Find Academic Supervisors

• Bioelectronics
• Nanotechnology
• CMOS Technology
• +12 more

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

Giovanni De MicheliView profile

Professor

• Integrated Circuit Design
• Hardware Synthesis
• Logic Optimization
• +5 more

Giovanni De Micheli is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), holding appointments in both the School of Computer and Communication Sciences (IC) and the School of Engineering (STI). He is affiliated with the Integrated Systems Laboratory (LSI) and serves as Scientific Director of EcoCloud. His primary office is located in INF 341 building at EPFL's Lausanne campus where he conducts research and teaching activities. Professor De Micheli's research spans multiple domains in electronic design automation and integrated circuit design. His primary interests include: Integrated Circuit Design and Hardware Synthesis Logic Optimization and Boolean Methods Nanoelectronics and 2D Electronics Quantum Computing and Emerging Technologies Low-Power Electronics and Energy-Efficient Systems Electronic Design Automation for Novel Computing Paradigms His recent publications demonstrate a strong focus on advancing logic synthesis techniques for both conventional and emerging technologies. Professor De Micheli's work bridges theoretical foundations with practical applications, particularly in adapting traditional EDA methods to novel computing paradigms like quantum computing and superconducting electronics. His research group has made significant contributions to the development of efficient algorithms for circuit optimization across multiple technology domains, with particular emphasis on area, power, and delay optimization while maintaining functional correctness. Professor De Micheli has supervised numerous doctoral students throughout his career at EPFL, mentoring over 40 PhD candidates whose research spans various aspects of electronic design automation, circuit design, and emerging technologies. His students have gone on to make significant contributions in both academia and industry. As Scientific Director of EcoCloud, Professor De Micheli leads research initiatives focused on energy-efficient computing systems and sustainable cloud infrastructure. His laboratory, the Integrated Systems Laboratory, serves as a hub for interdisciplinary research connecting computer science, electrical engineering, and materials science, with particular focus on next-generation computing technologies.

Giacomo IndiveriView profile

Professor

• Neuroscience
• Computer Science
• Machine Learning
• +6 more

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 .

Elison MatioliView profile

Professor

• Power Electronics
• Semiconductor Devices
• Nanotechnology
• +3 more

Elison Matioli is a Professor at the Institute of Electrical Engineering (STI) at EPFL and director of the POWERlab. He holds a B.Sc. in Applied Physics and Applied Mathematics from Ecole Polytechnique (France), a B.Sc. in Electrical Engineering from the University of São Paulo (Brazil), and a Ph.D. in Materials Science from the University of California, Santa Barbara. His postdoctoral research at MIT focused on electrical engineering and computer science. His research centers on advanced semiconductor devices, particularly GaN-based power electronics, microfluidic cooling systems, and nanotechnology innovations for high-power applications. Key areas include developing high-efficiency GaN transistors, optimizing power conversion systems, and exploring terahertz generation through nanoplasma switches. His work emphasizes integrating novel materials (e.g., diamond, LiNiO) and cooling solutions to enhance device performance and reliability. Publications highlight breakthroughs in GaN power devices, microfluidic integration for thermal management, and ultrafast switching technologies. His contributions span device physics, fabrication techniques, and energy-efficient systems, with applications in next-generation power electronics and renewable energy infrastructure.

Tobi DelbruckView profile

Professor

• Neuromorphic Engineering
• Event-Based Vision Systems
• Silicon Retinas
• +6 more

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 DonatiView profile

Researcher

• Neuromorphic Engineering
• Biomedical Signal Processing
• Wearable Healthcare Technologies
• +5 more

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 .

• Memristive Systems
• Neuromorphic Engineering
• Photonics
• +3 more

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 .

