جستجوی استاد راهنمای دانشگاهی

Claudia Plant is a Professor in the Faculty of Computer Science , leading the Research Group Data Mining and Machine Learning . Her research focuses on clustering algorithms, data mining, and machine learning applications in areas like biomedical data, wind energy, and causality inference. She has contributed to projects such as Knowledge-infused Deep Learning for Natural Language Processing (2020–2028) and Hybrid Computational Sciences (2021–2021). Plant has authored over 160 publications, with recent work emphasizing deep learning, anomaly detection, and GPU-optimized algorithms. She actively engages in academic activities, including talks on clustering methods and interdisciplinary projects like Governing Algorithms: The Politics of Data and Decision-Making . Her research interests span clustering algorithms , graph neural networks , causality discovery , and ethical digital transformation . Notable projects include causal analysis of wind farm dynamics and AI-enhanced education tools. Plant’s work bridges computational methods with societal challenges, such as empowering marginalized communities through ethical technology adoption.

• Data Mining
• Machine Learning
• Clustering Algorithms
• +۶ مورد دیگر

Andrei Khrennikov is Professor of Mathematics at the Department of Mathematics, Linnaeus University, where he also serves as director of the International Center for Mathematical Modeling (ICMM) . He leads a vibrant research group focused on interdisciplinary modeling in physics, biology, cognition, and social systems. Research Interests: His work spans a vast interdisciplinary landscape, including mathematical physics, p-adic and non-Archimedean analysis, quantum foundations, quantum-like modeling of cognition and decision-making, econophysics, and biological dynamics . He is a pioneer in applying quantum probability and formalism outside quantum physics, especially in psychology and social sciences. The Växjö series of quantum theory conferences , which he organizes, is the longest-running continuous conference series on quantum foundations, fostering dialogue between theorists, experimentalists, and philosophers. His recent publications (2021–2025) show a strong focus on quantum cognition, p-adic biology, entanglement models, and social laser theory , often leveraging generalized probability and open quantum systems frameworks. Scientific Contributions: Developed quantum-like models for cognition, decision-making, and biological processes. Pioneered use of p-adic and ultrametric analysis in genetics and brain dynamics. Advanced classical random field models as alternatives to quantum interpretations. Introduced the social laser model for collective emotional amplification in societies. He is actively involved in major research projects such as QUARTZ (Quantum Information Access and Retrieval Theory) and DYNALIFE (Information, Coding, and Biological Function) . His work bridges mathematics, physics, and cognitive science, promoting a unified framework for understanding complex systems through quantum-inspired tools.

• Mathematics
• Physics
• Biology
• +۲۳ مورد دیگر

James R. Lee is a Professor in the Department of Computer Science at the University of Washington. His research spans theoretical computer science, probability, and geometry. He has held visiting scientist roles at Microsoft Research (2023, 2018, 2017) and participated in programs at the Simons Institute (2023, 2020, 2018, 2017, 2014). Research Interests: Algorithms, complexity theory, convex optimization, metric embeddings, spectral graph theory, probability, stochastic processes, and the interplay between discrete and continuous analysis. Teaching: Courses on modern algorithms, quantum computing, optimization theory, and spectral methods in theoretical computer science. Scientific Contributions: Developed sparsification algorithms for generalized linear models and norms with near-linear size guarantees (STOC'24, FOCS'23). Extended Cheeger-type inequalities to higher eigenvalues (STOC'12, STOC'18). Proved super-polynomial lower bounds for LP/SDP relaxations in constraint satisfaction (STOC'15, FOCS'13). Disproved Benjamini-Papasoglou conjectures on annular separators (Discrete Comp. Geom. 2024). Advanced understanding of random walks in geometric and unimodular graphs (Israel J. Math. 2023, GAFA 2023). Scientific Awards: Best Paper Award, STOC 2015

