جست‌وجوی استاد و پژوهشگر

• Probability Theory
• Random Planar Maps
• Geometric Probability
• +۷ مورد دیگر

Nicolas Curien is a Professor at Paris-Saclay University, affiliated with the Probability and Statistics Team. His research spans Probability Theory , Random Planar Maps , Hyperbolic Geometry , and Stochastic Processes . Key Roles : Head of the M2 program "Mathematics of Randomness" at University of Paris Saclay Associate Editor for journals like Electronic Journal of Probability and Annals of Probability His research interests focus on geometric probability, random graphs, percolation theory, and the interplay between random metric spaces and combinatorial structures. Recent work includes studies on geodesic stability in Poisson-line metrics, hyperbolic Voronoi tessellations, and phase transitions in parking processes on random trees. He has supervised numerous PhD and Master’s students, including Alessandra Caraceni , Linxiao Chen , and Thomas Budzinski , with projects on random planar maps, frozen Erdős–Rényi graphs, and hyperbolic random planar maps. His scientific awards include the ERC Cog "SuPerGRandMa" (2023), the Prix Marc Yor (2022), and the Prix Jacques Herbrand (2019). Collaborative efforts and editorial roles further highlight his contributions to probabilistic models, including scaling limits of causal maps, harmonic measures in random trees, and geometric properties of infinite snakes via unimodularity. His work often bridges discrete structures with continuum limits, such as the Brownian plane and stable looptrees.

• Motion Planning and Robotics
• Computational Biology
• Parallel and Distributed Computing
• +۳ مورد دیگر

Nancy Amato is the Unocal Professor of Computer Science and Engineering (CSE) at Texas A&M University, co-directing the Parasol Lab. Her research focuses on motion planning, robotics, computational biology, and parallel computing. She has advised 16 PhD students and 25 master’s students, fostering academic and research careers. Recognized for teaching excellence, she received awards like the 2015 CSE Graduate Teaching Excellence Award and the 2013 Betty M. Unterberger Award. Her contributions to diversity in computing include the A. Nico Habermann Award (2014) for expanding underrepresented groups in research. She is an IEEE Fellow and AAAS Fellow for contributions to motion planning and computational biology. Amato earned bachelor’s degrees in economics and mathematical sciences from Stanford University and a master’s in CS from UC Berkeley, later studying under Franco Preparata at the University of Illinois. Education : Bachelor’s in Economics and Mathematical Sciences, Stanford University Master’s in Computer Science, UC Berkeley PhD Studies under Franco Preparata, University of Illinois Awards : 2013 IEEE Hewlett-Packard/Harriet B. Rigas Award 2014 A. Nico Habermann Award Fellow of IEEE and AAAS Grants/Advising : Directed over 160 students across PhD, master’s, undergraduate, and high school levels Co-developed the CRA-W Distributed Research Experiences for Undergraduates program Labs/Teams : Parasol Lab (focusing on parallel computing and robotics)

• Discrete Optimization
• Approximation Algorithms
• Mathematical Programming
• +۳ مورد دیگر

Zachary Friggstad is an Associate Professor in the Department of Computing Science at the University of Alberta. His research focuses on algorithm design for discrete optimization problems, including vehicle routing, facility placement, and scheduling. He specializes in approximation algorithms with proven performance guarantees, often leveraging convex relaxations like linear and semidefinite programming. Education: B.Sc. in Computing Science, University of Lethbridge, 2005 M.Sc. in Computing Science, University of Alberta, 2007 Ph.D. in Computing Science, University of Alberta, 2011 Research Interests: Discrete Optimization Approximation Algorithms Mathematical Programming Algorithm Design for NP-Hard Problems Graph Algorithms and Combinatorial Optimization His publications span over 50 works, with recent trends emphasizing fair clustering algorithms, TSP approximations, and narrative distillation in cross-media contexts. No scientific awards are explicitly listed in the provided text. He has advised no students in the listed records. His work bridges theoretical computer science and practical algorithmic solutions for complex optimization challenges.

