جستجوی استاد راهنمای دانشگاهی

• Database Systems
• Information Retrieval
• Probabilistic Databases
• +۴ مورد دیگر

Martin Theobald is a Professor in the Department of Computer Science at the University of Luxembourg's Faculty of Science, Technology and Communications. Previously affiliated with University of Ulm, Germany, his research spans database systems, information retrieval, and knowledge extraction with over 120 publications since 2002. His work bridges theoretical database foundations with practical applications in large-scale data processing. His research focuses on: Probabilistic and uncertain database systems Stream processing frameworks (notably the AIR architecture) Knowledge extraction from heterogeneous data sources Integration of machine learning with database systems Efficient query processing for structured and semi-structured data Recent publications demonstrate an evolving research trajectory toward real-time data stream processing with machine learning integration. His work on the AIR (Asynchronous Iterative Routing) framework and its extensions (TensAIR, OPTWIN) addresses critical challenges in concept drift detection, neural network training on streaming data, and efficient resource utilization. These contributions sit at the intersection of database systems, distributed computing, and machine learning, with applications in knowledge graph construction and question answering systems. Martin Theobald has mentored numerous researchers including Mauro Dalle Lucca Tosi, Alessandro Temperoni, and Vinu E. Venugopal, who have become active contributors to the database community. His collaborative network spans institutions across Europe, with frequent partnerships with researchers from University of Ulm, Max Planck Institute, and other European universities. His laboratory work focuses on developing scalable systems for processing evolving data streams, with particular emphasis on creating lightweight architectures that maintain high performance while minimizing resource consumption. Current projects involve integrating knowledge graphs with real-time analytics and developing adaptive systems that can handle concept drift in streaming environments.

Ralf Wernerمشاهده پروفایل

استاد

• Computational Statistics
• Data Analysis
• Business Mathematics
• +۶ مورد دیگر

Professor Ralf Werner serves as Professor of Business Mathematics at the University of Augsburg, where he leads the Computational Statistics and Data Analysis working group within the Institute of Mathematics at the Faculty of Mathematics, Natural Sciences and Technology. His academic career spans both theoretical research and practical industry applications in quantitative finance. Werner's research interests encompass: Computational Statistics and Data Analysis Optimization under Uncertainty Financial Engineering and Risk Management Actuarial Science and Insurance Mathematics Portfolio Optimization and Asset Allocation His scholarly output demonstrates a consistent focus on robust mathematical methods applied to financial problems, particularly in replicating portfolios for insurance applications, credit risk modeling, and statistical approaches to financial risk management. Werner's publications appear in leading journals across operations research, mathematical finance, and actuarial science. Professional qualifications include his habilitation at the Karlsruhe Institute of Technology (2011) and doctorate from Friedrich-Alexander University Erlangen (2001). He maintains active industry connections through his role as Scientific Advisor for DEVnet since 2010. Werner serves as Internship Coordinator and DAV (German Actuarial Society) correspondent, supporting students pursuing actuarial careers. He is an active member of multiple professional organizations including the Society for Operations Research (GOR), German Mathematical Society (DMV), and German Society for Insurance and Financial Mathematics (DGVFM).

