جستجوی استاد راهنمای دانشگاهی

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.

Ingo Scholtesمشاهده پروفایل

استاد

• Machine Learning
• Network Science
• Graph Mining
• +۵ مورد دیگر

Prof. Ingo Scholtes is a Full Professor of Machine Learning for Complex Networks at Julius-Maximilians-Universität Würzburg's Center for Artificial Intelligence and Data Science (CAIDAS). He holds a doctorate in computer science and mathematics from the University of Trier and has held roles including SNSF Professor at the University of Zurich, Full Professor at Bergische Universität Wuppertal, and Senior Assistant at ETH Zürich. His research focuses on higher-order graph analytics for temporal networks, machine learning, and computational social science. Education: PhD in Computer Science (University of Trier, Germany), Postdoctoral Research at ETH Zürich (2011–2016), and prior roles at Karlsruhe Institute of Technology and CERN. Research Interests: Machine learning on graphs, temporal network analysis, higher-order network models, and their applications in software engineering and social systems. He develops open-source tools like pathpy and git2net for network analysis. Recent Work: Focuses on causality-aware graph neural networks, temporal graph isomorphism, and network science applications in AI. Recent articles include studies on temporal network dynamics, path prediction, and Bayesian inference of network transitions. Awards: SNSF Professorship (2018), Junior-Fellowship (2014), and German Academic Scholarship Foundation (2004-2005). Active in editorial roles for EPJ Data Science and leadership in GI's Computational Social Science working group.

• Cloud Computing
• Distributed Systems
• Network Functions Virtualization (NFV)
• +۷ مورد دیگر

Prof. Dr. Thomas Michael Bohnert is a faculty member at ZHAW School of Engineering, specializing in distributed systems and cloud computing. He has led multiple projects including: Bringing FIWARE to the NEXT step (completed), Enterprise Cloud Robotics Platform (completed), Apache Cloudstack for NFV (completed), Solidna cloud storage (completed), T-NOVA NFV services (completed), and Mobile Cloud Network (completed). Research Focus: Cloud robotics Network Functions Virtualization (NFV) Software-Defined Networking (SDN) Mobile cloud networking Resilient cloud systems Energy-efficient cloud platforms Publications Trends: His work spans 2012-2024 with consistent focus on cloud-native application design, NFV orchestration, SDN implementation, and mobile cloud integration. Key themes include self-managing systems, distributed computing frameworks, and infrastructure optimization. Collaborations: Frequently collaborates with Andrew Edmonds, Giovanni Toffetti Carughi, Piyush Harsh, and Sandro Brunner across EU projects and industry partnerships.

• Computational Linguistics
• Natural Language Processing (NLP)
• Language Model Interpretability
• +۴ مورد دیگر

Dr. Dan Jurafsky is a Professor at the Department of Linguistics within Stanford University's School of Humanities and Sciences. His work spans computational linguistics, natural language processing, and AI ethics, with a particular focus on language model behavior, speech recognition, and ethical implications of anthropomorphism in AI systems. His recent research explores HumT for measuring human-like tone in LLMs, AnthroScore for anthropomorphism detection, and methods for improving low-resource language support through data augmentation and multilingual representation learning. He has also developed open-source tools like string2string for string algorithms. Jurafsky's publications address critical issues in NLP, including grounding gaps in conversational models, causal interpretability in linguistic tasks, and representational biases in multilingual models. His work emphasizes interdisciplinary applications, from educational NLP tools to Sumerian transliteration datasets, while advocating for rigorous statistical power analysis and ethical model evaluation.

