جست‌وجوی استاد و پژوهشگر

Marni Mishnaمشاهده پروفایل

استاد

• Analytic Combinatorics
• Enumerative Combinatorics
• Algorithmic Solutions
• +۵ مورد دیگر

Marni Mishna is a Full Professor in the Department of Mathematics at Simon Fraser University’s Faculty of Science. Her academic roles include Associate Dean, Equity, Diversity, and Inclusion (2023–2028) and PIMS Deputy Director (2019–2021). She has held visiting positions at institutions such as CNRS (France), LaBRI (University of Bordeaux), and the Fields Institute. Education: PhD in Mathematics (Université du Québec à Montréal, 2003), MSc in Pure Math (SFU, 2000), BMath (University of Waterloo, 1997). Her research spans analytic and enumerative combinatorics , focusing on generating functions , lattice paths , D-finite symmetric functions , and algorithmic solutions . She explores the intersection of combinatorics with art and design for mathematical communication. Recent articles analyze differential transcendence , Kronecker coefficients , and lattice path universality classes , emphasizing computational methods and asymptotic analysis. Her work often bridges graph theory , symmetric functions , and algebraic structures . She supervises students and postdocs in projects related to combinatorial theory , graph enumeration , and symmetric function applications . Her teaching includes advanced courses like MATH 443/743 (Combinatorics) and MATH 322 (Complex Analysis).

Steven M. Heilmanمشاهده پروفایل

استادیار

• Probability
• Analysis
• Geometry
• +۵ مورد دیگر

Steven M. Heilman is an Assistant Professor at the University of Southern California , specializing in research at the intersection of Probability, Analysis, Geometry , and Theoretical Computer Science . His work bridges mathematical theory with applications in algorithmic hardness, social choice, and quantum computing. Affiliation: Department of Mathematics, University of Southern California Advisor: Professor Assaf Naor (Princeton University) Research Trends: From 2021–2025, Heilman's publications focus on noise stability of voting systems, geometric inequalities, Gaussian isoperimetric problems, and algorithmic challenges in quantum computing. Key themes include symmetric sets, tree structures, and applications of probability to computational complexity. Advising & Grants: He supervises high school and undergraduate research projects. In 2025, he received an NSF CCF Grant AF: Small ($200,000) for research on geometric inequalities, clustering hardness, and social choice theory. Conferences: He organized the HIM Conference on Information Theory, Boolean Functions, and Lattice Problems (2024) and the IPAM Conference on Calculus of Variations in Probability and Geometry (2022).

Omer Bobrowskiمشاهده پروفایل

استاد

• Topological Data Analysis
• Stochastic Topology
• Applied Topology
• +۴ مورد دیگر

Omer Bobrowski is a Professor in Mathematical Data Science at Queen Mary University of London, affiliated with the School of Mathematical Sciences. His research focuses on stochastic topology, topological data analysis (TDA), and their applications in signal processing and natural language processing. He explores theoretical aspects like phase transitions in stochastic topology and noise distribution in TDA tools, while developing statistical methods for practical applications. His work has been supported by grants from the EPSRC (£396,018, 2024–2027) and the Leverhulme Trust (£330,778, 2024–2027). Collaborators include Primoz Skraba and others in the Centre for Probability, Statistics, and Data Science. Research Interests include: Random Topology, Applied Topology, Stochastic Geometry, and Probability Theory. His lab includes Research Staff Dr. Shu Kanazawa, Dr. Uzu Lim, and Dr. Duncan Parker. Bobrowski’s publications span foundational TDA theory and applied methodologies across diverse datasets.

