Find Academic Supervisors

• Graph-based learning
• Adaptation and learning in non-stationary environments
• Intelligence for embedded systems
• +5 more

Cesare Alippi is a Full Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), and also holds a professorship at Politecnico di Milano, Italy. He serves as a visiting Professor at Guangdong University of Technology (China) and Consultant Professor at Northwestern Polytechnic of Xi'an (China). His academic leadership extends to multiple international institutions where he has served as a visiting researcher including UCL (UK), MIT (USA), ESPCI (France), CASIA (China), A*STAR (Singapore), and University of Kobe (Japan). Professor Alippi's research interests center around graph-based learning, adaptation and learning in non-stationary environments, and intelligence for embedded, cyber-physical systems and IoT. His work bridges theoretical foundations with practical applications in sensor networks, environmental monitoring, and industrial processes. He has established significant research infrastructure including the Wireless Embedded Systems (WEmSy) Lab and the Internet of Things Lab, with notable deployments for marine environment monitoring in Queensland, Australia and the Fiji Islands, as well as rockfall and landslide monitoring systems across Italy and Switzerland. His research output shows a clear evolution toward graph-based deep learning approaches for time series analysis, anomaly detection, and spatiotemporal forecasting, reflecting the growing importance of graph neural networks in handling complex relational data in non-stationary environments. Major Awards: IEEE CIS Enrique Ruspini Meritorious Service Award (2024) IEEE CIS Outstanding Computational Intelligence Magazine Paper Award (2018) Gabor Award from International Neural Network Society (2016) IBM Faculty Award (2013) IEEE Instrumentation and Measurement Society Young Engineer Award (2004) Professor Alippi has held significant leadership roles including Past Board of Governors member of the International Neural Network Society, Past member of the Administrative Committee of the IEEE Computational Intelligence Society, and Past Vice-President for Education of the IEEE Computational Intelligence Society. He has served as Associate Editor for Proceedings of IEEE and several other prestigious journals. His research has been supported through numerous grants including an IBM Faculty Award in 2013 specifically for research on Intelligent Embedded Systems working in non-stationary environments. His research infrastructure includes the Wireless Embedded Systems (WEmSy) Lab and the Internet of Things Lab, with notable deployments including a sophisticated automatic, adaptive, sustainable and reliable wireless monitoring system for marine environments deployed in Queensland, Australia (2007) and under deployment at the Fiji Islands (2014-2015). He has also led several top-world deployments for rockfall and landslide monitoring across Italy and Switzerland since 2010, demonstrating the practical impact of his research in real-world harsh environments.

Ola SvenssonView profile

Associate Professor

• Approximation Algorithms
• Combinatorial Optimization
• Computational Complexity
• +3 more

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.

• Climate Policy
• Energy Economics
• Environmental Economics
• +3 more

Florian Landis is a Researcher at the Center for Energy and Environment within the School of Management and Law at Zurich University of Applied Sciences (ZHAW). His work focuses on the distributional impacts of energy and climate policy , particularly examining how carbon pricing mechanisms affect different socioeconomic groups in Switzerland. Previously, he held postdoctoral research positions at ETH Zurich (2015-2021) and ZEW Mannheim (2013-2015), and worked as a Short Term Consultant at the World Bank Group (2012). His educational background includes a Doctor of Science (2009-2012) and Master of Science in Physics (2001-2007), both from ETH Zurich. This interdisciplinary foundation enables his unique approach to energy economics problems. Landis specializes in computable general equilibrium modeling applied to climate policy analysis, with particular expertise in carbon pricing, decarbonization pathways, and policy design for energy transitions. His research frequently addresses the tension between policy efficiency and equity considerations, examining how different carbon tax designs impact welfare distribution across households. His publication portfolio shows a clear evolution from computational neuroscience (early work) toward energy economics and climate policy modeling. Recent work focuses on Swiss decarbonization scenarios, with consistent themes of carbon pricing efficiency, distributional impacts, and integrated energy-economic modeling approaches across multiple publications since 2017. Current research projects include: Renewable Fuels and Chemicals for Switzerland (Team member), Integrating very high shares of decentralized renewable energy into the Swiss energy system: Electricity market design and policy (Co-project leader), and DEcarbonisation of Cities and Regions with Renewable GAses (Team member).

• Deep Learning
• Statistics
• Data Science
• +4 more

Matthias Nyfeler is a Lecturer for Physics and Statistics at the Institute of Computational Life Sciences, Zurich University of Applied Sciences (ZHAW), since 2018. He previously served as a Lecturer at Jönköping University (2016-2018) and as a High School Teacher in Physics and Mathematics (2010-2016). His roles include Programme Director for the MSc specialisation in Applied Computational Life Sciences, Head of the Research Group Advance Signal Analytics, and Head of ICLS statistical consulting. Education: PhD in Theoretical Physics (University of Bern, 2005-2010), Master of Science in Physics (University of Bern, 2006-2009), Teaching Diploma for Physics and Mathematics (PHBern, 2010-2011), Postgraduate Studies in Secondary Education (Jönköping University, 2016-2017). His research focuses on Deep Learning and Statistical Signal Processing for applications like Drone Signal Classification and Bioacoustics . He also contributed to Quantum Antiferromagnetism and Cluster Algorithms earlier in his career. His recent publications highlight Robust CNN-based Drone Detection in low SNR environments and Multiscale Deep Learning for RF signal analysis. He led projects such as ChirpNet for AI biodiversity monitoring and TinyML Grasshopper Classifier. Matthias engages in Statistical Consulting and Mathematical Modeling , with a focus on Physical Computing and Radio Signal Processing . His work spans both academic research and applied technology development, including datasets for drone signal classification.