• Embedded Systems
• RF Technologies
• Bluetooth Low Energy (BLE)
• +۴ مورد دیگر

Boegli Alexis is an Associate Professor at Haute Ecole Arc - Ingénierie (HES-SO) since 2018, with a PhD in Science from the University of Neuchâtel. Specializing in embedded systems, RF technologies, and energy-efficient electronics, he focuses on applications requiring high constraints such as energy autonomy and compactness. His research spans BLE-based localization, dielectric elastomer actuators, and energy harvesting for biomedical devices. His educational background includes a BSC in Computer Science and Communication Systems from HES-SO and advanced studies in Microengineering at EPFL. He teaches courses like Electrotechnics I and co-supervises doctoral students in interdisciplinary projects. Key research areas include: RF Localization Systems (BLE AoA/AoD) High-Voltage Electronics for Capacitive Actuators Zero-Power Wearable Energy Harvesting Smart Sensor Networks Recent work demonstrates sub-meter accuracy in IoT localization systems using BLE and developed ultra-high-voltage (7kV) converters for dielectric elastomer actuators. His 2025 research explores inverted actuation cycles for facial prosthetics, reducing energy consumption by 1.5%. Patents include a BLE-based access control system combining RF positioning and video analysis (2022) and a real-time regulatory compliance method for wireless transmitters (2013). Collaboration with EPFL and CSEM drives technology transfer in industrial and biomedical applications. His projects often involve Innosuisse, SNSF, and industry partners.

• Combinatorial Optimization
• Artificial Intelligence
• Algorithms and Heuristics
• +۳ مورد دیگر

Eric Taillard is a Full Professor and Head of the Cross-functional Skills Group 'Optimization & Sustainability' at the School of Engineering and Management of the Canton of Vaud (HES-SO), part of the University of Applied Sciences and Arts Western Switzerland (HES-SO). He holds degrees in Computer Science, Engineering, and Production Management from HES-SO institutions. His research focuses on combinatorial optimization, metaheuristics, and algorithm design, with notable contributions to the Travelling Salesman Problem (TSP) and automated map labeling. Education: BSc in Computer Science and Communication Systems MSc in Engineering (Algorithms and Data Structures) MA in Production and Logistics Management Key Projects: Big Data in Combinatorial Optimization (2017–2020): Explored optimization techniques for large-scale problems. Parallel Computing on GPU Clusters (2010–2012): Enhanced combinatorial optimization via GPU parallelization. Automated Label Placement (2007–2008): Developed the PAL library for efficient cartographic labeling. Research Interests: Metaheuristics, TSP algorithms, POPMUSIC framework, algorithmic efficiency, and applications in logistics and cartography. His work has been published in journals like the EURO Journal of Operational Research and presented at Metaheuristics International Conferences. He leads interdisciplinary teams and collaborates with academic and industrial partners globally.

• Energy Policy
• Renewable Energy Systems
• Sustainable Development
• +۳ مورد دیگر

Stéphane Genoud is a Full Professor at the HES-SO Valais-Wallis, affiliated with the School of Management and the Institute of Entrepreneurship & Management. His work focuses on energy transition, renewable energy markets, and sustainable development. He leads the Energy Management Lab and has been principal investigator in numerous projects, including GROUP-IT initiatives to accelerate photovoltaic adoption and energy efficiency strategies. His research emphasizes bridging academic insights with practical implementation through collaborative frameworks. Education Programs: Involved in BSc programs in Energy and Environmental Techniques (School of Engineering) and Business Economics (School of Management). Key Projects: GROUP-IT (photovoltaic installation support), Clean Energy EXchange (CEEX) algorithm development, Delocalized Forecast for Smart Grids, and energy policy initiatives like Transition Énergétique for municipalities. Research Interests: Energy forecasting, energy market dynamics, decentralized renewable energy integration, and community-driven energy solutions. His work often involves interdisciplinary teams and industry partnerships to address grid stability, cost optimization, and policy implementation. Grants & Funding: Secured over 1.5M CHF in grants from sources like the Swiss Federal Office of Energy (FOEN), Innosuisse, and regional municipalities. Notable projects include GROUP-IT Neuchâtel-Milvignes (CHF 79,123) and the MSID distributed storage pilot (CHF 354,667). Engagement: Organized annual Energy Forum events, fostering dialogue between policymakers, industry, and academia. Collaborated with institutions like Romande Energie and SIG Vitale to advance regional energy strategies.

