جستجوی استاد راهنمای دانشگاهی

Martin Oderskyمشاهده پروفایل

استاد

• Programming languages
• Object-oriented programming
• Functional programming
• +۶ مورد دیگر

Martin Odersky is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences, where he heads the Programming Methods Laboratory (LAMP1). He maintains dual teaching appointments in the Systems and Software Engineering (SIN) and Software and Systems Engineering (SSC) sections. Education: Doctorate from ETH Zurich (1989) Odersky's research fundamentally explores the unification of object-oriented and functional programming paradigms. His work spans language design, type theory, compiler construction, and semantic foundations, driven by the thesis that these paradigms are complementary facets of a single computational model. This vision materialized in the Scala programming language, engineered for seamless Java/.NET interoperability while advancing type-safe abstractions for modern software development. His publication trajectory (1997-2005) reveals consistent innovation in bridging theoretical rigor with industrial applicability. Key themes include component-based modularity (Scalable Component Abstractions), dependent type systems for objects, and practical implementations of generics and functional constructs, all converging toward expressive yet safe programming models. Advising and Funding: Odersky has mentored 29 PhD students across his career, including 5 current candidates. His research sustains major funding from the Swiss National Science Foundation, European Commission, and Hasler Foundation, enabling foundational work in language design and implementation. Laboratory: He directs EPFL's Programming Methods Laboratory (LAMP), which drives Scala's evolution and investigates next-generation programming abstractions for concurrency, modularity, and type-driven development.

Suryanarayana Sankagiriمشاهده پروفایل

پژوهشگر

• Discrete Choice Models
• Recommendation Systems
• Blockchain Security
• +۴ مورد دیگر

Suryanarayana Sankagiri is a postdoctoral researcher at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland, affiliated with the Information and Network Dynamics (INDY1) group under Professor Matthias Grossglauser. Previously, he earned his Ph.D. in Electrical & Computer Engineering (2018-2022) from the University of Illinois at Urbana-Champaign , where he was supervised by Bruce Hajek and participated in the Coordinated Science Lab . He also holds an M.S. in Electrical & Computer Engineering from the University of Illinois (2016-2018) and a B.Tech. in Electrical Engineering from the Indian Institute of Technology Bombay (2012-2016). Education : Ph.D., Electrical & Computer Engineering, University of Illinois (2018-2022) M.S., Electrical & Computer Engineering, University of Illinois (2016-2018) B.Tech., Electrical Engineering, IIT Bombay (2012-2016) Suryanarayana's research focuses on discrete choice models and their application to recommendation systems , with a particular emphasis on learning from choice data and developing novel models for human decision-making. His broader interests include blockchain security under adverse network conditions, network dynamics , probabilistic modeling , and algorithm design . Recent work explores nonconvex matrix factorization and contextual dueling bandits for recommendation systems. His publications span theoretical and applied domains, including high-impact venues like ICML , Stochastic Systems , and IEEE Transactions on Networking . Themes include blockchain efficiency , hidden community detection in preferential attachment graphs, and temporal analysis of Indian classical music. Current projects involve refining recommendation systems through sparse comparison data and designing protocols for resilient blockchain networks. Scientific Awards : zkCapital Paper of the Week (2021) Rambus Fellowship (2021) Mavis Future Faculty Fellowship (2019) List of Teachers Ranked as Excellent (2019) Nomination for IIT Bombay Undergraduate Colloquium (2016) Best Poster Award, IIT Bombay Undergraduate Research Symposium (2013) Suryanarayana has advised no students listed in the provided materials. His work has been supported by fellowships such as the Mavis Future Faculty Fellowship and Rambus Fellowship . He contributes to the INDY1 group at EPFL, which investigates information and network dynamics through interdisciplinary approaches combining probability , network theory , and algorithmic design .