Fernand Hörnerمشاهده پروفایل

استاد

• Cultural Studies
• Media Studies
• Popular Culture
• +۷ مورد دیگر

Prof. Dr. habil. Fernand Hörner serves as Professor of Cultural Studies at Hochschule Düsseldorf within the Faculty of Social Sciences and Cultural Studies. He holds multiple significant leadership positions including Director of the Center for Digitalization and Digitality (Zentrum für Digitalisierung und Digitalität), Internationalization Commissioner, and Program Director of the MA Transforming Digitality. Additionally, he serves as Deputy Director of the Department of Media and Interaction at the Doctoral College of Universities of Applied Sciences NRW and as Speaker of the Working Group on Popular Culture and Media in the Society for Media Science. He is also the co-founder and co-editor of the Song Lexicon (Songlexikon). Prof. Hörner's research focuses on interdisciplinary analysis of popular culture, particularly music videos, examining the intersection of digital transformation and musical expression. His work explores voice as a semantic and aesthetic phenomenon, content analysis of user comments in digital spaces, and the theoretical frameworks for understanding media convergence. His methodological approach combines cultural theory, discourse analysis, and semiotics to investigate how popular culture forms meaning across different media platforms. His scholarly output reveals a consistent trajectory from his early work on dandyism and cultural identity toward contemporary digital culture and media convergence. The most recent publications demonstrate increasing focus on digital reception patterns, social media phenomena, and the transformation of musical culture in the digital age. His work maintains a strong theoretical foundation while engaging with contemporary cultural phenomena from music videos to viral social media gestures. Prof. Hörner has developed significant research infrastructure through the Song Lexicon project, which contains approximately 300 scholarly analyses of songs across various genres since the beginning of sound recording. This resource examines songs through multiple dimensions including historical context, cultural significance, reception history, and audiovisual presentation. His academic journey includes a habilitation at the University of Basel (2019), professorship at HSD since 2012, previous positions at Albert-Ludwigs-University Freiburg, and doctoral work on dandyism completed in 2007. His scholarly contributions span musicology, cultural studies, media theory, and digital humanities with particular attention to the interplay between visual and auditory elements in contemporary media culture.

Bin Dongمشاهده پروفایل

استاد

• Biomedical Imaging
• Machine Learning
• Artificial Intelligence
• +۹ مورد دیگر

Bin Dong is a Professor at the Beijing International Center for Mathematical Research (BICMR) and Deputy Director of the Center for Machine Learning Research (CMLR) at Peking University. He holds a Ph.D. in Mathematics from UCLA (2009), M.Sc. from National University of Singapore (2005), and B.S. from Peking University (2003). Current affiliations: BICMR (2023–present), CMLR (2022–present) Prior: Associate Professor at Peking University (2014–2022), Assistant Professor at University of Arizona (2011–2014), SEW Assistant Professor at UCSD (2009–2011) Research focuses on biomedical imaging (reconstruction/analysis, clinical decision-making), machine learning (PDE-Net, ODE-Net architectures), and AI for Mathematics (AI4M) (formal mathematics digitalization via Lean, AI-assisted theorem proving). Teaching includes Mathematical Image Processing and Learning by Research at Peking University. Key scientific awards: Wang Xuan Outstanding Young Scholar Award (2023) New Cornerstone Investigator (2023) Qiu Shi Outstanding Young Scholar Award (2014) Silver Medal, New World Mathematics Award (2007) Organized multiple workshops including the One World Seminar Series on Mathematics of Machine Learning and co-developed AI tools like Brainiac Buddy for education.

Daniel Peralta-Salasمشاهده پروفایل

استاد

• Dynamical Systems
• Partial Differential Equations
• Differential Geometry
• +۱۳ مورد دیگر

Daniel Peralta-Salas is a CSIC Research Professor and Chair of the Group 'Differential Geometry and Geometric Mechanics' at the Institute of Mathematical Sciences (ICMAT) in Madrid, Spain. ICMAT is a joint research institute of the Spanish National Research Council (CSIC) and several Madrid universities. He is an active researcher with leadership roles in the ICMAT board and multiple international advisory boards. PhD in Mathematics, Universidad Complutense de Madrid, 2006 His research lies at the intersection of dynamical systems , partial differential equations , and differential geometry , with applications in fluid mechanics, plasma physics, quantum mechanics, and mathematical physics. He has developed a unifying theory to study geometrically complex structures in physical models. His work includes proving long-standing conjectures by Arnold, Lord Kelvin, and Michael Berry, and constructing fluid flows that simulate universal Turing machines, thereby demonstrating undecidable dynamics in fluid particle paths. The most recent articles highlight his ongoing focus on steady Euler flows , topological obstructions in magnetic fields , optimal eigenvalue problems , and Turing universality in fluid dynamics . His publications span geometric analysis, spectral theory, and mathematical physics, often combining deep topological insight with PDE techniques. He has developed novel methods such as global approximation and inverse localization, which have broad implications across mathematical physics. His scientific awards include: ERC Starting Grant (2014–2019) Barcelona Dynamical Systems Prize (2015) Plenary Speaker, European Congress of Mathematics (2016) The Floer Lectures (2019) MINT Distinguished Lectures, Tel Aviv (2020) Plenary Speaker at major national and international mathematical societies (2021–2024) EMS Distinguished Speaker (2023) Peralta-Salas advises and collaborates extensively with researchers including Alberto Enciso, Robert Cardona, Eva Miranda, and others. His work has been supported by prestigious grants such as the ERC Starting Grant. He has published over 100 papers in top journals including Annals of Mathematics , Acta Mathematica , PNAS , and Physical Review Letters . He is a member of editorial boards for journals such as Revista Matemática Iberoamericana and Journal of Dynamics and Differential Equations , and serves on the scientific advisory board of IMTECH (UPC-Barcelona Tech). He leads the research group on Differential Geometry and Geometric Mechanics at ICMAT, which focuses on geometric structures in dynamical systems and PDEs. The group explores topics like Beltrami fields, vortex dynamics, and topological aspects of eigenfunctions. Their work is highly collaborative and interdisciplinary, bridging pure mathematics and theoretical physics.

