattoo-based SEMG system with Prof. Francesco Greco

• Logic Synthesis
• Digital Circuit Design
• Machine Learning
• +۳ مورد دیگر

Andrea Costamagna is a researcher affiliated with the École Polytechnique Fédérale de Lausanne (EPFL), working within the School of Computer and Communication Sciences and the Department of Communication Systems. His research focuses on logic synthesis, digital circuit design, and the intersection of machine learning with hardware implementation. His work includes optimizing digital circuits using techniques like resynthesis, resubstitution, and decomposition, with applications in FPGA design and low-power systems. Recent publications explore symmetry-based synthesis, glitch-aware power minimization, and the use of resistive switching devices in machine learning hardware. His research also extends to quantum physics modeling with deep learning.

Saqib Javedمشاهده پروفایل

پژوهشگر

• Computer Vision
• Deep Learning
• Efficient Neural Networks
• +۴ مورد دیگر

Saqib Javed is a doctoral researcher and Researcher at the Computer Vision Laboratory (CVLab) at EPFL, supervised by Prof. Pascal Fua and Dr. Mathieu Salzmann. His research focuses on energy-efficient deep networks, 3D reconstruction, quantization-aware training, and domain generalization. He holds a master’s degree from TU Munich and ETH Zurich. He is affiliated with the School of Computer and Communication Sciences (IC) and the Department of Computer Science at EPFL. His current projects include compressed Gaussian splatting for dynamic scenes, quantized diffusion models, and reducing inference time for vision-language models. He has been awarded the EPFL IC Distinguished Service Award and is a Global Leaders PhD Fellow. His work spans theoretical research and practical applications in low-power device optimization. Teaching roles include serving as a Teaching Assistant for courses like Introduction to Machine Learning (CS-233) and Probability and Statistics (MATH-232). He has supervised multiple students, including Chengkun Li and Ahmad Jarrar Khan, on projects related to quantization and 3D pose estimation. His research also involves collaborations with industry partners like BMW, Siemens, and Intel, focusing on hardware-friendly neural networks. Awards include the EPFL IC Distinguished Service Award (2024) and recognition for his contributions to efficient deep learning. His recent publications address domain generalization, Gaussian splatting, and modular quantization techniques, reflecting his interdisciplinary approach to advancing machine learning efficiency and applicability.

• Natural and Artificial Lighting
• Solar Energy (Passive and Active)
• Building Technology
• +۳ مورد دیگر

Jean-Louis Scartezzini is an Honorary Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Architecture, Civil and Environmental Engineering (ENAC) and the Solar Energy and Building Physics Laboratory (LESO-PB). His research focuses on natural/artificial lighting, solar energy systems, and building technology, with a strong emphasis on energy efficiency and sustainability. Director of LESO-PB since 1994 Founded and led several institutes, including the Institute for Infrastructure, Resources, and Environment (2002–2009) Doctorat in Physics from EPFL (1986) Extensive international collaborations, including visiting roles at NUS (2009) and LBNL/UCLA (1988) Research interests include: - Daylighting and lighting control systems - Passive/active solar technologies - Urban microclimate and energy systems - Stochastic simulation and predictive control Recent work addresses climate change impacts on energy systems, urban sustainability, and machine learning applications in energy optimization. Key publications span lighting health impacts, renewable integration, and microclimate modeling Awards include the European Solar Prize (2001/2002) and Walsh-Weston Bronze Medal (1998) Mentored over 20 PhD students, many leading in academia and industry (e.g., Marilyne Andersen at EPFL, Flavio Foradini at E4Tech).

Pasquale Davide Schiavoneمشاهده پروفایل

مدرس

• Embedded Systems
• RISC-V Architecture
• Ultra-low-power Computing
• +۵ مورد دیگر

Pasquale Davide Schiavone holds multiple research and teaching positions at École Polytechnique Fédérale de Lausanne (EPFL), serving as a Lecturer at the School of Computer and Communication Sciences (IC) and as a Scientist at both the Embedded Systems Laboratory (ESL) within the School of Engineering (STI) and PAT Administration. His interdisciplinary work bridges computer architecture, embedded systems design, and biomedical applications, with office located at ELG 136 in Lausanne, Switzerland. Dr. Schiavone's research focuses on ultra-low-power computing systems, particularly RISC-V architectures and TinyML applications for edge devices. His work develops open-source hardware platforms like X-HEEP and HEEPOCRATES that enable energy-efficient AI at the edge, with applications spanning biomedical monitoring, neural interfaces, and wearable computing. He explores innovative hardware-software co-design approaches to overcome energy constraints in resource-limited environments. His recent publications reveal a consistent research trajectory centered on open, configurable computing platforms for specialized applications. The work spans from fundamental RISC-V architecture improvements (ARCANE, e-GPU) to application-specific implementations for biomedical contexts (BiomedBench, neural interfaces). A strong emphasis on energy efficiency permeates all his research, whether through novel arithmetic approaches (Posit), system architecture (near-memory computing), or specialized accelerators (Strela, Quadrilatero). Lecturer, School of Computer and Communication Sciences (IC) Scientist, Embedded Systems Laboratory (ESL), School of Engineering (STI) Scientist, PAT Administration, School of Engineering (STI) Dr. Schiavone teaches courses on hardware compilation, presenting algorithms and methods for transforming hardware description languages into optimized circuit implementations. His Embedded Systems Laboratory work places him at the forefront of developing practical, open-source solutions for next-generation computing challenges in energy-constrained environments.