• Aerosol science and technology
• Combustion-generated nanoparticles
• Ultrafine particle characterization
• +۴ مورد دیگر

Prof. Dr. Heinz Burtscher serves as Professor at the FHNW University of Applied Sciences Northwestern Switzerland since 1996, where he founded and led the Institute of Aerosol and Sensor Technology until 2018. Affiliated with the School of Engineering and Environment , he specializes in Aerosol Measurement Technology and Measurement and Sensor Technology with focus on combustion-generated nanoparticles, environmental aerosol monitoring, and sensor development for particulate matter analysis. PhD in Electrical Engineering (1980) from ETH Zurich Postdoctoral qualification in experimental physics (1991) on combustion aerosols His research interests span: Characterization of small particles from combustion processes (e.g., diesel soot, wood burning) Development of field measurement techniques for particle emissions Advancements in sensor technology for ambient air monitoring Toxicological evaluation of nanoaerosols Innovations in exhaust gas cleaning systems Recent publications address sub-23 nm particle measurement , e-cigarette vapor characterization , and real-time SOA formation potential in combustion emissions. He received the Smoluchowski award (1994) from the Gesellschaft für Aerosolforschung (GAeF) and maintains active membership in GAeF and the Swiss Aerosol Group. As both educator and researcher, Burtscher teaches Power electronics , Electrical drives , and Sensor systems while leading projects on: Volcanic ash detection systems Nanoparticle exposure assessment Vehicle cabin air filtration Periodic emission inspection protocols He works closely with the Institute for Sensors and Electronics at FHNW and collaborates with ETH Zurich's combustion research groups.

• Materials Science
• Mechanical Engineering
• Computational Mechanics
• +۳ مورد دیگر

Antoine Sanner is a Researcher affiliated with the Institute of Construction Materials (Institute of Building Materials) at ETH Zurich, part of the College of Architecture, Civil and Environmental Engineering. His work focuses on computational mechanics of building materials, surface topography analysis, and adhesion science. He co-developed the dtool and dserver systems to enhance FAIR data practices in research. Research interests include the structural behavior of cement-based materials, mechanisms of material adhesion under varying surface conditions, and multiscale analysis of surface roughness effects. He has also contributed to engineering tools for characterizing surface topography across scales, emphasizing the creation and use of 'digital surface twins' for material studies. His publications consistently explore topics at the intersection of materials science and mechanical engineering, with recent work advancing understanding of surface adhesion dynamics and cement curing processes. No scientific awards are explicitly mentioned in the provided texts. As part of the Professorship for Computational Mechanics of Building Materials, Antoine contributes to research infrastructure and computational methods development. He has no listed advisees or grants, and his role appears to be full-time with no indication of part-time status. He collaborates on projects involving advanced materials characterization, particularly in polycrystalline diamond coatings and bearing component analysis, leveraging both experimental and computational methodologies.

Michele Lanzaمشاهده پروفایل

استاد

• Software Engineering
• Software Visualization
• Software Evolution
• +۷ مورد دیگر

Michele Lanza is a Full Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), Lugano, where he co-founded the faculty in 2004. He is the founder and director of the Software Institute (since 2017) and leads the REVEAL research group, focusing on software visualization, evolution, and analytics. He holds a PhD from the University of Bern (2003), where he also earned his MSc (1999), and was a postdoctoral researcher at the University of Zurich. Research Interests: Software Engineering Software Visualization (notably the 'City Metaphor') Mining Software Repositories (MSR) Software Evolution and Analytics Program Comprehension Reverse Engineering and Architecture Recovery His recent publications (2023–2025) emphasize immersive software visualization in virtual reality, automated documentation, code refactoring, and empirical studies on developer behavior and documentation. There is a strong trend toward human-centric, visual, and data-driven approaches, often leveraging VR and interactive tools for deeper software understanding. Scientific Awards: Ernst Denert Award (2003) Credit Suisse Teaching Award (2007, 2009) Best Paper Awards (SANER 2024, VISSOFT 2022, ICPC 2016) Most Influential Paper Award (MSR 2010) Advising and Grants: Prof. Lanza has supervised over 13 PhD students and numerous MSc and BSc theses, fostering a vibrant research group. He leads multiple funded projects, including SNF grants (FORCE, TUML, INSTINCT, PROBE, ESSENTIALS, BIGDATA), FFL (CSRD), and industry R&D initiatives. Funding supports travel, hardware, software, and PhD positions, enabling cutting-edge research in software engineering. Labs and Teams: He leads the REVEAL research group and the Software Institute at USI, which serve as hubs for innovation in software visualization, mining, and evolution. These teams are highly collaborative, interdisciplinary, and active in top-tier conferences (ICSE, FSE, ICSME, MSR, VISSOFT).

