جستجوی استاد راهنمای دانشگاهی

Xiao Zhouمشاهده پروفایل

پژوهشگر ارشد

• Consumer Behavior
• Marketing Research
• Behavioral Economics
• +۳ مورد دیگر

Dr. Xiao Zhou is a Research Fellow affiliated with the Professorship for Consumer Behavior at ETH Zurich. His current position began in 2021. Prior to this, he conducted postdoctoral research at the University of Reading (2020-2021) and completed his PhD in Consumer Behavior at the University of Copenhagen (2015-2019). His research focuses on advancing consumer behavior studies through interdisciplinary approaches, combining insights from marketing, behavioral economics, and human motion analysis. Zhou’s work emphasizes understanding decision-making processes and their applications in real-world contexts. Education history includes a PhD in Consumer Behavior from the University of Copenhagen (2015-2019), followed by postdoctoral training at the University of Reading (2020-2021). His academic trajectory reflects a strong foundation in both theoretical and applied research. His research interests span consumer behavior, marketing research methodologies, and behavioral economics. Notably, his recent publications explore cutting-edge technologies in motion capture and computer vision, including real-time human motion tracking and generative models for 3D reconstruction. This reflects a unique intersection of consumer behavior studies with technical advancements in computational methods. Zhou’s research outputs demonstrate expertise in areas such as inertial sensor-based motion analysis, physics-aware tracking systems, and hierarchical modeling techniques. His contributions highlight innovative solutions for challenges in human pose estimation and 3D reconstruction. He is currently based at ETH Zurich’s Department of Consumer Behavior, contributing to both academic research and potential industrial applications of his work.

Christoph Stadtfeldمشاهده پروفایل

دانشیار

• Social Network Analysis
• Dynamics of Social Networks
• Statistical Methods for Network Data
• +۲ مورد دیگر

Christoph Stadtfeld is Associate Professor of Social Networks at ETH Zurich's Department of Humanities, Social and Political Sciences and co-director of the ETH Social Networks Lab. His research examines social network dynamics, focusing on tie formation processes, network effects on individuals, and advanced statistical methodologies for longitudinal network analysis. Education: PhD from Karlsruhe Institute of Technology (2011) Postdoctoral researcher and Marie-Curie fellow at University of Groningen, University of Lugano, and MIT Media Lab (2011-2014) His work bridges sociology, statistics, and computer science to address fundamental questions about how social structures evolve and influence behavior. Key interests include relational event modeling, co-evolution of networks and attributes, and applications in mental health, political polarization, and scientific collaboration. He develops innovative methods for analyzing dynamic networks using cutting-edge computational approaches. Recent publications reveal strong emphasis on methodological rigor in temporal network analysis, with significant contributions to relational event modeling and dynamic network actor frameworks. His work increasingly addresses societal challenges including political polarization, mental health impacts of social isolation, and innovation dynamics in healthcare. Scientific awards: Raymond Boudon Award of the European Academy of Sociology (2017) Freeman Award of the International Network for Social Network Analysis (2021) As co-director of the ETH Social Networks Lab, Stadtfeld leads interdisciplinary research teams developing novel network methodologies. His work has been supported by prestigious fellowships including Marie-Curie funding, and he actively mentors graduate students in network science methodology and applications across diverse domains. The ETH Social Networks Lab serves as a hub for advancing network theory and methodology, with ongoing projects examining student networks during crises, scientific collaboration dynamics, and innovation ecosystems through the lens of network science.

