جست‌وجوی استاد و پژوهشگر

• High-Performance Computing
• Performance Modeling
• Parallel Computing
• +۳ مورد دیگر

Alexandru Calotoiu is a Researcher in the Department of Computer Science at ETH Zürich, affiliated with the Professorship for Scalable Parallel Computing. His work focuses on performance modeling, high-performance computing (HPC), serverless systems, and cloud computing. He leads research in empirical performance modeling for complex applications, optimization of parallel algorithms, and scalable cloud architectures. Key research areas include noise-resilient performance models, serverless computing frameworks, and compositional parallel programming. He has contributed to benchmarking tools like SeBS and developed techniques for loop scheduling, static analysis, and resource disaggregation in HPC environments. His publications from 2023–2025 emphasize serverless systems (e.g., FaaSKeeper, Cppless), performance embeddings for optimization, and specialized supercomputing for climate science. These studies address scalability, reproducibility, and cross-platform performance portability in data-centric workloads. No scientific awards are explicitly listed, but his work has been presented at leading conferences such as ISCA and IEEE/ACM events. He collaborates on projects like rFaaS (RDMA-enabled serverless platforms) and Process-as-a-Service frameworks. His research bridges theoretical models with practical implementations in distributed systems and cloud infrastructure.

• Graph Algorithms
• Theoretical Computer Science
• Approximation Algorithms
• +۲ مورد دیگر

Tianyi Zhang is a Researcher at the Professorship for Theoretical Computer Science, ETH Zurich, located at OAT Z 29, Andreasstrasse 5. His research focuses on advancing fundamental algorithms in graph theory, with particular expertise in dynamic graph problems, efficient spanner constructions, edge coloring optimizations, and shortest-path computations. Dr. Zhang develops both theoretical frameworks and practical implementations for complex computational challenges. His core research areas include the design of near-linear and subquadratic time algorithms for graph optimization problems, fault-tolerant network structures, streaming-optimized graph coloring, and geometric graph embeddings. Recent work emphasizes breakthroughs in Vizing's theorem implementations, dynamic set cover deamortization, and space-efficient distance oracles. Dr. Zhang's publications demonstrate consistent innovation in algorithm efficiency for planar graphs, Euclidean spaces, and dynamic network settings. His 2023-2025 articles reveal concentrated efforts on: 1) Optimizing edge coloring through multi-step Vizing chains and streaming adaptations, 2) Enhancing spanner constructions for doubling metrics and planar environments, and 3) Developing failure-resistant path algorithms with improved time/space complexity. These contributions address scalability challenges in large-scale network processing. He collaborates within the Theoretical Computer Science research group at ETH Zurich, contributing to the institution's leadership in algorithmic innovation. No information about awarded grants, supervised students, or educational background is available in the source materials.

• Seismology
• Geodynamics
• Gravitational Wave Astronomy
• +۳ مورد دیگر

Dr. Stefan Strub is a Researcher at ETH Zurich's Institute of Geophysics within the School of Earth and Planetary Sciences (D-EAPS). He is affiliated with the Professorship for Seismology and Geodynamics. His primary research focuses on gravitational wave astronomy, seismology, and geodynamics, with a strong emphasis on data analysis techniques for space-based missions like LISA. He develops advanced algorithms for parameter estimation in gravitational wave signals, including applications of machine learning and Bayesian methods. His work contributes to understanding massive black hole mergers, extreme mass ratio inspirals, and galactic binary systems. Key technical contributions include optimizing parameter estimation through genetic algorithms and GPU computing, as well as applying Gaussian Process Regression to LISA data. Dr. Strub's expertise spans both theoretical modeling and experimental sensor technology, as evidenced by his 2019 work on strain sensing applications. His research bridges geophysics with astrophysics, leveraging interdisciplinary approaches to tackle challenges in observational astronomy and earth sciences.