• Digital Journalism
• Media Transformation
• Journalism and Technology
• +۷ مورد دیگر

Laura Angela Amigo is a postdoctoral researcher at the Institute of Media and Journalism (IMeG) within the Faculty of Communication, Culture, and Society at Università della Svizzera italiana (USI). She also serves as a senior lecturer in communication at the InfoCom Department, University of Lille, France. Her work bridges academic research and practical media innovation across Europe. PhD in Journalism and Communication, University of Neuchâtel, Switzerland Master's in Communication, University of UMLV, France (magna cum laude) Master's (maîtrise) in Law and Political Science, University of Nice, France (magna cum laude) Bachelor's in Political Science, University of Lyon 3, France (cum laude) Her research centers on the digital transformation of journalism, particularly how emerging technologies reshape news production and how media organizations engage audiences. She investigates the use of AI in journalism, ethical challenges in public communication, and participatory forms of local journalism. Her work combines qualitative and critical approaches to understand evolving media ecosystems. The 15 most recent articles reflect a strong trajectory in digital journalism, audience engagement, and ethical implications of AI in media. Keywords include Artificial Intelligence, Journalism, Communication, Ethics, Digital Media , and Public Communication . The subfields span AI ethics, immersive journalism, participatory practices, newsroom innovation, algorithmic transparency, and media democratization , showing a consistent focus on technology's societal impact on journalism. Scientific recognition includes competitive funding and formal qualification: Qualification for assistant professorship, French National Council of Universities (CNU) Funding from Swiss National Science Foundation (SNSF) Funding from French National Research Agency (ANR) EU Horizon 2020 project 'Diacomet' Research commissioned by Swiss Federal Media Commission (COFEM) Study funded by Initiative for Media Innovation (IMI) Laura Amigo actively advises and contributes to academic and policy-oriented research. She has led major funded projects and collaborated internationally. Though no formal students are listed, her leadership roles in research and teaching indicate mentorship capacity. She has delivered over 50 presentations and taught at universities in Switzerland, France, Belgium, and Italy, demonstrating broad academic engagement. She is affiliated with the Institute of Media and Journalism (IMeG) at USI, a hub for critical media studies and innovation. Her involvement in EU and national projects positions her within influential research networks focused on media ethics, digital transformation, and public communication.

• Distributed Software Systems
• Network Function Virtualization
• Formal Verification
• +۳ مورد دیگر

Patrick Eugster is a full professor at the Università della Svizzera italiana (USI) and leads the Software Systems (SWYSTEMS) group within the Computer Systems Institute . He has held academic positions at Purdue University, TU Darmstadt, and MIT as a visiting faculty. His research focuses on distributed software systems , addressing challenges in consistency, efficiency, and security in decentralized environments. Current affiliation: USI Faculty of Informatics Prior affiliations: Purdue University (2005-2016), TU Darmstadt (2014-2017), MIT (2012/2013) Research Interests Distributed Systems : Investigating reliable failure detection, deterministic data paths for 6G, and hybrid synchronous/asynchronous architectures. Network Innovation : Optimizing TCAM encoding, analyzing microbursts, and developing quantum network protocols. Security & Verification : Creating confidentiality-preserving mechanisms and formal verification approaches for distributed software. Scientific Contributions 2025: Best paper at TACAS on Horn clause validation 2025: IFIP Jean-Claude Laprie Award for dependable computing 2024: Key papers at IEEE Network, ACM PLDI, and IEEE INFOCOM Funding & Collaborations Swiss National Science Foundation grants #200021_197353 and #200021_192121 EU Horizon Europe MSCA staff exchange project CloudStars Industry partners: Cisco, Amazon AWS, Facebook Research, SAP, Northrop Grumman Cybersecurity Research Consortium Labs & Teams Directs the SWYSTEMS group, which includes postdocs like Sina Darabi and Shamiek Mangipudi, PhD students such as Anita Buckley and Jérôme Graf, and alumni who have become faculty at institutions like Télécom Paris and University of Southern California.