Dominika Ignasiakمشاهده پروفایل

پژوهشگر

• Biomechanics
• Musculoskeletal Modeling
• Spinal Surgery
• +۳ مورد دیگر

Dr. Dominika Ignasiak is a Researcher affiliated with the Institute of Biomechanics at ETH Zürich. Her work focuses on spinal biomechanics, musculoskeletal modeling, and computational analysis of spinal pathologies. She contributes to understanding the biomechanical implications of surgical interventions, spinal deformities, and age-related changes in spinal alignment and loading. Her research integrates clinical data with advanced musculoskeletal modeling techniques, particularly in predicting postoperative outcomes and assessing spinal load distributions under dynamic conditions. Key areas include spinal stenosis, idiopathic scoliosis, and the biomechanics of spinal fusion surgery. Dr. Ignasiak collaborates on translational studies bridging computational simulations with clinical applications. Her publications emphasize the role of personalized models in optimizing surgical strategies and understanding degenerative spinal conditions. While no formal awards are listed, her contributions to spinal biomechanics research are evident through her active publication record in high-impact journals. Dr. Ignasiak is based at ETH Zürich’s Institute of Biomechanics, where she engages in cutting-edge research and contributes to both academic and clinical advancements in orthopedic biomechanics.

• Wave Propagation
• Seismic Data Modelling and Inversion
• Exploration Geophysics
• +۳ مورد دیگر

Prof. Dr. Johan Robertsson is a Full Professor of Applied Geophysics and Head of the Exploration and Environmental Geophysics (EEG) Group at ETH Zürich's Department of Earth and Planetary Sciences. He holds a MSc from Uppsala University (1991) and a PhD in Geophysics from Rice University (1994). Before joining ETH in 2012, he spent 15 years at Schlumberger in R&D roles, leading projects that revolutionized marine seismic data acquisition. His research focuses on wave propagation physics, seismic data inversion, and applications in exploration and environmental geophysics. He pioneered the use of Distributed Acoustic Sensing (DAS) for landslide monitoring and contributed to Mars seismology via the InSight mission. Education: MSc in Engineering Physics, Uppsala University (1991) PhD in Geophysics, Rice University (1994) Research Interests: Seismic wavefield modeling and inversion Planetary seismology (Mars, Moon) Acoustic metamaterials and wave control Environmental geohazard monitoring Marine seismic acquisition techniques His work on the Martian soil properties using InSight data and lunar exploration instrumentation (ALGEP) reflects his cross-disciplinary approach. He holds 90+ patents and has secured prestigious grants like the ERC Advanced Grant. Awards: EAGE Guido Bonarelli Award (2020) ERC Advanced Grant MATRIX (2017) EAGE Conrad Schlumberger Award (2018) Grants & Advising: Led the MATRIX ERC project advancing seismic imaging algorithms Advised over 20 PhD/MS students (names not listed) Secured Schlumberger's largest R&D project in marine seismic sampling His EEG Group operates cutting-edge labs for immersive wave experimentation and planetary geophysical instrumentation. Current initiatives include lunar subsurface exploration and acoustic invisibility experiments.

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +۷ مورد دیگر

Barbara Plank is a full professor and chair for AI and Computational Linguistics at Ludwig Maximilian University of Munich (LMU), where she heads the Munich AI and NLP (MaiNLP) lab and co-directs the Center for Information and Language Processing (CIS). She additionally serves as a visiting full professor at the IT University of Copenhagen, maintaining active dual institutional affiliations in computational linguistics and NLP research. Her research focuses on human-centric natural language processing challenges, particularly learning under sample selection bias (domain adaptation, transfer learning) and annotation bias, learning with limited data through continual/semi-supervised/weakly-supervised methods, multimodal learning at language-vision-speech interfaces, and fortuitous supervision for variety-space aware language understanding. She pioneers methodologies addressing human label variation as a critical factor in model robustness rather than mere noise. Recent publications (2024-2025) reveal dominant trends in modeling human label variation across NLP tasks, especially natural language inference and entity recognition, alongside dialectal language processing and LLM evaluation frameworks. Her work systematically investigates how human disagreement in annotations can be leveraged to build more robust, adaptable systems rather than treated as errors. Scientific recognition includes: ERC Consolidator Grant for the DIALECT project advancing natural language understanding for non-standard languages and dialects ACL 2024 Area Chair Award for the paper 'VariErr NLI: Separating Annotation Error from Human Label Variation' Leading the MaiNLP lab at CIS (LMU), she directs research integrated with MCML (Munich Center for Machine Learning), Munich Intelligent Robotics, ELLIS Unit Munich, UniDive, and COST action. Current projects include ERC-funded DIALECT and KLIMA-MEMES, focusing on human-facing NLP solutions for real-world language diversity challenges. She actively shapes the field through ACL leadership as VP-Elect and numerous keynotes emphasizing human-centric approaches. The MaiNLP lab at Akademiestr. 7, 80799 Munich, drives innovation in computational linguistics through interdisciplinary collaboration, maintaining strong ties with European research networks while developing practical applications for language variation and robust NLP systems. The lab's work directly informs her teaching in LMU's Computational Linguistics programs, bridging research and education in cutting-edge NLP methodologies.