• Algorithms
• Parallel Computing
• Machine Learning
• +۳ مورد دیگر

Quentin Stout is a Professor in the Department of Computer Science and Engineering at the University of Michigan, Ann Arbor. His research focuses on algorithms, parallel computing, machine learning, and computational physics, with notable contributions to adaptive mesh refinement, isotonic regression, and neural network architectures. He actively mentors PhD students, emphasizing adaptability in advising and collaboration in group meetings. Stout's work spans theoretical and applied domains, including radiative shock hydrodynamics modeling and space weather simulations. He has developed frameworks like CRASH and the Space Weather Modeling Framework (SWMF), advancing interdisciplinary research in computational science. His advising style prioritizes student independence, with weekly meetings and flexible communication channels. Research interests include parallel algorithms, energy-efficient computing, and statistical methods. He encourages students to explore interdisciplinary opportunities beyond their thesis work, leveraging Ann Arbor's academic and cultural resources. No awards are listed for Stout in the provided text. Advising emphasizes timely feedback and collaboration, with group meetings featuring student-led presentations and open discussions. He supports internships during summers and advocates for balanced work-life integration, encouraging breaks without compromising academic progress. Key projects include the SWMF, which integrates space physics simulations, and adaptive mesh refinement techniques for atmospheric and plasma dynamics modeling. His lab’s work bridges computer science and applied mathematics, addressing challenges in high-performance computing and scientific visualization.

• Geospatial Data Management
• Distributed Computing
• Machine Learning
• +۴ مورد دیگر

Prof. Werner Martin is a Professor of Big Geospatial Data Management at the Technical University of Munich (TUM), affiliated with the School of Engineering and Design and the Department of Aerospace and Geodesy. His research focuses on georeferenced data processing, distributed computing, quantum algorithms, and machine learning applications in geospatial contexts. Prof. Martin holds a doctorate from LMU Munich and has held academic and research positions at institutions including LMU Munich, Leibniz-University Hannover, the German Aerospace Center (DLR), and UniBW Munich. His work bridges theoretical advancements with practical applications in spatial data analysis, visualization, and high-performance computing. Awards ACM SIGSPATIAL GIS Certificate of Appreciation (2019) 1st place ACM SIGSPATIAL GIS Cup (2015) IPIN Best Paper Award (2014) His recent publications emphasize geospatial AI, quantum computing for data processing, and environmental monitoring systems. Collaborations with industry partners like DLR highlight his focus on real-world geospatial challenges.

Christina Goldschmidtمشاهده پروفایل

استاد

• Random Discrete Structures
• Random Trees and Graphs
• Scaling Limits
• +۲ مورد دیگر

Christina Goldschmidt is a Professor of Probability at the University of Oxford's Department of Statistics and a Tutorial Fellow at Lady Margaret Hall. She holds a PhD from the Statistical Laboratory at the University of Cambridge, supervised by James Norris, and has held postdoctoral positions at Université Paris VI and EPSRC fellowships at Oxford. Her research focuses on random discrete structures, scaling limits of random graphs and trees, and combinatorial stochastic processes, including coagulation-fragmentation dynamics. Education: BSc and MSc in Mathematics from Cambridge, PhD in Probability. Postdoctoral experience includes time at Université Paris VI under Jean Bertoin and roles at Pembroke College Cambridge and Warwick University. Research Interests: Scaling limits of random graphs and trees, phase transitions in random networks, stable trees, and applications of stochastic processes to combinatorial structures. Key Awards: EPSRC Early Career Fellowship (2016–2020), EPSRC Postdoctoral Fellowship (2007–2009). Active in the Probability research group at Oxford and supervises graduate students in stochastic processes and random graphs. Labs/Teams: Member of the Probability Group at the Department of Statistics, collaborating internationally on projects related to random graph scaling limits and combinatorial analysis.

