جست‌وجوی استاد و پژوهشگر

Alan Soperمشاهده پروفایل

مدرس ارشد

• Combinatorial Optimization
• Scheduling Theory
• Operations Research
• +۳ مورد دیگر

Dr Alan Soper is a Senior Lecturer at the University of Greenwich, affiliated with the School of Computing and Mathematical Sciences within the Faculty of Engineering and Science. His research focuses on combinatorial optimization, scheduling theory, and algorithm design, particularly exploring pre-emption effects on parallel machines and scheduling under time-changing conditions. He has contributed to transportation scheduling and computational algorithms for graph partitioning and drawing. Dr Soper holds a PhD from the University of Cambridge (1982), an MSc in Foundations of Advanced Information Technology from Imperial College London (1989), and a Mathematics MA. His career spans theoretical physics research (1978), industry work at Digital Equipment Corporation (1984–1988), and academic research in algorithms and optimization. He has presented work at conferences like ECCO, EURO, and INFORMS, and his research addresses applications in graph partitioning, vehicle routing, and nuclear fuel management systems. His recent publications analyze scheduling strategies on uniform and unrelated parallel machines, preemption efficiency, and cyclical optimization techniques. His work bridges theoretical foundations with applied computational challenges, emphasizing algorithmic innovation in operations research and combinatorial problems.

Joanna Mitroمشاهده پروفایل

استاد

• Probability and stochastic processes
• Markov processes
• Stochastic modeling
• +۳ مورد دیگر

Joanna Mitro is a Professor of Mathematical Sciences at the University of Cincinnati, College of Arts and Sciences. She holds a PhD in Mathematics from UC San Diego (1977) and has held academic positions including Visiting Lecturer at University of Illinois (1977-1980), Assistant/Associate Professor at UC (1980-1992), and her current rank since 1992. Her research focuses on probability theory with specialization in Markov processes, stochastic modeling, and actuarial science education. She has led NSF grants like the 2009 Cincinnati Probability Symposium (PI) and collaborated on the Ohio Board of Regents health professions initiative (2010-2014). Her work includes seminal contributions on dual Markov processes, time reversal techniques, and random walks on trees. Notable publications include foundational studies in Annals of Probability and Stochastic Processes and Their Applications . She has held administrative roles including Associate Dean for Undergraduate Affairs (2008-2015).

Gabor N Sarkozyمشاهده پروفایل

استاد

• Graph Theory
• Discrete Mathematics
• Theoretical Computer Science
• +۳ مورد دیگر

Gabor N Sarkozy is a Professor in the Department of Computer Science at Worcester Polytechnic Institute (WPI). He holds a PhD from Rutgers University (1994) and completed a postdoc at the University of Pennsylvania (1994-1996). His research focuses on graph theory, discrete mathematics, and theoretical computer science, particularly the structure of large graphs and Ramsey-type problems. Education: BS, Eötvös University (1990); MS, PhD, Rutgers University (1994); Postdoc, University of Pennsylvania (1994-1996) His scholarly work spans over 100 publications, with notable collaborations with Endre Szemerédi, János Komlós, and András Gyárfás. Key contributions include algorithmic applications of the Blow-up Lemma, monochromatic cycle partitions, and advancements in Ramsey theory for hypergraphs and planar graphs. Professional highlights include the Good Teaching Award (1995) and the Doctor of the Hungarian Academy of Sciences (2009). He founded the Budapest Project Center, WPI's first project center in Eastern Europe, and remains actively engaged in educational data mining projects. Scientific Awards Good Teaching Award, 1995 Doctor of the Hungarian Academy of Sciences, 2009 His research trends over the past two decades show a transition from classical Ramsey theory and graph decomposition (1995-2010) to interdisciplinary applications in time series analysis and educational data mining (2011-2024), while maintaining core contributions to combinatorial graph theory. Advising and grants are not explicitly detailed in the provided texts, though his collaborative nature is evident through extensive co-authorships. He maintains active research groups at WPI and the Rényi Institute, with ongoing projects in Ramsey-type problems and algorithmic applications.

Margaret Bayerمشاهده پروفایل

استاد

• Combinatorics
• Discrete Geometry
• Convex Polytopes
• +۳ مورد دیگر

Margaret Bayer is a Professor in the Department of Mathematics at the University of Kansas, within the College of Liberal Arts & Sciences. She specializes in combinatorics and discrete geometry, with research focusing on convex polytopes, hyperplane arrangements, Eulerian posets, and flag vectors. Her work bridges combinatorics with algebraic geometry, particularly through connections to toric varieties. Her research explores the combinatorial structure of geometric objects, including face lattices of polytopes and the interplay between algebraic and geometric properties. Recent work includes studies on cut complexes of graphs, matching complexes, and applications of combinatorial methods in education and algorithm design. Bayer has authored/co-authored over 40 publications, including foundational works on flag vectors, the cd-index of Eulerian posets, and lattice polytopes derived from Schur polynomials. Her articles often address topics like polytope enumeration, topological properties of graph complexes, and combinatorial optimization in exam design. She serves as Book Review Editor for the Association for Women in Mathematics Newsletter and has advised numerous collaborative projects. Her teaching includes intermediate analysis and discrete mathematics courses.