• Computational Linguistics
• Natural Language Processing (NLP)
• Language Model Interpretability
• +4 more

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)
• +4 more

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.

• Transportation and Logistics
• Vehicle Sharing Systems
• Vehicle Routing Problems
• +4 more

Ataç Selin is a Researcher at the University of Applied Sciences and Arts Western Switzerland (HES-SO), affiliated with the Interdisciplinary Institute for Business Development (IIDE) at HEIG-VD. She holds a PhD in Transportation Science from EPFL (2023) and focuses on optimizing vehicle sharing systems, logistics, and sustainable urban mobility. Her work integrates simulation-optimization frameworks to address challenges in bike/car sharing systems, electric vehicle infrastructure, and craft beer distribution logistics. Education: PhD in Transportation Science (2023), École Polytechnique Fédérale de Lausanne (EPFL) MSc in Operations Research (2016), Middle East Technical University (METU) BSc in Industrial Engineering (2013), Middle East Technical University (METU) Research Interests: Her research spans vehicle routing optimization, demand forecasting in transportation networks, and decision-making frameworks for sustainable systems. She has pioneered a holistic management framework for vehicle sharing systems, emphasizing rebalancing strategies, clustering algorithms, and environmental impact mitigation. Key Projects: "Craft Beer Distribution Optimization" (2024), funded by Innosuisse, focuses on collaborative logistics platforms for Swiss craft breweries. "Light Electric Vehicle Sharing Systems" (2024), developing decision support tools for EV infrastructure. Awards: Recipient of the EPFL EDCE Mobility Award (2021) for contributions to VSS optimization and the METU Best Graduate Performance Award (2016).

• Energy Policy
• Renewable Energy Systems
• Sustainable Development
• +3 more

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.

• Urban Transportation Systems
• Autonomous Mobility-on-Demand
• Vehicle Repositioning
• +4 more

Pengbo Zhu is a researcher at the École polytechnique fédérale de Lausanne (EPFL), specifically affiliated with the Laboratory of Urban Transport Systems (LUTS) within the School of Architecture, Civil and Environmental Engineering (ENAC). His work focuses on developing innovative control algorithms to address critical challenges in urban transportation systems, particularly in the domain of Autonomous Mobility-on-Demand (AMoD) and ride-hailing services. Dr. Zhu's research interests center around vehicle repositioning strategies, hierarchical control frameworks, and data-enabled predictive control methods for optimizing urban mobility. His work bridges transportation engineering with control systems theory, developing solutions that balance passenger demand with vehicle supply in dynamic urban environments. He has made significant contributions to coverage control algorithms that align vehicle distribution with demand patterns across city districts. Analysis of his publication trends shows a consistent focus on hierarchical control approaches for vehicle repositioning, with increasing sophistication from 2022 to 2025. His research has evolved from basic coverage control methods to integrated multi-layer frameworks that combine macroscopic traffic modeling with microscopic vehicle guidance, demonstrating both theoretical depth and practical applicability in real-world urban networks. Dr. Zhu's work has been supported by prestigious funding sources including the Swiss National Science Foundation and the European Union's Horizon 2020 program. His research demonstrates strong potential for practical implementation, with simulations conducted on real urban networks (particularly Shenzhen, China) showing significant improvements in key performance metrics like passenger waiting times and service rates. As an active researcher at EPFL, Dr. Zhu collaborates extensively with Professor Nikolaos Geroliminis and other researchers in the urban transportation field. His work contributes to the development of more efficient, sustainable urban transportation systems that benefit customers, service providers, and the environment through optimized fleet operations in mobility-on-demand services.

Tania Manríquez RoaView profile

Research Fellow

• Bioethics
• Public Health Ethics
• Global Health
• +5 more

Tania Manríquez Roa is a postdoctoral research fellow at the University of Zurich's Institute of Biomedical Ethics (IBME), specializing in contemporary ethical challenges in global health and research ethics. She serves as Academic Coordinator for the Forum for Global Health Ethics (since 2019) and Scientific Coordinator of the Centre for Medical Humanities (since 2024). PhD in Bioethics, University of Zurich MA in Global Ethics, King’s College London BA in Social Anthropology, University of Chile Her research focuses on global health ethics , public health equity , and ethical dilemmas in AI applications . She examines issues such as vaccine distribution during pandemics , self-experimentation , and mercury-related health hazards in artisanal gold mining. Recent work explores psychedelic ethics and financial incentives in health research . Tania’s publications emphasize health equity in pandemic triage guidelines, COVAX-related vaccine distribution challenges , and ethical AI integration in healthcare. She critiques opaque algorithms in mental health apps and advocates for context-sensitive ethical frameworks . Scholarship recipient, University of Zurich CONICYT Chile scholarship Recognized for top entrance scores at University of Chile As a policy consultant, she has collaborated with the World Health Organization , UNICEF , and ETH Zurich on projects addressing equitable pandemic preparedness and mercury-related health risks . Her fieldwork spans Chile, Mexico, Mozambique, and Switzerland .

• Renewable Energy
• Energy Systems Optimization
• Thermal Energy Storage
• +4 more

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
• +6 more

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.

Matija PiškorecView profile

Researcher

• Machine Learning
• Complex Systems
• Statistical Inference
• +5 more

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
• +5 more

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
• +4 more

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.