• Robotics
• Artificial Intelligence
• Task and Motion Planning
• +۴ مورد دیگر

Rahul Shome is a tenure-track lecturer in the School of Computing at the Australian National University (ANU), specializing in Robotics & AI. His research focuses on planning algorithms for human-centric robotics applications, with expertise in task and motion planning, multi-robot systems, and collaborative automation. He holds a Ph.D. and M.S. from Rutgers University, advised by Prof. Kostas E. Bekris, and completed postdoctoral work at Rice University under Prof. Lydia E. Kavraki. Education: Ph.D. and M.S. in Robotics, Rutgers University (advisor: Prof. Kostas E. Bekris) Postdoctoral Research Associate, Rice University (advisor: Prof. Lydia E. Kavraki) Research Interests: Development of practical robotics solutions with theoretical guarantees Integration of AI techniques for real-world automation challenges Multi-robot coordination and manipulation in dynamic environments Human-centric robotics emphasizing privacy, ethics, and collaboration His publications span journals and conferences like IEEE Robotics and Automation Letters, with awards including the Best Paper Award at IEEE MRS. Shome actively serves on editorial and organizing boards for major robotics venues. Current research directions explore algorithmic foundations in stochastic decision-making, topology, and machine learning integration. Advising & Opportunities: Open PhD and research positions in robotics planning and collaborative automation Focus areas: AI-driven robotics, human-robot interaction, and perception systems

Torsten Mützeمشاهده پروفایل

استاد

• Discrete Mathematics
• Theoretical Computer Science
• Graph Theory
• +۵ مورد دیگر

Torsten Mütze is a Professor at the Institute of Mathematics at the University of Kassel. Previously, he held positions as an Assistant Professor at the University of Warwick (2019–2024) and was affiliated with Charles University Prague's Department of Theoretical Computer Science and Mathematical Logic. His academic journey includes a postdoc under Martin Skutella at TU Berlin, research stays at Georgia Tech and ETH Zurich, and a software engineering role at Supercomputing Systems Zurich. Education: PhD in 2011 from ETH Zurich under Angelika Steger's supervision Master's and Bachelor's degrees in related fields Research Interests: Focuses on discrete mathematics and theoretical computer science, including combinatorial algorithms, graph theory, computational geometry, order theory, Ramsey theory, and combinatorial games. His work bridges foundational theory and real-world applications, particularly in algorithm design and combinatorial generation. Advising & Grants: Supervised students: Francesco Verciani, Nastaran Behrooznia, Namrata, Arturo Merino, Frieder Smolny, Karl Däubel, Jerri Nummenpalo, and Ondřej Mička Funded projects: DFG Heisenberg grant 522790373, Chancellor's International Scholarships, and EU funding Labs & Collaborations: Organizes workshops like 'Combinatorics, Algorithms and Geometry' and contributes to research networks such as the 'Combinatorial Optimization and Graph Algorithms' group. His work involves collaborations with institutions globally, including ETH Zurich, Georgia Tech, and TU Berlin.

• Combinatorics
• Graph Theory
• Discrete Mathematics
• +۵ مورد دیگر

Marcos Noy Serrano is a Professor in the Department of Mathematics at Universitat Politecnica de Catalunya (UPC), where he is a key member of the GAPCOMB research group focused on Geometric, Algebraic and Probabilistic Combinatorics. With a career spanning over three decades, he has established himself as a leading researcher in combinatorics and discrete mathematics. His research interests center on combinatorics, particularly in graph theory, enumerative combinatorics, and computational geometry. Noy's work frequently explores planar graphs, random structures, and combinatorial enumeration, with significant contributions to understanding the properties and counting of various combinatorial structures. His research combines algebraic, geometric, and probabilistic approaches to tackle fundamental problems in discrete mathematics. Noy's scholarly output shows consistent productivity with over 300 documented activities, including numerous journal articles in top combinatorics publications, research projects, and conference presentations. His recent work (2021-2024) focuses on chordal graphs with bounded tree-width, enumeration of various planar graph structures, random cubic planar maps, and logical properties of random sparse structures, demonstrating his continued engagement with cutting-edge problems in combinatorics. Among his notable recognitions are the prestigious Medalla Narcís Monturiol al mèrit científic i tecnològic and the Humboldt Research Award, highlighting the international impact of his work. He has also led significant research projects including the María de Maeztu Program for Centers and Units of Excellence in R&D and the COntemporary COmbinatorics and Applications (COCOA) project. Noy has supervised doctoral students, including Larrauri, L. who completed work on First Order Logic of Random Sparse Structures. He maintains active research collaborations across Spain and internationally, contributing to the vibrant combinatorics research community.