Kyojin Chooمشاهده پروفایل

استادیار

• Charge-domain circuits
• Sensor interfaces
• Energy converters
• +۴ مورد دیگر

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 Ottavianoمشاهده پروفایل

پژوهشگر

• Computer Architecture
• Embedded Systems
• Real-Time Systems
• +۳ مورد دیگر

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.

• 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.

Hugo Subtilمشاهده پروفایل

پژوهشگر

• Political Economy
• Political Science
• Computational Social Science
• +۳ مورد دیگر

Hugo Subtil is a postdoctoral researcher at the Department of Political Science, Faculty of Arts and Social Sciences, University of Zurich, affiliated with the Chair of Comparative Politics in Political Institutions and European Politics. He is an active member of the University's Digital Society Initiative (DSI), particularly engaged with the DSI Community AI & Law and multiple other interdisciplinary communities including Cybersecurity, Digital Humanities, and Ethics. His academic background includes: Economics studies at École Polytechnique (France) PhD from École des Mines and École Polytechnique (France) Subtil's research program integrates Political Economy, Political Science, and Computational Social Science to investigate European political dynamics through quantitative text analysis. He specializes in extracting political ideologies from large-scale text corpora using machine learning algorithms and social media data, with dual research foci: (1) how institutional design shapes social norms and behaviors, and (2) longitudinal evolution of political ideologies. His methodological approach bridges traditional political science with cutting-edge computational techniques for analyzing legislative discourse and public communication. Analysis of his 12 publications (2020-2025) reveals a clear trajectory from historical economic analysis toward contemporary computational political science. Early work (2020-2021) examined Marxian economics and pandemic-era urban migration patterns, while recent research (2023-2025) increasingly focuses on European Parliament discourse, populism, and emotional rhetoric using advanced text mining techniques. This evolution demonstrates growing specialization in computational analysis of political communication within European institutions. No scientific awards or major honors are documented in the available information. While no formal advisees or grant funding details are specified, Subtil's collaborative work within the DSI framework suggests engagement with interdisciplinary research teams addressing digital society challenges. His position within the Chair of Comparative Politics indicates involvement in departmental research initiatives related to European governance. Subtil operates at the nexus of multiple research ecosystems: the Department of Political Science's European Politics research group, the university-wide Digital Society Initiative, and specialized DSI communities exploring AI-law intersections. His work contributes to the DSI's mission of addressing societal challenges through digitalization research, particularly in computational analysis of political discourse and institutional behavior.

Yuning Jiangمشاهده پروفایل

استاد مهمان

• Optimal Control
• Model Predictive Control
• Power Systems
• +۴ مورد دیگر

Yuning Jiang is a Visiting Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Automatic Control Laboratory (LA3) within the School of Engineering (STI). He teaches the doctoral course Optimal Control for Dynamic Systems and contributes to research in distributed optimization, model predictive control (MPC), and smart grid technologies. His work bridges theoretical advancements in control systems with practical applications in power networks and autonomous systems. Current research emphasizes scalable solutions for AC optimal power flow, real-time MPC for embedded systems, and robust optimization under uncertainty. His research interests span Optimal Control , Power Systems , Smart Grids , and Federated Learning . Notable contributions include distributed algorithms for large-scale power systems and privacy-preserving co-simulation frameworks. Recent publications focus on microservice deployment in satellite-terrestrial networks and real-time pricing mechanisms for vehicle-to-grid (V2G) integration. Yuning holds a position in the EDEE-ENS unit under EPFL’s Academic Affairs division (VPA-AVP-DLE), reflecting his role in academic administration and teaching infrastructure. His lab, the Automatic Control Laboratory, focuses on cutting-edge research in control theory and its interdisciplinary applications.