• Wireless Communication
• Machine Learning
• Digital Signal Processing
• +۶ مورد دیگر

Prof. Christoph Studer is a Full Professor of Integrated Information Processing at ETH Zurich's Department of Information Technology and Electrical Engineering. He leads the Integrated Systems Laboratory and directs SwissChips. His research focuses on wireless communication, machine learning, signal processing, and hardware-efficient algorithms, with applications in B5G systems, sensing-communication integration, and low-power signal processing. He holds a Ph.D. and M.S. from ETH Zurich (2009 and 2006) and has held academic positions at Cornell University before returning to ETH in 2020. Notable honors include the NSF CAREER Award (2017), ETH Medal for Doctoral Dissertation (2011), and multiple teaching awards. Education: M.S. and Ph.D. in Information Technology and Electrical Engineering, ETH Zurich (2006, 2009) Visiting Researcher, Stanford University (2005) Research Interests: Develops algorithms and hardware for high-throughput, low-power wireless systems. Key areas include: B5G multi-antenna systems and simultaneous sensing-communication (SISCO) Analog-to-feature (A2F) conversion for low-power signal classification Hardware-software co-design for efficient microchip integration Publications: Focus on channel charting, jammer mitigation, and deep learning for communication. Recent work includes CSI2Vec, jammer-resilient synchronization, and distributed MIMO systems. Awards: US NSF CAREER Award (2017) Michael Tien Teaching Award (2016) ETH Medal for Doctoral Thesis (2011) Labs/Teams: Leads the Integrated Systems Laboratory at ETH and directs SwissChips, a national initiative for integrated circuit development.

Ola Svenssonمشاهده پروفایل

دانشیار

• Approximation Algorithms
• Combinatorial Optimization
• Computational Complexity
• +۳ مورد دیگر

Ola Svensson is an Associate Professor at the School of Computer and Communication Sciences, EPFL. His research focuses on approximation algorithms, combinatorial optimization, computational complexity, and scheduling. He has been supported by grants including the ERC Starting Grant "OptApprox" (2014-2019), SNF grants, and the ERC Consolidator Grant "POTCO" (2023-). He teaches courses such as Advanced Algorithms and Approximation Algorithms and Hardness of Approximation. Education: PhD from IDSIA - Universita della Svizzera italiana (2009) and Master's from Uppsala University (2005). Research Interests: Design and analysis of approximation algorithms for NP-hard problems, scheduling, and computational complexity. He explores limitations of approximation techniques through hardness results and contributes to theoretical computer science. Publications span clustering, scheduling, and graph problems like the Traveling Salesman Problem. Recent work includes learning-augmented algorithms and robust optimization. Awards: I&C teaching award and best paper awards at FOCS (2017) and STOC (2018). Over a dozen PhD students advised, many entering postdocs or industry roles. Labs/Teams: Part of the theory group at EPFL, collaborating on academic projects and course development.

Adam Hugh Clarkمشاهده پروفایل

پژوهشگر

• Heterogeneous Catalysis
• X-ray Absorption Spectroscopy
• Electrochemistry
• +۹ مورد دیگر

Dr. Adam Hugh Clark is a tenure track scientist at the Paul Scherrer Institute (PSI) in Switzerland, specializing in advanced spectroscopic techniques and heterogeneous catalysis. He holds a Bachelor's degree in Physics from the University of Nottingham , and a Master's and PhD in Molecular Modelling and Materials Science from University College London . At PSI, he focuses on uncovering structure-activity relationships in catalytic materials using time-resolved X-ray absorption spectroscopy (XAS). Education B.Sc. in Physics, University of Nottingham M.Sc. and PhD in Molecular Modelling and Materials Science, University College London Research Interests Clark’s research centers on heterogeneous catalysis , particularly ceria-based materials for semi-hydrogenation and perovskite oxides for oxygen evolution reactions (OER). He develops and applies highly time-resolved XAS and modulation-excitation spectroscopy to study dynamic material properties during reactions. His work bridges materials science and operando XAS , with applications in electrochemistry and sustainable chemical processes. Recent projects include platinum single-atom catalysts for vinyl chloride production and LaFe0.8Ni0.8O3 perovskites for redox studies. Publications & Software Development His 2025 publications span quantum simulation , MOF synthesis , and high-energy particle physics collaborations. Earlier works (2019–2020) introduced ProQEXAFS , a Python-based software for rapid QEXAFS data processing. He also advanced fluorescence-detected XAS for low-concentration samples and contributed to understanding Fe-doped Co perovskites in OER. Institutional Roles Clark manages the SuperXAS beamline at the Swiss Light Source and leads software development for quick-scanning XAS analysis . Since 2025, he has served on the ChemCatChem early career advisory board , promoting interdisciplinary catalysis research. Labs & Collaborations He works within the Operando Spectroscopy group at PSI, collaborating with institutions like CERN and ETH Zürich on projects involving density functional theory (DFT) , synchrotron techniques , and advanced detector systems (e.g., CMS). His affiliations include the Particle Physics LTP and Advanced Spectroscopy and X-ray Sources LSX laboratories at PSI.