• Civil Engineering
• Computational Fluid Dynamics
• Porous Media Flow
• +۳ مورد دیگر

Dr. Luka Malenica is a dedicated researcher at ETH Zurich's Professorship for Durability of Engineering Materials, focusing on computational modeling of material degradation processes in civil infrastructure. His work bridges theoretical numerical methods with practical engineering applications through direct involvement in the department's research operations. His research program centers on multiphase flow in porous media , corrosion mechanisms in reinforced concrete , and advanced numerical techniques . He employs pore-scale direct numerical simulations to investigate steel-concrete interface phenomena, developing predictive models for infrastructure durability. His methodological innovations include control volume isogeometric analysis, adaptive multiresolution modeling, and deep learning applications for adaptive meshing—addressing challenges in heterogeneous media flow and transport phenomena. Analysis of his 15 most recent publications reveals a consistent research trajectory since 2015, with accelerating output in corrosion science (5 papers in 2024-2025) and computational methods (7 papers 2019-2022). Key interdisciplinary connections span civil engineering (corrosion in reinforced concrete), chemical engineering (bubble column reactors), and hydrology (karst aquifer modeling), unified by his expertise in numerical simulation of transport phenomena. Recent work demonstrates increasing sophistication in modeling macrovoid formation at steel-concrete interfaces and capillary-driven multiphase systems.

Fernando Pedoneمشاهده پروفایل

استاد

• Dependable Distributed Systems
• Distributed Algorithms
• Distributed Data Management Systems
• +۶ مورد دیگر

Fernando Pedone is a Full Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), leading the Computer Systems Institute (SYS). He holds a Ph.D. in Computer Science from EPFL (1999). His research focuses on dependable distributed systems, distributed algorithms, and fault-tolerant data management. Pedone has authored over 70 papers and co-edited 'Replication: Theory and Practice.' Roles: Full Professor, SYS Director Affiliations: USI, Swiss National Science Foundation (SNSF), Interchain Foundation Teaching: Distributed Algorithms, Distributed Systems, Operating Systems Research interests span atomic multicast protocols, state machine replication, blockchain synchronization, and consensus algorithms. His work bridges theoretical foundations with practical implementations, emphasizing scalability and fault tolerance. Pedone's projects are sponsored by entities like SNSF, CTI, and Microsoft Research. Notable contributions include 'Heron' (shared-memory state replication), 'PrimCast' (atomic multicast), and studies on blockchain state synchronization. His lab oversees over 20 PhD students, with alumni holding roles in academia and industry. Grants and collaborations include partnerships with the Hasler Foundation, European Commission, and Western Digital Research. Pedone actively participates in conferences like Middleware, DSN, and EuroSys.

• Seismology
• Geophysics
• Seismic Tomography
• +۵ مورد دیگر

Prof. Dr. Andreas Fichtner is a Full Professor of Seismology and Wave Physics at ETH Zurich's Department of Earth and Planetary Sciences. He leads research in seismic tomography, fiber-optic sensing, and high-performance computing, deploying innovative techniques for imaging Earth's interior. His work includes developing distributed fiber-optic sensing for seismic monitoring in urban areas, volcanoes, and glaciers. Beyond seismology, he explores applications in medical ultrasound imaging and metamaterial design. Research interests span seismic wave inversion, uncertainty quantification, and fiber-optic technology. Notable achievements include co-founding Mondaic, a spin-off providing full-waveform modeling solutions. Awards include the 2011 Keiiti Aki Award (AGU), 2015 Early Career Scientist Award (IUGG), and 2018 Hoffmann Prize. He currently serves on the Board of Directors of the Seismological Society of America. Key contributions include pioneering fiber-optic seismology in ice streams and volcanoes, advancing multi-scale inversion methods, and integrating seismic data for continental-scale tomography. His research bridges geophysics with engineering, medical imaging, and computational science.