• Algorithms
• Computational Complexity
• Convex Optimization
• +۴ مورد دیگر

Anna Beer is a researcher in the Faculty of Computer Science, specializing in data mining and machine learning with a focus on density-based clustering, spectral clustering, and interactive clustering frameworks. She holds a BSc and MSc in computer science and maintains an ORCID profile (https://orcid.org/0000-0002-6890-997X) for her research contributions. Research Themes: Development of clustering algorithms (e.g., DISCO, Scar, LUCKe), fairness in density-based clustering (FairDen), and applications to molecular dynamics and climate research (DROPP). Collaborations: Works with colleagues like Ira Assent, Christian Plant, and Lars Krieger, with recent contributions to conferences like ICLR 2025. Activities: Presented research on density-connectivity distance at a 2023 oral contribution. Publications: 9 publications since 2019, including 3 in 2025 and 6 in 2024, covering topics from cluster evaluation to deep active learning strategies.

• Data Mining
• Machine Learning
• Clustering Algorithms
• +۳ مورد دیگر

Debarati Das is an Assistant Professor in Computer Science and Engineering , specializing in Clustering Algorithms , Edit Distance , and Approximation Algorithms . Her research focuses on theoretical computer science, particularly in algorithm design for data streams, permutation clustering, and sequence alignment. Grants: NSF CAREER Award (2024), NSF Student Travel Grant (2023). Her work includes breakthroughs in consensus clustering, achieving sub-2-approximation, and developing space-efficient algorithms for edit distance in distributed models. Recent projects explore dynamic shortest paths in planar graphs and pseudorandomness extraction. Her publications span journals like the Journal of the ACM and conferences such as SODA, STOC, and FOCS. Collaborations include researchers from institutions in the U.S. and Europe, with applications in computational biology and parallel computing.

• Clustering
• Edit Distance
• Approximation Algorithms
• +۹ مورد دیگر

Dr. Carlo Cavicchia is an Assistant Professor of Statistics at the Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam. He holds a PhD in Methodological Statistics from La Sapienza University of Rome and has held roles such as Research Fellow at UnitelmaSapienza University and Consultant for NGOs in Zanzibar. His research focuses on latent variable models, composite indicators, and unsupervised classification, with applications in environmental policy, sports analytics, and teacher job satisfaction. Cavicchia teaches statistics and data science courses at undergraduate and graduate levels and actively contributes to academic communities through journal reviewing, conference organizing, and editorial roles. Education: PhD in Methodological Statistics (La Sapienza University of Rome, 2020) MSc in Statistics and Decision Sciences (La Sapienza University of Rome, 2016) BSc in Statistics (La Sapienza University of Rome, 2013) Dutch University Teaching Qualification (BKO, 2022) Research Interests: Cavicchia’s work emphasizes hierarchical models, non-parametric statistics, and data science applications. He develops methodologies for composite indicators, including ultrametric Gaussian mixture models and disjoint principal component analysis. His research bridges theoretical advancements with real-world problems, such as waste management in Italian municipalities and ranking European football teams using composite metrics. Grants & Awards: 2024: IFCS Chikio Hayashi Award 2023: ESE Starter Grant (€300,000) 2017: Research Grant for Junior Researchers (€1,270) 2016: PhD Scholarship, La Sapienza University Academic Engagement: Cavicchia serves as IASC Data Analysis Competition Officer (2023–2025), co-edits the ISI Magazine , and organizes conferences like DSSV 2020 and DSSV-ECDA 2021. He is an elected member of the International Statistical Institute and contributes to SVQS’s Sustainability initiatives. Labs & Teams: He co-organizes the Econometrics internal seminars at Erasmus University and collaborates with researchers at University of Naples Federico II on hierarchical models and convex clustering.