Kirsten Emilie MoselundView profile

Professor

• Semiconductor Devices
• Quantum Computing
• Integrated Photonics
• +3 more

Kirsten Emilie Moselund is a Full Professor of Electrical and Microengineering at École Polytechnique Fédérale de Lausanne (EPFL) and Head of the Laboratory of Nano and Quantum Technologies (LNQ) at Paul Scherrer Institut (PSI) since 2022. She bridges quantum and classical technologies through interdisciplinary research collaborations across the ETH domain. Her leadership spans multiple groups in quantum computing and nanotechnology, including the ETHZ-PSI Quantum Computing Hub. Education: M.Sc. in Engineering (2003) and Ph.D. in Microelectronics (2008), both from EPFL and Technical University of Denmark (DTU) Her research focuses on semiconductor device innovation, including low-power electronics , cryogenic electronics , and integrated photonics , with an emphasis on III-V on silicon monolithic integration for hybrid quantum-classical systems. Key subfields include topological devices , nanophotonics , and neuromorphic computing . Recent publications highlight advancements in III-V photonic integration , nanoscale lasers , and optoelectronic device physics , reflecting her expertise in bridging materials science with quantum engineering. Notably, her work on hybrid photonic-plasmonic nanolasers earned an ERC Starting Grant . As an academic leader, Moselund has directed multiple Ph.D. theses and contributed to over 100 publications with 25 patents filed. She serves on technical committees for major conferences like IEDM and participates in European and Swiss research initiatives. Labs & Teams: Lead the LNQ laboratory at PSI with six research groups Professional Memberships: Wissenschaftliche Beirat of IHP Microelectronics, Kuratorium IMS Chips

Christian EnzView profile

Professor

• Very low-power analog circuit design
• RF IC design
• Semiconductor device modeling
• +4 more

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.

Kyojin ChooView profile

Assistant Professor

• Charge-domain circuits
• Sensor interfaces
• Energy converters
• +4 more

Kyojin Choo is a Tenure Track Assistant Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) in the School of Engineering , affiliated with the Mixed-Signal Integrated Circuits Lab (MSIC-LAB). He also holds teaching roles in Microengineering and Electrical and Electronics Engineering at EPFL. B.S. and M.S. in Electrical Engineering from Seoul National University (2007, 2009) Ph.D. in Electrical Engineering from the University of Michigan (2018) His research focuses on charge-domain analog/mixed-signal circuits , low-power sensor interfaces , and compact ADCs for IoT, wearables, and millimeter-scale systems. He has pioneered charge-injection cell techniques for energy-efficient circuits in energy management, sensor front-ends, and communication. His work emphasizes reducing power consumption to nanowatt levels while enabling ultra-compact designs. His recent publications highlight advancements in compact SAR ADCs , low-power MEMS accelerometers , millimeter-scale imaging systems , and ultra-low-power timing generators . His research integrates charge-domain circuit design with sensor interface optimization , energy harvesting , and high-speed link architectures . He holds over 20 US patents and has taught courses in Microengineering and Electrical Engineering at EPFL. His group (MSIC-LAB) addresses challenges in battery-free sensor design, power-constrained system scaling, and commercialization of wearables with unconventional form factors.

Alessandro OttavianoView profile

Researcher

• Computer Architecture
• Embedded Systems
• Real-Time Systems
• +3 more

Dr. Alessandro Ottaviano is a Researcher affiliated with the Department of Digital Integrated Circuits and Systems at ETH Zürich. His work focuses on advanced computer architecture and embedded systems, particularly in the domains of RISC-V processors, real-time systems, and heterogeneous computing. He contributes to the design of time-predictable virtual memory solutions, mixed-criticality systems, and energy-efficient hardware-software interfaces. Key research areas include modular processor architectures, hardware monitoring for safety-critical applications, and power management in high-performance computing (HPC) systems. His recent projects involve developing controllers for 2.5D systems-in-package and creating open-source networking solutions for mixed-criticality environments. Ottaviano’s work often emphasizes open-source hardware design and scalable system-level approaches to address challenges in autonomous systems and edge computing. He collaborates on advancements in interrupt handling for virtualized systems, peripheral event linking for IoT devices, and FPGA-based thermal emulation for many-core processors. His research bridges theoretical computer architecture principles with practical implementations in embedded and real-time systems.

• Robotics
• Computer Vision
• Sensor Systems
• +3 more

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.

Ivan PudduView profile

Researcher

• Information Security
• Cybersecurity
• Computer Science
• +3 more

Dr. Ivan Puddu is a Researcher affiliated with the Institute for Information Security at ETH Zürich. His work focuses on advancing cybersecurity, particularly in the realms of Trusted Execution Environments (TEEs), hardware security, and privacy-preserving technologies. He explores vulnerabilities in modern computing systems, including attacks on enclave-based security mechanisms and side-channel exploits. His research also addresses distributed systems, blockchain, and FPGA-accelerated architectures, aiming to enhance system sovereignty and data integrity. Notable contributions include studies on code confidentiality in TEEs, disaggregated memory systems, and mitigating security threats in low-power networks.

• Neuromorphic Engineering
• Neural Networks
• Edge Computing
• +3 more

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 RodinoView profile

Research Fellow

• Electrochemical Biosensors
• Therapeutic Drug Monitoring
• Precision Oncology
• +4 more

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