• Mathematical Methods in Signal Processing
• Data Science
• Dynamical Systems
• +۵ مورد دیگر

Nada Sissouno is a Professor of Mathematics and Didactics of Mathematics at the Faculty of Electrical Engineering, Media and Informatics at Amberg-Weiden University of Applied Sciences since November 2023. She also serves as Vice Dean and Co-head of the Competence Center Grundlagen (CCG). Additionally, she maintains a position as a guest researcher at the Research Group: Applied and Numerical Analysis and Optimization and Data Analysis at the Technical University of Munich (TUM). Her educational background includes a Doctorate in Mathematics (Dr. rer. nat.) from TU Darmstadt (2007-2011) and a Diplom in Mathematics with a minor in psychology from TU Darmstadt (2000-2007). She has completed further education as a Diversity Manager in 2021 and holds certificates in teaching in higher education from the Bavarian Universities (2014-2016). Professor Sissouno's research focuses on mathematical methods in signal and image processing, data science, dynamical systems, numerical simulation, and approximation theory. Her work particularly emphasizes spline functions on domains, wavelets and frames, and evidence-based development of teaching methodologies. Her recent publications demonstrate strong expertise in mathematical imaging, phase retrieval problems, and approximation theory, with applications spanning ptychographic imaging, variational inpainting methods, and structural sparsity in multiple measurements. Her collaborative research bridges theoretical mathematics with practical applications in signal processing and image analysis, with a particular focus on developing robust numerical algorithms for complex data analysis problems. She has published in prestigious journals including Advances in Computational Mathematics, Journal of Fourier Analysis and Applications, IEEE Transactions on Signal Processing, and Inverse Problems. Referentin für Talentmanagement & Diversity at TUM (2022-2023) Deputy spokesperson of Research Associates' Council of the TUM (2019-2023) Gender equality officer of Department of Mathematics (2019-2022) Professor Sissouno teaches mathematics courses for engineering and computer science students, with a focus on making mathematical concepts accessible and relevant to practical applications. She has been involved in teacher training and the evidence-based development of teaching methodologies, demonstrating her commitment to both research excellence and educational innovation.

• Programming Languages
• Compilers
• Formal Verification
• +۷ مورد دیگر

Clément Pit-Claudel is an assistant professor at École Polytechnique Fédérale de Lausanne (EPFL), where he heads the SYSTEMF lab in the School of Computer and Communication Sciences. His research focuses on programming languages, compilers, and formal verification, with broader interests spanning systems engineering, hardware design languages, security, performance engineering, and type theory. Education: Undergraduate studies at École Polytechnique PhD at MIT with Adam Chlipala, specializing in proof-producing compilers Pit-Claudel's research program is organized around three main axes: extensible compilation (teaching compilers domain-specific optimization tricks), hardware design languages and verification (creating ways to describe and verify hardware), and tooling for proof assistants (to support verification efforts and lower entry barriers). His work bridges theoretical foundations with practical applications, as evidenced by algorithms from his Elk project being merged into V8 (and hence Chrome and Node.js). Scientific Awards: Distinguished artifact, Untangling Mechanized Proofs, ACM SIGPLAN International Conference on Software Language Engineering (2020) William A. Martin Memorial Thesis Award for Outstanding Thesis in CS, MIT (2016) Frederick C. Hennie III Teaching Award in Recognition of Outstanding Contributions to Departmental Teaching, MIT (2016) Pit-Claudel has extensive experience mentoring students through MIT's Undergraduate Research Opportunities Program and currently teaches Software Construction to approximately 400 undergraduate students and Interactive Theorem Proving at the graduate level. He's deeply committed to educational excellence, having developed innovative teaching methods including continuous assessment through oral examinations and designing assignments that lead students to build concrete artifacts they can be proud of. The SYSTEMF lab, created in January 2023, focuses on building "small, fast, and completely verified components for critical systems, at reasonable cost." The lab's philosophy of "full assurance, without compromise" combines machine-checked proofs of correctness, hardware-software co-design, low-level compiler engineering, and new tools for interactive theorem proving.