• Coding Theory
• Combinatorics
• Error-Correcting Codes
• +۲ مورد دیگر

Anina Gruica is a Research Fellow in the Algebra group at the Technical University of Denmark (DTU), specializing in coding theory with emphases on density questions, combinatorial structures of error-correcting codes, and DNA-based data storage systems. Her work bridges theoretical mathematics and practical applications in next-generation storage technologies. Her research program centers on Coding Theory and Combinatorics, investigating the geometric and probabilistic properties of codes in metric spaces. Key interests include rank-metric codes, MRD codes, and combinatorial optimization for DNA storage efficiency, where she develops novel approaches to random access and coverage depth challenges through algebraic and geometric frameworks. Dr. Gruica's publication portfolio reveals a strong interdisciplinary trajectory, with increasing focus on DNA storage applications since 2022. Her work combines deep theoretical insights in combinatorial geometry with practical storage system design, resulting in high-impact publications across SIAM journals, IEEE conferences, and arXiv preprints that address both classical coding problems and emerging biological storage constraints. She has received competitive recognition including: ALCOCRYPT conference travel award (February 2023) DIAMANT PhD travel grant (2000 EUR, January 2023) DIAMANT visitor grant (1900 EUR, October 2021) SIAM Travel Award (August 2021) As co-organizer of the Postgraduate International Coding theory Seminar (PICS), Dr. Gruica actively mentors junior researchers while maintaining extensive collaborations with A. Ravagnani, J. Sheekey, and E. Yaakobi. Her conference presentations at venues like ISIT and SIAM AG23 demonstrate her leadership in translating theoretical advances to storage applications. She contributes to DTU's Algebra group research ecosystem, focusing on algebraic structures for coding theory and cryptography. Her current projects, evident from 2024-2025 preprints, explore combinatorial geometry for DNA storage efficiency and advanced rank-metric code constructions, positioning her at the forefront of coding theory's application to biological data systems.

Eveliina Peltolaمشاهده پروفایل

دانشیار

• Mathematical Physics
• Probability Theory
• Conformal Field Theory
• +۳ مورد دیگر

Eveliina Peltola is an Associate Professor at Aalto University's Department of Mathematics and Systems Analysis, within the School of Science. She is also affiliated with the University of Bonn's Hausdorff Center for Mathematics. Her research focuses on mathematical physics, combining algebraic, geometric, and probabilistic methods to study conformal field theory, random geometry, and scaling limits. Her academic positions include roles in Algebra and Discrete Mathematics, Mathematical Physics, and Analysis. She is a member of the Finnish Academy of Science and Letters and has been supported by grants such as the Academy of Finland, ERC Starting Grant, and German Research Foundation. Key research interests include Schramm-Loewner Evolution (SLE), conformal invariance, and logarithmic conformal field theory. Recent work involves connection probabilities of interfaces, large deviations, and degenerate conformal blocks. Notable publications span 2016–2025, addressing topics like SLE processes, Ising models, and geometric probability. Eveliina's contributions are supported by grants including the ISCoURaGe Finnish Centre of Excellence and the SFB Collaborative Research Centre 1060. Her research bridges mathematics and physics, with applications in statistical mechanics and random geometry. Awards and recognitions include her membership in the Finnish Academy of Science and Letters and funding from prestigious institutions like the ERC and Academy of Finland.

• Mathematics
• Geometric Function Theory
• Partial Differential Equations
• +۴ مورد دیگر

Kari Astala is a Research Professor and Research Director at the Department of Mathematics and Statistics, University of Helsinki. He also serves as the Supervisor for the Doctoral Programme in Mathematics and Statistics. His research focuses on geometric function theory, partial differential equations, and quasiconformal mappings, with interdisciplinary applications in inverse problems and materials science. Affiliations: University of Helsinki, Department of Mathematics and Statistics, Doctoral Programme in Mathematics and Statistics Major research interests include the study of quasiconformal mappings, elliptic PDEs, and their connections to nonlinear elasticity and inverse problems. Astala has contributed to foundational results in the field, such as the solution to Calderón’s inverse conductivity problem in the plane and the development of theories around Beltrami equations and Schauder estimates. His publications (43) span decades, with recent work addressing global smoothness in Triebel-Lizorkin spaces and homogenization of singular integrals. Key articles include analyses of nonlinear Beltrami operators and principal maps, reflecting his deep engagement with geometric analysis and its applications. Awards: Salem Prize (1994), Finnish Science Foundation's Magnus Ehrnrooth Prize (2003), Finnish Cultural Foundation Prize of Recognition (2011) Astala has actively supervised doctoral students and led research projects like QUAMAP (2019–2024), exploring quasiconformal methods in analysis. He maintains international collaborations, including visiting positions at the Instituto de Ciencias Matematicas (ICMAT) and the Universidad Autonoma de Madrid.