Rainer Gabrielمشاهده پروفایل

پژوهشگر

• Gerontology
• Social Policy
• Life Course Analysis
• +۵ مورد دیگر

Dr. Rainer Gabriel is a researcher at the Zurich University of Applied Sciences (ZHAW) within the School of Social Work and Institute of Diversity and Social Integration . His work focuses on aging, poverty dynamics, and socioeconomic determinants of health, with a particular emphasis on labor force participation and welfare policies. Primary research areas: Gerontology, Social Policy, Life Course Analysis, Poverty Dynamics Key projects: Analyzing employment trajectories and cancer risks, evaluating Swiss disability action plans, studying cognitive reserve and neighborhood effects Publications: Frequent collaborations with Stéphane Cullati, Matthias Kliegel, and Michel Oris in journals like Scientific Reports and PNAS His recent work explores how lifetime socioeconomic conditions influence cognitive decline and frailty in old age, using longitudinal data from the SHARE study. Gabriel also investigates non-take-up of social benefits and the impact of leisure activities on cognitive health.

• Induced Seismicity
• Geothermal Energy
• Hydro-Geomechanical Modeling
• +۳ مورد دیگر

Dr. Vanille Ritz is a postdoctoral researcher at the Swiss Seismological Service (SED), ETH Zurich, with a split position between the Modelling Group and the GeoBest team. Her expertise lies in developing hydro-geomechanical and statistical models to understand and forecast induced seismicity in geothermal systems. She focuses on projects like GeoBest, which provides seismological support for Swiss geothermal energy initiatives, and has been a key contact for cantons Vaud, Jura, and Geneva. She holds a Ph.D. from ETH Zurich (2023) and a M.Sc. in Seismology from Université de Strasbourg (2017). Research interests include induced seismicity mitigation, geothermal reservoir engineering, and real-time seismic monitoring. Her work integrates data-driven approaches with physics-based models to optimize energy production while minimizing seismic risks. Notable contributions include the 'Transient Evolution of Earthquake Size Distributions' study (2022), recognized with the SSA Student Award. Education: Ph.D., ETH Zurich (2018–2023): Modelling Induced Seismicity in Deep Geothermal Systems M.Sc., Université de Strasbourg (2015–2017): Seismology Geophysical Engineering, Ecole et Observatoire des Sciences de la Terre (2014–2017) Professional activities include leadership in projects like DEEP (2021–2024), COSEISMIQ (2018–2021), and DESTRESS (2017–2018), advancing de-risking strategies for geothermal energy. Awards include the 2023 SSA Student Presentation Award for seismic risk indicator research. Her work bridges geoscience and engineering, emphasizing collaboration with cantonal governments and energy stakeholders to ensure sustainable geothermal development. Current efforts focus on synthetic benchmark datasets and real-time forecasting tools for induced seismicity management.

• Financial Economics
• Portfolio Optimization
• Stochastic Dominance
• +۵ مورد دیگر

Professor Wing-Keung Wong is a distinguished academic at the Department of Finance, Asia University . With over 187 scholarly papers and 638 citations, his work spans critical areas in financial economics and quantitative finance. Current affiliation: Asia University, Department of Finance Past affiliations: National University of Singapore, Chinese University of Hong Kong, Erasmus University Rotterdam Research Themes include: Portfolio optimization and stochastic dominance theory Market efficiency analysis across diverse financial instruments Behavioral finance and investor decision-making models Risk measurement with VAR and CVaR frameworks International financial market integration studies Quantitative trading system development Key Article Trends reveal consistent focus on empirical finance, mathematical modeling, and decision science applications in portfolio management and market anomalies.