• Database Systems
• Data Management
• Machine Learning
• +۴ مورد دیگر

Tova Milo is a leading academic in database systems and data management at Tel Aviv University. Her research focuses on advancing automated data analysis, machine learning, and efficient data management techniques. She has contributed to systems like LINX (language-driven data exploration), TabEE (tabular embeddings explanations), and DPClustX (differentially private clustering explanations). Her work bridges database theory and practical applications, addressing challenges in fraud detection, crowdsourcing, and large language model utilization. Key contributions include: Development of systems for automated data exploration (e.g., ATENA, LINX) Foundations for explainable AI in databases (FEDEX, TabEE) Algorithms for category tree construction and cost-effective data processing Techniques for photo archiving under storage constraints She has received the 2022 TCDE Impact Award and actively contributes to top venues like SIGMOD, VLDB, and ICDE. Her research emphasizes balancing theoretical rigor with real-world applicability.

Anders Møllerمشاهده پروفایل

استاد

• Static Program Analysis
• Dynamic Program Analysis
• JavaScript
• +۵ مورد دیگر

Anders Møller is a Professor at the Department of Computer Science , Aarhus University , Denmark. His career spans roles as an author , committee member , and session chair in conferences like SPLASH, OOPSLA, ECOOP, ISSTA, ICSE, and PLDI. Affiliation: Aarhus University Co-founder: Coana Research Focus : Specializing in static and dynamic program analysis for JavaScript, TypeScript, Java, and Node.js applications, his work addresses: Pointer analysis precision in Java Race condition detection in Node.js Library evolution and semantic patching Soundness improvements in static analyzers Type safety in modern languages Concolic execution for web testing Publication Trends : Recent work (2021–2024) emphasizes security-critical static analysis (taint specifications, Node.js security), soundness optimization (approximate interpretation), and program verification (channel-based communication). Earlier work (2013–2018) includes foundational contributions to JavaScript refactoring , Dart type safety , and AJAX race detection . Scientific Recognition : ISSTA 2019 Distinguished Paper Award Leadership Roles : Active in steering committees for SPLASH, ECOOP, and SIGPLAN, with chairs in OOPSLA, ECOOP, and PLDI program committees.

• Stochastic Analysis
• Rough Path Theory
• Mathematical Finance
• +۵ مورد دیگر

Paul GASSIAT is a Lecturer at CEREMADE (Paris Dauphine University-PSL) and DMA (École Normale Supérieure, Paris). His research focuses on stochastic analysis, particularly rough path theory, stochastic PDEs, and applications to financial mathematics. 2011 PhD in Mathematics, supervised by Huyên Pham 2019 Habilitation (Authorization to supervise research) Research interests include: Pathwise stochastic analysis and regularization by noise Stochastic Hamilton-Jacobi equations Rough volatility modeling Applications to financial mathematics and machine learning optimization Scientific roles: JUNIOR MEMBER OF THE UNIVERSITY INSTITUTE OF FRANCE (2024-2029) Co-head of the MASEF Master program (2023/2024) Member of the editorial board of EJP/ECP (2020-) Member of the RT Matrisk office (2024-)