• Fractals
• Geometric Measure Theory
• Metric Rectifiability
• +۳ مورد دیگر

Tuomas Orponen is a Professor at the Department of Mathematics and Statistics, University of Helsinki, where he serves as a supervisor for the Doctoral Programme in Mathematics and Statistics. His research focuses on fractal geometry, geometric measure theory, and quantitative rectifiability, with particular emphasis on the interplay between geometric configurations and measure-theoretic properties in Euclidean and non-Euclidean spaces. He has led major research projects such as 'Incidences on Fractals' and 'Quantitative Rectifiability of Sets and Measures,' supported by the University of Helsinki. Orponen has published over 40 peer-reviewed articles and actively contributes to academic activities, including organizing conferences like 'Geometric Measure Theory and its Connections' and delivering invited talks at events like the Barcelona Analysis Conference 2019. His work bridges pure mathematics and applications in harmonic analysis and combinatorics, addressing questions about fractal structures, projection theorems, and metric dimensions. Orponen has collaborated internationally, visiting institutions such as the Institute of Mathematics of the Polish Academy of Sciences (IMPAN) and hosting researchers at the University of Helsinki. His research has advanced understanding in areas like Hölder-regular surfaces, self-similar measures, and continuous analogues of combinatorial problems.

Amirali Khodadadian Gostarمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Data Analytics
• Multi-Object Tracking
• +۵ مورد دیگر

Dr. Amirali Khodadadian Gostar is a Senior Lecturer at the School of Engineering, RMIT University. His research focuses on machine learning, data analytics, multi-object tracking, sensor management, and data-driven manufacturing. He has contributed to advancements in autonomous systems, anomaly detection, and multi-agent coordination through projects like distributed information fusion for connected vehicles and geometrically-informed tracking algorithms. Research Interests : Image processing, sensor fusion, robotics, control systems, and industrial automation. Key Projects : Development of electronic pre-tension systems for seatbelts, AI-driven logistics optimization, and stereo vision systems for defect detection. Publications : Over 60 peer-reviewed articles in top journals/conferences such as IEEE Transactions on Intelligent Transportation Systems and ISA Transactions, focusing on tracking algorithms, anomaly detection, and multi-agent systems. His work bridges theoretical frameworks (e.g., random finite set theory) with practical applications in robotics, transportation, and manufacturing. He actively supervises PhD/Master's students on topics ranging from quantum AI in logistics to eye gaze tracking for visual attention modeling.

• Photovoltaic Materials
• Quantum Dot Systems
• Complex Networks
• +۵ مورد دیگر

Lucas Cuadra Rodríguez is a Full Professor in the Department of Signal Theory and Communications at Universidad Alfonso X El Sabio (UAX). He holds a PhD from Universidad Politécnica de Madrid (2004), specializing in intermediate band solar cell development. His research spans quantum dot systems, network science applications in materials and energy systems, and machine learning for environmental and engineering challenges. Key areas include photovoltaic materials, complex network modeling of disordered systems, and renewable energy optimization. Education: Doctorado en Física from Universidad Politécnica de Madrid (2004), supervised by Dr. Antonio Marti Vega and Dr. Antonio Luque López. His work bridges physics, computer science, and engineering, with a focus on interdisciplinary solutions for energy and environmental systems. Research Interests: His primary focus is on developing novel semiconductor solar cell structures, particularly quantum dot-based intermediate band solar cells, and applying network science to study carrier transport in nanomaterials. He also explores machine learning applications in Earth observation, wind energy prediction, and complex system analysis. His recent work emphasizes spatially embedded networks and their relevance to material science and renewable energy infrastructure. Notable Projects: Leading the GHEODE Research Group (Modern Heuristics and Network Design), he investigates optimization algorithms for smart grids and network robustness. Recent studies include modeling electron transport in van der Waals materials and analyzing fog event persistence through nonlinear dynamics. Awards: No specific awards mentioned in the provided text. Advising & Grants: While his PhD supervision details are noted, no current student advisees or grant projects are detailed here. His work often involves collaborative interdisciplinary projects with engineering and environmental science teams. Labs/Teams: Active in the GHEODE Group at UAX, focusing on heuristic algorithms and network-based solutions for engineering challenges.