Matija Piškorecمشاهده پروفایل

پژوهشگر

• Machine Learning
• Complex Systems
• Statistical Inference
• +۵ مورد دیگر

Matija Piškorec is a Senior Research Associate at the Faculty of Informatics, University of Zurich. His research spans machine learning, complex systems, and blockchain technologies, with a focus on statistical inference of social influence and network analysis. Primary Affiliation: Faculty of Informatics, University of Zurich Research Interests Machine learning and complex systems Statistical inference of influence in online social networks Blockchain technologies and distributed ledger systems Information visualization and interactive web applications in computational biology Publications His recent work explores blockchain networks like Polkadot and Ethereum, analyzing their structure and consensus mechanisms. Earlier research focuses on social network influence, financial data cohesiveness, and computational biology tools. Awards No scientific awards or honors were explicitly mentioned in the text. Additional Contributions Developed web-based visualization tools (e.g., MultiNets) and applied machine learning to diverse domains, including microbiology and finance.

• Computational Fluid Dynamics
• Discrete Element Method
• High Performance Computing
• +۵ مورد دیگر

Mark Sawley is a Senior Scientist at École Polytechnique Fédérale de Lausanne (EPFL) with dual appointments in the Institute of Mechanical Engineering (IGM) for administration and the School of Management (SGM) for teaching. With over 30 years of experience in academic, government laboratory, and private institutions across Switzerland and Australia, he holds a PhD in Physics and has founded/co-founded two high-tech startup companies. His administrative roles include coordinating ACCES for Computational Engineering promotion and serving as Coordinator for Academic Affairs at the STI Faculty. Dr. Sawley's research spans computational fluid dynamics, discrete element method simulations, and high-performance computing applications. His work bridges multiple disciplines with applications in materials science (concrete simulation), bioengineering (blood flow modeling), marine engineering (America's Cup yacht design), avalanche dynamics, and industrial particulate processing. His recent publications (2018-2021) demonstrate continued activity in applying numerical methods to solve complex engineering problems. His scientific contributions include 37 peer-reviewed journal papers, 58 conference proceedings, and 21 articles for general audiences. His work uniquely connects technical research with science communication through projects like TIMBRE!! and the DEM Gallery, emphasizing the relationship between science and art. 37 scientific papers in international peer-reviewed journals 58 papers in international conference proceedings 21 science communication articles for general audiences Professor Sawley has advised PhD students including Serge Wüthrich (1992) and Olivier Byrde (1997). His Computational Granular Dynamics lab (http://cgd.epfl.ch) provides a platform for interdisciplinary research connecting physics, engineering, and computational science. His administrative leadership in academic affairs and computational engineering promotion demonstrates his commitment to advancing both research and education at EPFL.

• Economics
• Innovation Economics
• R&D Networks
• +۴ مورد دیگر

Michael David König is a Lecturer at the Department of Management, Technology, and Economics at ETH Zürich, specializing in Innovation Economics within the KOF Swiss Economic Institute. His research focuses on the intersection of network theory and economics, particularly examining R&D networks, technology spillovers, and innovation dynamics. König maintains an active research profile with publications spanning economics, network science, and computer science. König's research spans multiple domains including economic network analysis, innovation economics, and technology diffusion. He has made significant contributions to understanding how firms form R&D collaborations and how knowledge flows through these networks. His work combines theoretical modeling with empirical analysis of large-scale network data, revealing patterns such as oscillatory dynamics in R&D collaboration intensity. Recent research has also addressed practical economic issues, including firm responses to the COVID-19 pandemic and factors influencing R&D investment decisions in Switzerland. His interdisciplinary approach bridges economics with computational methods, reflecting his background in both theoretical and applied network analysis. König's publication record demonstrates a strong interdisciplinary trajectory, beginning with contributions to wireless network protocols and distributed systems before focusing more intensively on economic applications of network theory. A consistent theme across his career has been the study of how networks evolve and how these structures influence outcomes in various domains, from technology diffusion to economic fluctuations. His research often employs sophisticated modeling techniques to analyze the coevolution of networks and economic behavior, with particular attention to the dynamics of knowledge creation and diffusion. König teaches Introduction to Microeconomics at ETH Zürich, as evidenced by his listing in the Autumn Semester 2025 course catalog. His office is located at LEE G 224, Leonhardstrasse 21, 8092 Zürich, Switzerland. He is affiliated with the KOF Innovation Economics research group, which focuses on innovation, technological change, and their economic implications.