Enric Ventura Capellمشاهده پروفایل

دانشیار

• Group Theory
• Combinatorics
• Algebra
• +۳ مورد دیگر

Enric Ventura Capell is an Associate Professor in the Department of Mathematics at the Polytechnic University of Catalonia (UPC), specifically within the Faculty of Mathematics and Statistics (FME). He is affiliated with the Institute of Mathematics of UPC-BarcelonaTech and serves as a key researcher in the GAPCOMB group (Geometric, Algebraic and Probabilistic Combinatorics). With a documented record of 338 academic activities spanning over three decades, Professor Ventura Capell maintains an active and influential research profile in pure mathematics. His research expertise centers on Group Theory with specialized focus on Free Groups, Geometric Group Theory, and Combinatorial Group Theory. Professor Ventura Capell has made significant contributions to the theory and applications of Stallings automata, subgroup structures in various group extensions, intersection problems in free groups, and algorithmic approaches to fundamental group-theoretic questions. His work consistently bridges theoretical mathematics with computational methods, providing both theoretical insights and practical algorithmic solutions to complex algebraic problems. Analysis of his recent publications (2021-2025) reveals a continued emphasis on geometric and combinatorial aspects of group theory, particularly exploring H-equations with integral matrices, intersection configurations in free and free-abelian groups, and the central tree property in subgroup structures. His research demonstrates increasing sophistication in handling complex algebraic structures while maintaining strong connections to broader mathematical frameworks and computational applications. Professor Ventura Capell has established extensive collaborative networks with researchers including Jorge Delgado Rodriguez, Mallika Roy, Armando Martino, and Jose Burillo Puig. His research has been supported by multiple competitive grants from Spanish national research programs (Plan Estatal de Investigación) and the Catalan government's research initiatives, including projects like GEOGROUPS and GAPCOMB. As a core member of the GAPCOMB research group, he contributes to a vibrant research environment focused on geometric, algebraic, and probabilistic approaches to combinatorial problems. The group fosters interdisciplinary research that connects pure mathematics with applications in computer science and other fields, maintaining strong connections with international research centers including the Centre de Recerca Matemàtica (CRM).

Moshe Cohenمشاهده پروفایل

استادیار

• Knot Theory
• Topology
• Combinatorics
• +۳ مورد دیگر

Moshe Cohen is an Assistant Professor in the Department of Mathematics at SUNY New Paltz. He holds a PhD and MS from Louisiana State University and a BS from Binghamton University. His research focuses on the intersection of topology and combinatorics, particularly knot theory and line arrangements. He has supervised numerous undergraduate research projects, including studies on 2-bridge knots, moduli spaces of line arrangements, and random knot models. Cohen has received grants such as the MAA NREUP (co-PI) and AYURE funding. He actively participates in academic service, co-organizing conferences like Unknot V and SUMR. His teaching philosophy emphasizes collaborative learning, with courses like MAT 304 (Foundations of Algebra) and MAT 331 (Axiomatic Geometry) adopting active learning models. His research has been presented at venues like the Banff International Research Station and the Joint Mathematics Meetings. Notable awards include the David Oxley Memorial Teaching Award and recognition for an outstanding poster presentation. Cohen also maintains a community-focused approach, managing the 'Not KNerds' Facebook group for knot theorists.