• Statistics
• Data Science
• Machine Learning
• +۶ مورد دیگر

Jayadev S. Athreya is a Professor of Mathematics and Comparative History of Ideas at the University of Washington. He also serves as co-Director of the Pacific Institute for the Mathematical Sciences (PIMS) and founder of the Washington Experimental Mathematics Lab. His research focuses on ergodic theory, dynamical systems, geometry, and number theory, with a particular emphasis on translation surfaces, billiards dynamics, and moduli spaces. He holds a PhD from the University of Chicago (2006) and has been actively involved in promoting mathematical education and outreach. Axioms emphasizing equitable and joyful mathematics experiences guide his work. Education: PhD in Mathematics, University of Chicago, 2006 Research Interests: Athreya’s interdisciplinary work bridges geometry, dynamics, and number theory. Key areas include the study of billiards in polygons, Teichmüller theory, and the statistical properties of geodesics on hyperbolic surfaces. His contributions to translation surfaces and counting problems in geometry have advanced understanding of moduli spaces and extremal cocycles. Labs/Teams: He leads the Washington Experimental Mathematics Lab, fostering collaborative research through hands-on projects in geometry and combinatorics. The lab emphasizes creativity and inclusivity in mathematical exploration. Grants/Advising: While specific grants are not detailed, his leadership roles and active research output indicate sustained funding and mentorship in experimental mathematics and education initiatives.

• Ergodic Theory
• Dynamical Systems
• Geometry
• +۳ مورد دیگر

Reinhard Pichler is a Full Professor at the Vienna University of Technology (TU Wien), affiliated with the Faculty of Informatics and the Department of Databases and Artificial Intelligence . His research focuses on Database Theory , Computational Logic , and Parameterized Complexity . He leads multiple research projects like DeConquer (2023–2027) and HyperTrac (2018–2022), addressing challenges in query optimization and hypergraph decompositions. He holds the prestigious START Prize (2014–2022) for young researchers. His work spans theoretical foundations (e.g., hypertree decompositions) and practical applications (e.g., SPARQL query processing systems like SparqLog). He contributes to academic governance, serving on faculty councils and curriculum commissions. His research innovations bridge algorithmic theory and real-world database systems, emphasizing efficient query evaluation and tractability analysis. Key contributions include advancing fractional hypertree decompositions , SPARQL query optimization , and consistent query answering . His projects often involve collaborations with industry and international funders like the Austrian Science Fund (FWF) and Vienna Science and Technology Fund (WWTF). He actively publishes in top venues like Journal of the ACM , ACM Transactions on Database Systems , and Proceedings of the VLDB Endowment . His academic leadership extends to course design, teaching advanced topics like Complexity Theory and Theoretical Computer Science . He mentors doctoral students and oversees research teams exploring cutting-edge areas like uncertain databases and cloud-based computational social choice .

• Database Theory
• Computational Logic
• Parameterized Complexity
• +۴ مورد دیگر

Alberto Marcone is a Full Professor of Mathematical Logic at the University of Udine, where he serves as the Director of the Department of Mathematical, Computer and Physical Sciences (DMIF) since October 1, 2024. His academic home is within the Department of Mathematical, Computer and Physical Sciences at the University of Udine, located at Via delle Scienze, 208 -- Loc. Rizzi, 33100 Udine, Italy. Professor Marcone's research spans several interconnected areas within mathematical logic. His primary interests include reverse mathematics, descriptive set theory, well-quasi-order and better-quasi-order theory, and computable analysis with particular emphasis on the Weihrauch lattice. His work explores the logical strength of mathematical theorems, classification problems in continuum theory, and the computational content of mathematical principles. He has made significant contributions to understanding the relationships between different mathematical principles and their proof-theoretic strength. Analysis of his recent publications reveals a consistent focus on the intricate connections between order theory, reverse mathematics, and descriptive set theory. His work often examines the logical strength of combinatorial principles related to well-quasi-orders and better-quasi-orders, while increasingly exploring connections to computable analysis through the Weihrauch lattice framework. Recent publications demonstrate growing international collaboration, particularly with researchers across Europe, and an expanding application of logical methods to topological and metric space problems, including connections to knot theory and fractal geometry. Member of editorial board of the journal Computability Member of the board of the PhD program in Mathematics and Physics Organizer of Logic Colloquium 2018 (Udine) Organizer of Special Session on Computability Theory at AMS-UMI International Joint Meeting (Palermo, July 2024) Organizer of XXVIII Incontro di Logica AILA (Udine, September 2024) Professor Marcone teaches Mathematical Logic for both undergraduate and graduate mathematics programs at the University of Udine. His office is located on the 2nd floor, room A2 90, where he holds student reception hours either in person or via Microsoft Teams by appointment. As department director, he oversees the academic and administrative functions of the Department of Mathematical, Computer and Physical Sciences.