Thomas W. Repsمشاهده پروفایل

استاد

• Program analysis
• Abstract interpretation
• Model checking
• +۷ مورد دیگر

Thomas W. Reps is the J. Barkley Rosser Professor & Rajiv and Ritu Batra Chair in the Computer Sciences Department of the University of Wisconsin-Madison, where he has been a faculty member since 1985. He is also President of GrammaTech, Inc., which he co-founded in 1988 to commercialize research on programming environments. Reps received his Ph.D. in Computer Science from Cornell University in 1982, winning the ACM Doctoral Dissertation Award. His research spans program analysis, abstract interpretation, model checking, programming languages, and computer security. Reps's most influential work includes pioneering program slicing techniques with Susan Horwitz, development of the Cornell Program Synthesizer and Synthesizer Generator with Tim Teitelbaum, and significant contributions to interprocedural dataflow analysis. His recent work extends into quantum computing and advanced program synthesis techniques. The analysis of his publications reveals consistent focus on program analysis techniques, with recent papers exploring quantum circuit verification, abstract transformer synthesis, and program synthesis. His work bridges theoretical foundations with practical applications, often addressing scalability challenges in program analysis. NSF Presidential Young Investigator Award (1986) Packard Fellowship (1988) ACM Fellow (2005) ACM SIGPLAN Programming Languages Achievement Award (2017) Elected foreign member of Academia Europaea (2013) Multiple best paper awards including ETAPS (2004, 2008) Reps has advised numerous students, several of whom have received departmental and national recognition. His work on the Wisconsin Program-Slicing Tool led to commercial products through GrammaTech. He has served on advisory boards for significant projects including Year 2000 remediation for the Department of Defense and F/A-22 avionics software integration.

Julien Basteمشاهده پروفایل

دانشیار

• Algorithms
• Graph Theory
• Parameterized Complexity
• +۳ مورد دیگر

Julien Baste is an Associate Professor at the University of Lille, France, since September 2020. He teaches computer science at IUT de Lille (Institut Universitaire de Technologie de Lille) and conducts his research as a member of the ORKAD research team within CRIStAL (Centre de Recherche en Informatique, Signal et Automatique de Lille). Dr. Baste's research interests focus on theoretical aspects of computer science, particularly in Algorithms, reductions, graph theory, parameterized complexity, diversity, and multi-objective optimization. His work bridges theoretical foundations with practical applications, especially in optimization problems related to graph structures and computational complexity. An analysis of his recent publications reveals a consistent trajectory in parameterized algorithms and graph theory. His work frequently addresses problems parameterized by treewidth, developing fixed-parameter tractable algorithms for various graph problems. He has made significant contributions to understanding the complexity of graph modification problems, matchings, domination problems, and hitting set problems. His research has increasingly incorporated applications in areas like selective deconstruction and optimization of industrial processes, demonstrating the practical relevance of his theoretical work. Dr. Baste maintains an active research presence through numerous conference participations and collaborations with researchers across Europe. His research profile shows regular publication in top-tier theoretical computer science venues including SODA, IPEC, WG, and various IEEE conferences. The ORKAD research team at CRIStAL provides the institutional context for his ongoing research activities in algorithms and optimization.

Ulrike Bückingمشاهده پروفایل

مدرس ارشد

• Discrete Differential Geometry
• Conformal Geometry
• Discrete Surfaces
• +۳ مورد دیگر

Ulrike Bücking serves as a Senior Lecturer in the Department of Mathematics and Computer Science at Free University of Berlin, where she is Deputy Head of the Primary School Mathematics Group within the Discrete Methods in Algebraic Geometry & Mathematics for Teacher Training working group. Her academic responsibilities include teaching mathematical professional knowledge courses for primary school teacher candidates since 2019, with recent expansion to advanced specialized instruction for mathematics-focused teacher trainees. Her research spans two interconnected domains: theoretical discrete differential geometry focusing on convergence of discrete conformal mappings, rigidity of planar patterns, and discrete minimal surfaces; and mathematics education specifically tailored for primary school teacher preparation. This dual expertise manifests in publications ranging from pure mathematical investigations of circle patterns and discrete Riemann surfaces to innovative pedagogical frameworks for mathematics teacher education. Analysis of her 15 most recent publications reveals a consistent trajectory in discrete complex analysis with increasing integration of mathematics education research since 2020. Her geometric work demonstrates methodological evolution from foundational circle pattern theory toward sophisticated discrete surface constructions, while her educational publications address practical curriculum development for teacher training programs. The 2023 MatheProfIL paper exemplifies her applied approach to bridging theoretical mathematics with classroom pedagogy. Dr. Bücking maintained continuous research activity through her decade-long participation (2012-2024) in the Collaborative Research Center/Transregio 'Discretization in Geometry and Dynamics' (Project A01: Discrete Riemann Surfaces). Her teaching portfolio shows significant evolution from advanced mathematics courses for physicists at TU Berlin (2002-2018) to specialized mathematics education for primary teachers at Free University of Berlin. She actively contributes to the Primary School Mathematics Group and collaborates within the Discrete Methods in Algebraic Geometry & Mathematics for Teacher Training working group, maintaining an office at Arnimallee 3 in Berlin's mathematics institute where she supervises course development and coordinates teacher education initiatives.