Frank Tillenkampمشاهده پروفایل

استاد

• Refrigeration Technology
• Heat Pumps
• Energy Efficiency
• +۴ مورد دیگر

Prof. Dr.-Ing. Frank Tillenkamp is a full Professor for Refrigeration Technology, Fluid Dynamics and Energy Systems at ZHAW School of Engineering, where he serves dual leadership roles as Director of the Institute of Energy Systems and Fluid Engineering and Department Director of Mechanical Engineering, Energy Technology and Aviatics (MEA). His research focuses on advancing sustainable energy solutions through refrigeration technology, heat pump optimization, and energy efficiency in building systems. His primary research domains include: Advanced refrigeration cycle design and CO2-based systems Heat pump hydraulics and performance optimization Exergy-based efficiency assessment methods Blast safety valve mechanics and fluid-structure interactions Energy storage solutions for commercial applications Publication analysis reveals three dominant research trajectories: Energy efficiency optimization in refrigeration/HVAC systems (6 publications) Safety engineering for blast-resistant components (4 publications) Sustainable energy integration in buildings (3 publications) Recent work shows increasing focus on computational methods including FSI simulations and computer vision applications. Professor Tillenkamp leads multiple research initiatives: Underground Farming : Investigating sustainable agriculture systems (ongoing) Community Energy Storage : Completed project on energy grid integration Cooling System Comparison : Analyzing commercial refrigeration configurations (ongoing) He maintains active industry engagement as Chairman of SNV INB NK 181 standards committee for refrigeration systems and contributes to SIA heating standards. His laboratory focuses on experimental validation of energy systems, with particular expertise in hydraulic network optimization and refrigeration test rigs.

Marcel Honeggerمشاهده پروفایل

مدرس

• Robotics
• Mechatronics
• Control Systems
• +۴ مورد دیگر

Prof. Dr. Marcel Honegger is a Lecturer in Robotics and Mechatronics at the Institute of Mechatronic Systems within the School of Engineering at Zurich University of Applied Sciences (ZHAW). He co-leads the Institute and focuses on the development of robot systems, drive controls, and control/regulation software for robotics and mechatronics. Ph.D., ETH Zurich (1996-1999) Dipl. Mech. Eng., ETH Zurich (1990-1996) His research spans robotics, mechatronics, and control systems, with recent work on predictive maintenance using autoencoder-based anomaly detection for delta robots and RGBD segmentation for agricultural automation. Earlier projects involved adaptive controllers for parallel manipulators and Java frameworks for robot control systems. Honegger has led projects such as the full automatic sprinkler robot (FASR) and the Advanced Rail Track Information System . He previously worked as a Senior R&D Engineer at CSEM Alpnach (2001-2009) and Project Manager at maxon motor ag (2009-2014). His publications reflect expertise in industrial automation, sensor integration, and mechanical design. He is involved in teaching and R&D collaborations, with an ORCID ID: 0009-0004-8178-136X.

Sophie G Martinمشاهده پروفایل

استاد

• Cell polarization
• Cytoskeleton organization
• Cell-cell fusion
• +۵ مورد دیگر

Sophie G Martin is a Full Professor in the Department of Molecular and Cellular Biology at the University of Geneva , Switzerland. Her research focuses on molecular mechanisms of cell polarization , actin and sterol dynamics , and cell-cell fusion processes using Schizosaccharomyces pombe as a model organism. Current research explores TORC1 reactivation during mating, Cdc42 threshold dynamics in fusion decisions, and cross-species actin network imaging Leaders the Martin Lab at Geneva, mentoring 14+ students/postdocs including Laura Merlini and Melvin Bérard Research Highlights : Through quantitative live-cell imaging, electron microscopy, and proteomics, her lab investigates: Coordination of cytoskeletal organization with membrane dynamics Phosphoproteomic signaling networks in sexual reproduction Actin focus architecture in fusion processes Evolutionary conservation of aster formation mechanisms Recent Publications (2023-2024) reveal key findings about: Cdc42 concentration thresholds in mating TORC1's dual role in starvation and reproduction Arp2/3-dependent endosome shaping Novel microscopy methodologies (Cryo-ExM, IntAct-U-ExM) Mechanistic parallels between actin and microtubule organization Collaborations span structural biology, microscopy, and yeast genetics communities, including Marko Kaksonen, Carolyn Bertozzi, and Tim Clausen's group.