• Mathematical Logic
• Reverse Mathematics
• Descriptive Set Theory
• +۴ مورد دیگر

Patrice Koehl is a full-time Professor in the Department of Computer Science at the University of California, Davis. His research bridges computational biology, structural bioinformatics, and theoretical biophysics, focusing on geometric and physical modeling of biomolecular systems. He has made significant contributions to protein structure prediction, ion channel modeling, and development of computational methods for molecular simulations. Research interests include: Geometric modeling of biological macromolecules Optimal transport theory for shape analysis Statistical mechanics in biomolecular simulations Topological data analysis for cellular morphology Multi-scale modeling of viral structures Recent research trends show strong emphasis on: Protein conformational transitions using action minimization Persistence diagrams for morphological signatures Geometric approaches to assignment problems Computational methods for macromolecular surface analysis Interdisciplinary applications of physics to biological data

• Computational Biology
• Structural Bioinformatics
• Molecular Modeling
• +۴ مورد دیگر

Konrad Aguilar is an Assistant Professor of Mathematics and Statistics at Pomona College, currently on sabbatical for the 2025-2026 academic year. He holds a PhD in Mathematics from the University of Denver (2015), an M.S. in Mathematics from the same institution, and a B.S. in Applied Mathematics from California State Polytechnic University, Pomona. His research focuses on noncommutative/quantum metric geometry, blending tools from functional analysis, operator algebras, and metric geometry to study convergence of operator algebras and finite-dimensional approximations. Research Interests include compact quantum metric spaces, Quantum Gromov-Hausdorff convergence, finite-dimensional approximations, and compact quantum groups. His work has led to contributions in areas such as AF algebras, Podleś spheres, and quantum ultrametrics. He has collaborated with leading mathematicians like Frédéric Latrémolière and Jens Kaad, producing influential papers in Studia Mathematica , Journal of Operator Theory , and Journal of Geometry and Physics . Awards include the MAA Project NExT fellowship (2021-2022) and the AMS-Simons Travel Grant (2019-2022). He actively mentors undergraduates in matrix analysis and finite-dimensional algebraic structures, bridging foundational theory with advanced research. His articles explore topics such as quantum metric spaces, spectral triples, and convergence in noncommutative geometry, reflecting a deep engagement with both pure mathematics and its applications in quantum frameworks. Recent work includes studies on Podleś sphere spectra and quantum metrics on tensor products of C*-algebras.

• Noncommutative Geometry
• C*-algebras
• Quantum Metric Spaces
• +۴ مورد دیگر

James R. Lee is a Professor in the Department of Computer Science at the University of Washington, with a focus on algorithms, complexity, and the theory of computation. He is affiliated with the UW Theory Group and currently on leave at Microsoft Research, which may delay responses to UW emails. Research Interests: Algorithms, complexity, geometry/discrete-continuous interfaces, probability, stochastic processes, metric embeddings, spectral graph theory, convex optimization. Recent Work Trends: Sparsification of generalized linear models and norms, spectral hypergraph methods, entropic regularization for metrical task systems, and analysis of scaling exponents in random graphs. His papers address sparsifier existence, lower bounds for SDP/LP relaxations, and geometric random walk properties. Scientific Awards: Best Paper Award at STOC 2015. Students: Farzam Ebrahimnejad, Ewin Tang, Yichuan Deng (co-advised with Shayan Oveis-Gharan, Shirshendu Ganguly, and others). Email: jrl@cs.washington.edu