Michael Mathioudakisمشاهده پروفایل

استاد مهمان

• Data Mining
• Social Media Analysis
• Text Mining
• +۴ مورد دیگر

Michael Mathioudakis serves as a Visiting Faculty member in the Department of Computer Science at Aalto University and is affiliated with the Adj. Prof. Gionis Aris research group and the Helsinki Institute for Information Technology (HIIT). His academic work spans multiple institutions and research collaborations focused on data-intensive computing and analysis. His educational background includes a Doctor of Philosophy from the University of Toronto, awarded on June 5, 2013. This foundation has enabled his research contributions across various domains of computer science and data analysis. Mathioudakis's research interests focus on Data Mining , Social Media Analysis , Text Mining , Social Network Analysis , and Bayesian Networks . His work explores the intersection of big data technologies with social phenomena, particularly examining how information flows through social networks and how probabilistic models can be optimized for real-world applications. His fingerprint analysis reveals significant contributions to Random Walk algorithms (100%), Social Network analysis (83%), Bayesian Networks (66%), and Big Data applications (33%). His publication record shows a consistent output from 2015-2022 with 22 total research outputs, including conference proceedings and journal articles. His work demonstrates a clear trajectory from foundational data mining research toward increasingly complex applications in social media analysis and urban informatics, with notable contributions to efficient algorithms for Bayesian network processing and social media content exposure systems. Mathioudakis has collaborated extensively with researchers across multiple institutions, as evidenced by his co-authorship on papers involving teams from various international organizations. His work contributes to UN Sustainable Development Goals, particularly in areas related to data-driven approaches to societal challenges.

Mikkel Thorupمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Hash Functions
• +۳ مورد دیگر

Mikkel Thorup is a Professor at the Department of Computer Science, University of Copenhagen, and a VILLUM Investigator heading the Basic Algorithms Research Copenhagen (BARC) Center supported by a €5.3 million grant from the VILLUM Foundation. Born in 1965, he holds a D.Phil. from Oxford University (1993). Prior roles include positions at the University of Copenhagen (1993–1998) and AT&T Labs-Research (1998–2013). His research focuses on algorithms, data structures, and hashing, with a particular emphasis on unifying theoretical and practical aspects. Awards include the ACM Fellowship, Villum Kann Rasmussen Award, and Fulkerson Prize. Education: D.Phil. in Computer Science, Oxford University (1993). Earlier positions: University of Copenhagen (1993–1998), AT&T Labs-Research (1998–2013). Research interests encompass algorithm design, data structure optimization, and hashing techniques. His work bridges theory and practice, addressing problems like graph clustering, optimization, and efficient sampling. He is known for contributions to correlation clustering, hash function analysis, and dynamic graph algorithms. Awards include the 2011 MAA Robbins Award, 2015 Villum Kann Rasmussen Award (Denmark’s top research prize), and 2021 AMS-MOS Fulkerson Prize. His Erdős number is 2, and he boasts an H-index above 60 with over 200 publications in top venues like STOC, FOCS, and SODA. Advising and grants: Leads BARC since 2017, funded by VILLUM Foundation. His research has influenced both academia and industry, particularly in telecommunications and algorithmic efficiency. Collaborates internationally, with a focus on foundational algorithmic challenges. Labs/Teams: Founder and head of BARC, fostering research in algorithms and their applications. Engages in interdisciplinary work combining theory with practical implementations.

• Combinatorics
• Probability
• Statistical Mechanics
• +۴ مورد دیگر

Olivier Bernardi is a Professor of Mathematics and Chair of the Brandeis University Department of Mathematics. His research focuses on combinatorics, with applications in probability, mathematical physics, computer science, and algebra. He specializes in bijective methods, encoding complex geometric structures into simpler forms like lattice paths and trees. A key interest is the combinatorics of maps (embedded graphs), which intersect fields like random surface theory and representation theory. Education includes a Ph.D. from Université Bordeaux 1, and M.S. and B.S. degrees from École Normale Supérieure Paris. His work bridges theoretical combinatorics with practical algorithms, emphasizing structural insights through bijections. Recent publications explore Tutte polynomials, percolation on triangulations, and geometric drawing algorithms. Awards and grants are not explicitly listed, but his leadership role as Department Chair highlights institutional contributions. He advises on research in discrete mathematics and collaborates on projects involving graph enumeration and algebraic combinatorics. His research spans foundational topics, with applications in both pure and applied mathematical domains.

Karthik Srikantaمشاهده پروفایل

استادیار

• Complexity Theory
• Discrete Geometry
• Hardness of Approximation
• +۴ مورد دیگر

Karthik C. S. is an Assistant Professor in the Department of Computer Science at Rutgers University, specializing in complexity theory, discrete geometry, and parameterized complexity. He is supported by the NSF CAREER Award Simons Foundation Junior Faculty Fellowship National Science Foundation grants . His research explores hardness of approximation, fine-grained complexity, and algorithm design in metric spaces.