Zhengqing Wuمشاهده پروفایل

پژوهشگر

• Machine Learning
• Robotics
• Neural Networks
• +۳ مورد دیگر

Zhengqing Wu is a Doctoral Assistant and Student at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Laboratory for Information and Inference Systems (LIONS) under the Institute of Electrical Engineering (IEM) within the School of Engineering . Their research focuses on machine learning, robotics, quantum computing, and control systems, with notable contributions to neural network optimization, terrain-aware robotics, and quantum parameter-efficient fine-tuning. They are part of the Doctoral Program in Computer and Communication Sciences (EDIC). Key research interests include layer-wise quantization in neural networks, analysis of shallow ReLU networks' loss landscapes, and developing terrain-aware control systems for quadrupedal robots. Their work bridges theoretical insights (e.g., neural noise dynamics) with applied robotics and quantum computing advancements. Education: Doctoral Program in Computer and Communication Sciences (EDIC), EPFL Affiliations: LIONS Lab, EPFL No scientific awards are explicitly mentioned in the provided texts. Their advising and grant activities are not detailed here. The LIONS Lab focuses on information theory, signal processing, and machine learning applications.

• Medical Robotics
• Magnetic Actuation Systems
• Soft Robotics
• +۳ مورد دیگر

Salvador Pane is a Professor at ETH Zurich's Department of Mechanical and Process Engineering within the Institute of Robotics and Intelligent Systems. His research focuses on developing advanced medical robotics systems, particularly magnetic navigation technologies for minimally invasive procedures. His research expertise spans Medical Robotics , Magnetic Actuation Systems , and Shape Memory Polymers , with emphasis on targeted drug delivery, catheter navigation, and variable stiffness mechanisms. Key innovations include electromagnetically guided microcatheters, human-scale clinical navigation systems, and programmable magnetic cilia for fluid control. His publication portfolio demonstrates strong trends in translational medical robotics with 8 high-impact publications between 2020-2024 in journals including Advanced Science , Nature Communications , and IEEE Transactions on Robotics . Work frequently addresses clinical implementation challenges in electromagnetic navigation and biomaterial integration. Pane leads collaborative research with significant clinical relevance, evidenced by news coverage of multiple publications. His team has developed clinically ready systems for magnetic particle injection and human-scale navigation, with research picked up by multiple news outlets and demonstrating strong Mendeley readership. Current work centers on the Robotic Materials Lab at ETH Zurich, focusing on electromagnetic navigation systems, variable stiffness catheters, and magnetic swarm control. The lab maintains strong industry and clinical partnerships for translating robotic technologies into medical practice.

• Renewable Energy
• Energy Systems Optimization
• Thermal Energy Storage
• +۴ مورد دیگر

Ueli Schilt is a Research Associate and Doctoral Student at the Lucerne School of Engineering and Architecture, part of the Lucerne University of Applied Sciences and Arts (HSLU). His work focuses on thermal energy systems, renewable generation, and energy efficiency in Swiss urban and regional contexts. He is affiliated with the Institute of Mechanical Engineering and Energy Technology (IME), specifically within the Thermal Energy Storage research group. Role: Research Associate & Doctoral Student Institution: Lucerne University of Applied Sciences and Arts (HSLU) School: School of Engineering and Architecture Institute: Institute of Mechanical Engineering and Energy Technology (IME) Research Focus: Thermal energy storage, multi-energy system optimization, renewable integration Ueli Schilt’s research explores the integration of thermal energy storage in multi-energy systems, solar PV expansion, and heating system retrofits. His work emphasizes temperature considerations, load forecasting, and sensor technology validation. Key projects include decentralized renewable generation in Swiss regions and the SENSHOEK initiative for adaptive heating controls. Recent publications highlight advancements in air quality monitoring, heat pump consumption analysis, and communal energy planning tools. While no scientific awards are explicitly listed, his contributions to peer-reviewed journals and international conferences indicate active academic engagement. Collaborations with Philipp Schütz and other researchers underscore interdisciplinary teamwork in energy modeling and policy support.