• Algorithmic Algebra
• Computational Complexity
• Invariant Theory
• +۴ مورد دیگر

Prof. Peter Bürgisser is a Professor in the Institute of Mathematics at Technische Universität Berlin, leading the Research Group on Algorithmic Algebra. His work focuses on computational complexity, invariant theory, algebraic geometry, and probabilistic methods in mathematics. He holds a prominent role in advancing theoretical computer science and algorithmic algebra through his research and publications. Research interests include Algorithmic Algebra, Computational Complexity, Invariant Theory, Optimization, and Probability Theory. His contributions span foundational work in geometric complexity theory, probabilistic algebraic geometry, and efficient algorithms for algebraic problems. Publications highlight his expertise in topics like random fewnomials, nonarchimedean geometry, and polynomial time algorithms for invariant theory. His work is published in top journals such as Journal für die reine und angewandte Mathematik and Foundations of Computational Mathematics . Prof. Bürgisser is actively involved in academic activities, including teaching and advising, though specific student names are not listed in the provided texts. His research has been supported by grants and collaborations with institutions worldwide.

Wolfgang Polonikمشاهده پروفایل

استاد

• Mathematical Statistics
• Statistical Learning Theory
• Nonparametric Statistics
• +۶ مورد دیگر

Wolfgang Polonik is a Professor in the Department of Statistics at the University of California, Davis, where he conducts research at the intersection of mathematical statistics, nonparametric methods, and topological data analysis. His work combines deep theoretical foundations with applications in high-dimensional and complex data structures. His research interests include Mathematical Statistics, Statistical Learning Theory, Nonparametric Statistics, Shape Constraints, Modality, Nonstationary Time Series, Empirical Process Theory, Topological Data Analysis, and Random Networks . He applies these to problems involving geometric and topological inference, manifold learning, and anomaly detection. The recent publications highlight a strong focus on persistent homology, bootstrap methods for topological features, nonparametric regression on manifolds, and multiscale geometric analysis . His work often bridges theoretical statistics with computational topology and machine learning, particularly through the use of persistence diagrams, level sets, and filament estimation. Collaborations with researchers like W. Qiao and G. Chandler are frequent. Dr. Polonik has served as an Associate Editor for several top-tier journals, including: Journal of the Royal Statistical Society – Series B (2012–2015) Journal of Multivariate Analysis (since 2003) Journal of Statistical Planning and Inference (2004–2012) Annals of Statistics (2007–2012) He is a member of leading professional societies such as the Institute of Mathematical Statistics, American Statistical Association, Bernoulli Society, and International Statistical Institute . While no formal advising or grant information is listed, his editorial roles and publication record reflect significant scholarly impact. He is affiliated with the College of Letters and Science at UC Davis.

• random walks
• stochastic process
• neurosciences
• +۲ مورد دیگر

Dr. Daniel Han is a researcher at the University of New South Wales (UNSW), affiliated with the School of Mathematics and Statistics and the Department of Mathematics and Statistics. His work focuses on interdisciplinary research at the intersection of mathematics, neurosciences, and cell biology, with a particular emphasis on stochastic processes and random walks. His current research interests include applying mathematical models to neurodegenerative diseases and healthcare challenges, such as telemedicine in rural aged care. Dr. Han's profile can be found at his UNSW webpage . His research spans diverse topics, including biomarker development for Parkinson’s disease, intercultural competence through virtual exchange, and moduli spaces in algebraic geometry. He has contributed to both theoretical and applied domains, publishing widely in journals across mathematics, neurology, and education. His recent work highlights the application of mathematical frameworks to real-world problems in healthcare and education.