• Quantum Information
• Quantum Control
• Precision Spectroscopy
• +۳ مورد دیگر

Dr. Fabian Schmid is a Researcher affiliated with the Institute for Quantum Electronics at ETH Zürich, working within the Professorship for Experimental Quantum Information . His research focuses on quantum control, precision spectroscopy, and optical frequency comb technologies. Key applications include molecular ion manipulation, laser cooling techniques, and advanced spectroscopic methods for atomic and molecular systems. His work bridges quantum physics and optics, with contributions to ultra-stable laser systems, low-repetition-rate frequency combs, and high-resolution spectroscopic measurements. Recent efforts target applications in trapped ion systems and new boson constraints via calcium isotope studies. Schmid's experimental setups often involve precision engineering of optical components and cavity-stabilized laser systems. Notable experimental achievements include demonstrating quantum control over single molecular ions (H₂⁺) and developing number-resolved detection methods for Coulomb crystals. His research also explores synergies between dual-species laser cooling and cavity-based technologies. While currently holding no listed academic awards, Schmid's contributions are evident through his prolific publishing record in top-tier physics journals. His lab work integrates cutting-edge quantum optics with atomic physics to advance fundamental understanding and precision measurement capabilities.

Lars-Erik Cedermanمشاهده پروفایل

استاد

• Political Science
• International Relations
• Ethnic Conflict
• +۴ مورد دیگر

Lars-Erik Cederman is a Full Professor in the Department of Humanities, Social and Political Sciences at ETH Zurich, Switzerland, where he conducts cutting-edge research at the intersection of political science, international relations, and computational social science. His work focuses on the structural and historical drivers of ethnic conflict, nationalism, and state formation across global contexts. His primary research interests include: Political Science International Relations Ethnic Conflict Nationalism Civil War State Formation Computational Social Science Cederman's scholarship demonstrates exceptional methodological innovation, combining large-scale historical datasets like CShapes and Ethnic Power Relations with computational modeling to analyze patterns of violence and state transformation. His recent publications reveal a sustained focus on how historical legacies—particularly colonialism, infrastructure development, and ethnic geography—shape contemporary conflicts, with significant contributions to understanding ethnic cleansing, separatist mobilization, and the geopolitical strategies of nationalist movements from post-Napoleonic Europe to modern Russia. His work bridges theoretical rigor with empirical depth, offering critical insights for conflict resolution and peacebuilding.

• Information Theory
• Communication Theory
• Signal Processing
• +۳ مورد دیگر

Dina Khaled Sayed Abdelhadi is a Doctoral Assistant at the Communication Theory Laboratory (LTHC) within the School of Computer and Communication Sciences (IC) at École Polytechnique Fédérale de Lausanne (EPFL). She is also a PhD student in the Doctoral Program in Computer and Communication Sciences (EDIC), hosted under the EDOC school at EPFL. Her work is centered in the Institute of Computer and Communication Sciences (IINFCOM), focusing on theoretical and applied aspects of communication systems. Her research interests are rooted in Information Theory , Communication Theory , and Signal Processing , with potential applications in wireless networks and data transmission. Given her affiliation with LTHC, her work likely involves advanced mathematical modeling, probabilistic methods, and algorithm design for communication systems. No scientific awards or publications were mentioned in the provided text. However, her position as a Doctoral Assistant suggests active involvement in research projects funded by EPFL or external agencies, possibly including collaborations within the laboratory or international consortia. She is advised by faculty within the LTHC group, though no advisor is explicitly named. There is no mention of students supervised by her. She is part of a structured doctoral program, indicating rigorous academic training and research progression. The Communication Theory Laboratory (LTHC) at EPFL is known for cutting-edge research in information theory, network coding, and communication algorithms. As a member of this lab, Dina contributes to ongoing projects that bridge theoretical advances with practical communication technologies.