• Algorithms
• Complexity Theory
• Probability
• +۵ مورد دیگر

Franz-Viktor Kuhlmann is an Ordinary Professor at the University of Szczecin, Poland, and Emeritus Professor at the University of Saskatchewan, Canada. His primary affiliation is with the Institute of Mathematics at the University of Szczecin, where he holds a full professorship. He has also held tenured positions at the University of Saskatchewan from 2004 to 2015, serving as a Professor and Associate Professor. Education: He earned a Teacher's Diploma (1983) and Master's Degree (1982) from the University of Münster, followed by a Ph.D. (1990) and Habilitation (1995) from the University of Heidelberg. His doctoral advisor was Peter Roquette, and his master's advisor was Falko Lorenz. Research Interests: Kuhlmann specializes in valuation theory, real algebra, model-theoretic algebra, and applications to algebraic geometry. His work includes studies on local uniformization, model theory of valued fields, spaces of real places, and fixed point theory in ultrametric spaces. He has contributed significantly to resolving foundational problems in valuation theory, such as the defect in field extensions and the Ax-Kochen-Ershov principles. Editorial and Leadership Roles: He serves on the editorial boards of the Journal of Algebra and Annales Mathematicae Silesianae . He co-organized major conferences, including the 1999 International Conference on Valuation Theory in Saskatoon and the 2011 Segovia conference. He maintains the Valuation Theory Home Page, a critical resource for the field. Professional Contributions: Kuhlmann has authored over 50 peer-reviewed papers, co-edited major conference proceedings, and developed foundational frameworks in valuation theory. His work bridges algebra, logic, and geometry, with applications in model theory and algebraic geometry. Affiliations: Member of the American Mathematical Society, Polish Mathematical Society, German Mathematical Society, and the Association of Symbolic Logic.

• Valuation Theory
• Real Algebra and Ordered Structures
• Model Theoretic Algebra
• +۵ مورد دیگر

Zhengchao Wan is an Assistant Professor in the Department of Mathematics at the University of Missouri, part of the College of Arts and Science. His research focuses on the intersection of machine learning, topological data analysis, metric geometry, and probability theory. He explores applications of these areas in graph-based learning, optimal transport, and geometric data analysis. His work includes developing novel methods for graph neural networks, analyzing effective resistance in networks, and advancing topological techniques like persistent homology and the persistent Laplacian. He also contributes to foundational studies in metric geometry, including ultrametric spaces and Gromov-type distances. Recent publications highlight his contributions to robust graph learning algorithms, flow matching ODE dynamics, and the theoretical underpinnings of graph transformers. His research bridges abstract mathematical concepts with practical machine learning challenges, emphasizing both theoretical rigor and real-world applicability.

• Machine Learning
• Topological Data Analysis
• Metric Geometry
• +۳ مورد دیگر

Michel L. Lapidus is a Distinguished Professor of Mathematics and holder of the Burton Jones Endowed Chair in Pure Mathematics at the University of California, Riverside. He holds cross-appointments in Physics/Astronomy and Computer Science. He earned his Ph.D. and Doctorat d'État ès Sciences from Université Pierre et Marie Curie (Paris VI). His research bridges fractal geometry , mathematical physics , and number theory , focusing on spectral analysis of fractal drums, p-adic fractal strings, Feynman path integrals, and connections between fractal zeta functions and the Riemann hypothesis. Recent work explores complex dimensions, multifractal zeta functions, and noncommutative fractal structures. Publication trends reveal deep interplays between geometric measure theory, dynamical systems, and spectral theory, with applications to quantum physics and arithmetic geometry. His articles frequently employ zeta functions, tube formulas, and operator algebras to characterize fractal spaces. Scientific Awards: Fellow of AAAS and AMS; Anassilaos International Prize; Dissertation Mentor Award; Creative Research Medal He directs the Fractal and Mathematical Physics Research Group , mentoring over 20 PhD students and postdocs. Funded by NSF grants including DMS-1107750, his work supports investigations into fractal spectral theory and noncommutative flows.

• Fractal Geometry
• Mathematical Physics
• Spectral Analysis
• +۵ مورد دیگر