• E-Food
• Quick Commerce
• Food Delivery
• +۶ مورد دیگر

Dr. Matthias Schu is a Lecturer at the Institute of Communication and Marketing within Lucerne School of Business at Lucerne University of Applied Sciences and Arts. He holds a doctorate in E-Commerce Internationalization from the University of Fribourg (Switzerland) and a business degree with specialization in Trade from Saarland University (Germany). With over a decade of industry experience, he has held leadership positions at Praktiker Deutschland, Swiss Federal Railways (SBB), and Coop Group. Research Focus: Dr. Schu's expertise spans E-Food ecosystems, Quick Commerce logistics, Omnichannel retail integration, and international e-commerce strategies. His work examines behavioral economics in sustainability, returns management optimization, and algorithmic nudging techniques. Current projects include: Algorithmic Nudging for Sustainability in E-Commerce Marketing, Loyalty and Sustainability in Swiss E-Commerce Returns Management in Swiss Online Retail Lock-In Effects in E-Food markets Professional Activities: He operates three advisory startups: 'Dr. Matthias Schu | retail | ecommerce | internationalization strategy', 'Disrupt Retail', and 'E-Food Consult', providing strategic guidance to retailers and producers. An active thought leader, he serves on the etailment Expert Council, reviews academic journals, and delivers keynote addresses on retail innovation.

Blaise Mellyمشاهده پروفایل

استاد

• Econometrics
• Labor Economics
• Empirical Microeconomics
• +۴ مورد دیگر

Blaise Melly is a Professor of Econometrics and Head of the Department of Economics at the University of Bern. He also serves as an Associate Editor of the Journal of Business and Economic Statistics . His research focuses on econometric methods, labor economics, and empirical microeconomics, with a strong emphasis on quantile regression techniques and their applications in policy analysis. Key research interests include panel data analysis, counterfactual analysis, treatment effects, and wage gap studies. He has developed influential Stata modules (e.g., QRPROCESS) and contributed to software tools for quantile regression. His work addresses issues like public vs. private sector wage gaps, informal labor markets, and policy evaluation using advanced statistical methodologies. Melly’s articles span methodological advancements (e.g., fast algorithms for quantile processes) and applied analyses (e.g., gender wage gaps, public sector wage dynamics). He actively contributes to the academic community through editorial roles and software development.

• 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.

• Quantum Physics
• Semiconductor Physics
• Quantum Computing
• +۶ مورد دیگر

Dr. Christian Philipp Scheller is a Research Associate at the Department of of Physics, University of Basel, working within the Quantum Coherence Lab (Zumbühl Group). His research focuses on low-temperature quantum transport experiments, particularly in semiconductor nanostructures for quantum computing applications. The lab investigates spin qubits in materials like GaAs, Ge/Si nanowires, and graphene, with projects including microkelvin electronics, tunneling spectroscopy, and spin-orbit interaction studies. Scheller's work contributes to advancing qubit stability, coherence, and fabrication techniques. His publications span high-impact journals like Nature Communications and Physical Review Research , covering topics such as Luttinger liquids, Pauli spin blockade, and Coulomb blockade thermometry. The group's research intersects quantum physics, nanoelectronics, and machine learning for quantum device optimization. Key affiliations include the Swiss Nanoscience Institute (SNI), NCCR SPIN (Swiss national research program), and collaborations with institutions like ETH Zurich, Harvard University, and Delft University of Technology. The lab's experimental approach combines ultra-low temperatures (sub-millikelvin), magnetic fields, and advanced measurement techniques.