• Quantum Optics
• Quantum Simulation
• Ultracold Atoms
• +۳ مورد دیگر

Konrad Viebahn is a Researcher at ETH Zurich's Department of Physics, working within the Professorship for Quantum Optics. Based at HPF D 23, Otto-Stern-Weg 1, Zurich, he contributes to experimental quantum simulation research with contact via viebahnk@ethz.ch and +41 44 633 23 45. His research centers on quantum many-body systems in optical lattices, specializing in topological phenomena and Floquet engineering. Key interests include Thouless pumping in driven systems, quantum control of ultracold atoms, and mitigating heating in Floquet-Hubbard lattices. His work bridges theoretical concepts like topological phase transitions with experimental implementations using laser-cooled atomic gases. Analysis of his 2021-2025 publications reveals a consistent focus on engineering topological quantum behavior through periodic driving techniques. His group pioneers two-tone driving methods to manipulate band structures, enabling protected quantum gates and precise charge pumping. This research directly addresses challenges in quantum simulation scalability and error mitigation for future quantum technologies. As part of ETH Zurich's Quantum Optics group, Dr. Viebahn utilizes advanced optical lattice platforms to study strongly correlated quantum matter. The team's experimental setup involves precision laser systems for creating dynamical potentials, with recent work emphasizing the interplay between interactions and topology in non-equilibrium systems.

Anja Skrivervikمشاهده پروفایل

استاد

• Antenna Design
• Wireless Power Transfer
• Implantable Medical Devices
• +۷ مورد دیگر

Anja Skrivervik is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), holding multiple key academic positions across the institution. She serves as a Full Professor in the School of Engineering (STI) within the Electromagnetics and Antennas group, as Director of the Electrical Engineering Doctoral Program, and as a Full Professor in multiple teaching units including EDEE, SEL, and EDMI. Her extensive institutional affiliations demonstrate her significant leadership role within EPFL's engineering and educational frameworks. Professor Skrivervik's research spans multiple cutting-edge domains in electromagnetic engineering with a particular focus on antenna design for specialized applications. Her work prominently features implantable medical devices, where she develops antennas and wireless power transfer systems for deep-body bioelectronics. She has made significant contributions to mm-Wave technology, particularly in multibeam systems for 5G applications and wireless power transfer. Her research also encompasses tissue phantom development for electromagnetic characterization, with recent work on biodegradable alternatives to traditional materials. The interdisciplinary nature of her work bridges electrical engineering, biomedical applications, and materials science. An analysis of her recent publications (2023-2025) reveals a consistent research trajectory focused on solving practical challenges in antenna design for constrained environments. Her work shows particular strength in optimizing antenna performance for implantable medical devices, where size, efficiency, and biocompatibility present unique challenges. She has developed novel approaches to beamsteering, mutual coupling reduction, and RF radiation modeling specifically tailored for medical applications. Her contributions to tissue phantom development represent an important methodological advancement for testing and validating implantable devices. As Director of the Electrical Engineering Doctoral Program and through her multiple professorial appointments, Professor Skrivervik plays a central role in shaping graduate education at EPFL. Her leadership extends to serving on the Doctoral Commission, where she helps set standards and policies for doctoral education across the institution. While specific grant information isn't detailed in the available materials, her extensive publication record across top journals and conferences suggests successful funding of her research activities. Her work appears to be conducted within EPFL's Electromagnetics and Antennas group (SCI STI AS), which likely houses specialized laboratories for antenna measurement, electromagnetic simulation, and biomedical device testing. The focus on tissue phantoms and implantable devices suggests dedicated facilities for biomedical electromagnetic testing, while her mm-Wave and 5G research indicates capabilities in high-frequency measurement and characterization.