Aya Kachiمشاهده پروفایل

دانشیار

• International Political Economy
• Energy Policy
• Statistical Methodology
• +۳ مورد دیگر

Prof. Dr. Aya Kachi is an Associate Professor at the University of Basel's Faculty of Business and Economics, specializing in International Political Economy and Energy Policy. Her research focuses on statistical methodology, public policy quality, and sustainable development. She holds a Ph.D. from the University of Illinois (2012), M.A. from Duke University (2004), and B.A. from the University of Tokyo (2002). She leads the Empirical Methodology Section of the Swiss Political Science Association and contributes to the Research Network Sustainable Future. Her work bridges energy governance and climate policy, emphasizing public attitudes and policy effectiveness. Recent research includes studies on consumer preferences for sustainable dairy products, GHG emission reduction strategies, and comparative analyses of coal regimes. Prof. Kachi's publications span climate policy, energy transitions, and institutional frameworks, with a focus on Switzerland and international contexts. She collaborates with institutions like SCCER-CREST and actively participates in academic networks, emphasizing empirical rigor and policy relevance.

Masashi Sugiyamaمشاهده پروفایل

استاد

• statistical machine learning
• weakly supervised learning
• learning from noisy supervision
• +۶ مورد دیگر

Masashi Sugiyama is a Professor at the Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, where he has been serving since 2014. He concurrently serves as the Director of the RIKEN Center for Advanced Intelligence Project (AIP) since 2016, leading research groups focused on fundamental AI technologies, AI applications, and social issues of AI. His academic journey began at Tokyo Institute of Technology, where he earned his Bachelor, Master, and Doctor of Engineering degrees in Computer Science in 1997, 1999, and 2001 respectively, before becoming an Assistant Professor and later Associate Professor at the same institution. Sugiyama's research primarily focuses on statistical machine learning, with particular expertise in weakly supervised learning, learning from noisy supervision, and learning under distribution shift. His work has established important theoretical frameworks for density ratio estimation, covariate shift adaptation, and non-stationary environments. He has developed numerous practical algorithms including KLIEP (Kullback-Leibler importance estimation procedure), uLSIF (unconstrained least-squares importance fitting), and LSDD (least-squares density difference), which have become standard tools in the machine learning community. Analysis of his recent publications reveals a strong emphasis on reliable and robust machine learning techniques that can handle imperfect supervision and data distribution changes. His work spans theoretical foundations, algorithm development, and practical applications across various domains including bioinformatics, anomaly detection, and dimensionality reduction. The recurring themes in his research include direct density ratio estimation methods, importance weighting techniques, and mutual information-based approaches for various machine learning tasks. Award for Science and Technology from the Japanese Minister of Education, Culture, Sports, Science and Technology (2022) Japan Academy Medal (2017) Japan Society for the Promotion of Science Award (2017) Faculty Award from IBM (2007) Nagao Special Researcher Award from the Information Processing Society of Japan (2011) Young Scientists' Prize for the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology Japan (2014) Sugiyama has served as program co-chair for major machine learning conferences including NeurIPS 2015, AISTATS 2019, and ACML 2010 and 2020. He has received prestigious fellowships including the Alexander von Humboldt Foundation Research Fellowship (2003-2004) and the European Commission Program Erasmus Mundus Scholarship (2006). He is the (co-)author of influential machine learning monographs including Machine Learning in Non-Stationary Environments (MIT Press, 2012), Density Ratio Estimation in Machine Learning (Cambridge University Press, 2012), Statistical Reinforcement Learning (Chapman & Hall, 2015), and Machine Learning from Weak Supervision (MIT Press, 2022). At RIKEN AIP, Sugiyama leads research initiatives focused on developing robust AI systems that can operate reliably in real-world conditions with imperfect data. His laboratory maintains an active software development effort, providing open-source implementations of many of his research contributions, which has significantly influenced both academic research and practical applications of machine learning.