Walid BEN AMEURمشاهده پروفایل

استاد

• Operations Research
• Network Optimization
• Mathematical Programming
• +۳ مورد دیگر

Prof. Walid Ben-Ameur is a Professor at Telecom SudParis, affiliated with the SAMOVAR laboratory. His research focuses on Operations Research, Network Optimization, and Algorithmic Game Theory. He has contributed significantly to areas such as combinatorial optimization, robust network design, and mathematical programming. His work includes advancements in polyhedral combinatorics, stochastic games, and distributed computing frameworks. Recent studies explore strategic investments in social networks, robust routing algorithms, and the theoretical foundations of optimization under uncertainty. While no scientific awards are explicitly mentioned, his prolific publication record highlights impactful contributions to the field. His research often bridges theoretical insights with practical applications in telecommunications and distributed systems. Key research interests include the design of efficient algorithms for network infrastructure, optimization under uncertainty, and game-theoretic models for distributed systems. His articles frequently address challenges in robust network design, opinion dynamics in social networks, and the computational aspects of combinatorial problems. Prof. Ben-Ameur collaborates extensively, with notable contributions to journals like Operations Research Letters, SIAM Journal on Optimization, and Networks. His work often intersects with telecommunications, as evidenced by studies on fiber cable network design and traffic engineering. He has also explored advanced topics such as multipolar robust optimization and the application of game theory to distributed computing environments.

Elisabeth BRUNETمشاهده پروفایل

مدرس

• Parallel Computing
• High-Performance Computing
• Computer Architecture
• +۳ مورد دیگر

Elisabeth BRUNET is a Lecturer at Telecom SudParis, part of the Institut Mines-Télécom. Her research focuses on parallel computing, high-performance computing systems, and communication optimization. She has contributed to projects involving GPU porting, MPI communication protocols, and fault-tolerant checkpointing strategies. Her interdisciplinary work extends to biophysics and stochastic processes, with notable publications in journals like Physical Review Fluids and Scientific Reports . She has also explored applications in sports biomechanics and medical imaging analysis. Key collaborations include work on NewMadeleine communication libraries and unified checkpointing models for extreme-scale systems. Her technical contributions span across both theoretical and applied domains, addressing challenges in distributed computing architectures and performance optimization. Education: While specific academic degrees are not detailed in the provided text, her extensive publication record indicates advanced expertise in computer science and mathematics. Research Interests: Parallel computing architectures, stochastic processes in biological systems, high-performance communication networks, and GPU-accelerated algorithms. Awards: No specific awards are mentioned in the text, though her contributions have been recognized through collaborative projects and peer-reviewed publications.

Ole Sönnerbornمشاهده پروفایل

مدرس

• Quantum Mechanics
• Mathematical Physics
• Topology and Geometry in Physics
• +۳ مورد دیگر

Ole Sönnerborn is a Lecturer in Mathematics at Karlstad University, focusing on the intersection of topology, geometry, and quantum mechanics. His research explores quantum systems with topological/geometric origins, including holonomy, geometric phases, quantum speed limits, and quantum information theory. He teaches advanced mathematics courses for engineering and mathematics education programs. Key research areas include: Quantum holonomy and its applications in computation Time constraints for quantum processes (quantum speed limits) Self-testing quantum systems and Bell inequality violations Geometric uncertainty principles Symmetric informationally complete measurements (SICs) Recent work (2023-2025) emphasizes iso-holonomic inequalities, tight quantum speed limits, and non-adiabatic holonomic computation. Over 20 peer-reviewed articles span topics from quantum control to topological systems. Teaching responsibilities include: Mathematics for Engineers I/II Mathematical relationships in single-variable calculus Discrete Mathematics and Algebraic Structures Linear Algebra II Supervises bachelor/master thesis projects in mathematical physics and quantum theory. No awards explicitly listed in provided materials.