Christoph Höllerمشاهده پروفایل

استاد

• Building Physics
• Architectural Acoustics
• Signal Processing
• +۵ مورد دیگر

Christoph Höller is a Professor for Applied Physics and Building Physics at OTH Regensburg, where he serves as Vice Dean of the Faculty of Applied Natural and Cultural Sciences (since 2021) and Chairman of the Examination Committee for Microsystems Technology/Sensor Technology and Analytics/Environmental and Industrial Sensor Technology (since 2019). He is also Head of the Building Physics Laboratory, which he leads together with Prof. Dr. Oliver Steffens. His research focuses on building acoustics, room acoustics, noise protection, and signal processing, with particular expertise in structure-borne sound, sound insulation, and vibration analysis. Höller's work bridges theoretical acoustics with practical building applications, contributing significantly to standards development through his involvement with NA 001-02-31 AA, NA 001-02-32 AA, NABau NA 005-55-75-04 AK, CEN/TC 126/WG 7, and ISO/TC 43/SC 2/WG 18. Höller's recent publications demonstrate his continued leadership in building acoustics, with focus areas including timber construction acoustics, reception plate methodology, transient noise assessment, and practical teaching methods. His work shows a consistent pattern of addressing both theoretical challenges and practical implementation issues in building physics. University Teaching Bavaria certificate from the BayZiel Didactics Center OTH Regensburg Award for Quality and Innovation in Teaching (2024) Teaching Innovation Funding at OTH Regensburg (2025-2027) Höller actively supervises student work, regularly offering topics for projects, bachelor's theses, and master's theses primarily in building physics. His Building Physics Laboratory is available for consultations, measurements, and contract research projects. Current research projects include SPlanRoB and AkuPap, focusing on practical applications of building acoustics principles.

• Theoretical Computer Science
• Algorithms
• Approximation Algorithms
• +۷ مورد دیگر

Shaofeng Jiang is an Assistant Professor at Peking University, affiliated with the School of Computer Science and the Center on Frontiers of Computing Studies. He previously held an assistant professor position at Aalto University and was a postdoctoral researcher at the Weizmann Institute of Science under Robert Krauthgamer. He earned his PhD from the University of Hong Kong under Hubert Chan and completed his bachelor's at Shandong University. PhD: University of Hong Kong, supervised by Hubert Chan Bachelor's: Shandong University His research lies in theoretical computer science, focusing on algorithm design for massive and high-dimensional data. Key interests include approximation algorithms, online algorithms, streaming algorithms, clustering, coresets, and dimensionality reduction. His work often bridges theoretical guarantees with practical applications in distributed and parallel computing environments. The recent publications reveal a strong trend in developing efficient and scalable algorithms for clustering problems, particularly through coreset construction, dimensionality reduction, and distributed models like MPC. There is a growing emphasis on fairness, robustness, and dynamic settings, indicating a forward-looking research agenda in adaptive and responsible algorithmic systems. He actively mentors PhD students and teaches both undergraduate and graduate courses in programming and computational social science. He has served on program committees for top conferences including NeurIPS, ICML, and STOC, and co-organized a Dagstuhl seminar on clustering. Scientific Service and Leadership: Co-organizer, Dagstuhl Seminar on New Trends in Clustering (2026) Area Chair, NeurIPS 2024 and 2025 Program Committee, IPDPS 2019, SWAT 2022, COCOA 2024, ICALP 2026 He has received no explicitly mentioned scientific awards. His grants and funding sources are not detailed in the text. He leads a research group focused on theoretical foundations of data-efficient algorithms, collaborating with students on cutting-edge problems in high-dimensional and streaming data analysis.