• Extremal Combinatorics
• Probabilistic Combinatorics
• Discrete Probability
• +۶ مورد دیگر

Patrick Morris is a postdoctoral researcher in the GAPCOMB group at Universitat Politècnica de Catalunya (UPC) in Barcelona, funded by a Marie Curie fellowship. He holds a PhD in Combinatorics and Graph Theory from Freie Universität Berlin (2021), a Master's from the same institution, and a 4-year MSci from the University of Bristol. His research focuses on Extremal and Probabilistic Combinatorics with applications to Discrete Probability, Number Theory, and Algebraic Group Theory. Notably, his work on canonical Ramsey theorems earned a Best Paper Award at LAGOS 2023. His studies often explore structural properties of graphs and hypergraphs under random perturbations, with emphasis on Hamiltonicity, bootstrap percolation, and transversal problems. Collaborations include projects with Prof. Guillem Perarnau and Prof. Tibor Szabó, yielding impactful results in combinatorial theory. Education: PhD in Mathematics (2021), Freie Universität Berlin Master's in Combinatorics & Graph Theory (Freie Universität Berlin) MSci in Mathematics (University of Bristol, 2015) Research Interests: Extremal Combinatorics Probabilistic Combinatorics Bootstrap Percolation Hypergraph Theory Random Graphs Ramsey-Turán Theory Key Contributions: Over 15 peer-reviewed papers in top journals (e.g., Random Structures & Algorithms , Journal of Combinatorial Theory ), with focus on Hamilton cycles, clique factors, and canonical Ramsey-type theorems. His work bridges combinatorial structure and probabilistic methods, often addressing open problems in graph theory.

• Computational Social Science
• Data Science
• Multivariate Social Networks
• +۱۰ مورد دیگر

Termeh Shafie is a full-time Professor in the Department of Politics and Public Administration at the University of Konstanz, specializing in Computational Social Science and Data Science. With a strong statistical foundation, she develops advanced methodologies for analyzing multivariate social networks while bridging archaeological network reconstruction with modern data science techniques through projects like NEXUS 1492. Key Research Areas: Multigraph modeling, network entropy analysis, isotope geoprovenance, and hypergraph representations Projects: NEXUS 1492 archaeological network reconstruction Her 15 most recent publications demonstrate significant contributions to network methodology (random multigraph models, centrality index analysis), archaeological applications (Caribbean attack networks, Iroquoian settlement patterns), and data privacy frameworks. Articles span 2012–2025 with interdisciplinary focus on statistical sociology, archaeological theory, and computational modeling. Current teaching includes courses on social network analysis, data science, and statistical learning. Office hours available via ILIAS booking system. Contact details provided for both academic and administrative correspondence.

• Graph Theory
• Random Graph Theory
• Algorithms
• +۳ مورد دیگر

Stefanie Gerke is a Professor in the Department of Mathematics at Royal Holloway, University of London, where she joined in 2007 and is affiliated with the Centre for Algorithms and Applications. Her research spans discrete mathematics with emphasis on theoretical foundations and practical algorithmic applications. Her educational background includes a Diplom in Mathematics from Freie Universität Berlin followed by a PhD in Mathematics from the University of Oxford. She held prestigious postdoctoral positions at TU Munich (as a Bavarian Habilitationsfoerderpreis recipient) and ETH Zurich under Angelika Steger's group. Gerke's research focuses on graph theory, specializing in random graph structures, algorithmic solutions for combinatorial problems, and network analysis. Her work bridges theoretical computer science and discrete mathematics, with significant contributions to oriented graph theory, kernel conjectures, and economic network modeling. Recent publications demonstrate expertise in resolving longstanding graph theory conjectures through probabilistic methods and combinatorial optimization. Her publication trends (2023-2025) reveal concentrated work on oriented graph structures, anti-traceability properties, maximum cut problems, and economic network constraints. Key thematic threads include solving Seymour's and Sullivan's conjectures, developing bounds for directed cuts, and modeling public goods allocation in constrained networks, reflecting interdisciplinary applications from theoretical computer science to economic theory. Bavarian Habilitationsfoerderpreis Gerke has supervised 4 research students and secured significant funding including an EPSRC grant for "Successive Shortest Structures in Random Graphs" (2022-2023) and London Mathematical Society projects for "Probabilistic Combinatorics: Marking Colin McDiarmid's Retirement" (2016) and CMU-RHUL collaboration (2012). She actively participates in international combinatorics networks with recent collaborations across multiple countries. As a core member of Royal Holloway's Centre for Algorithms and Applications, she contributes to the university's discrete mathematics research ecosystem through collaborative projects, international workshops, and mentorship within the Department of Mathematics.

Marius Zimandمشاهده پروفایل

استاد

• computational complexity
• algorithmic information theory
• cryptography

Marius Zimand is a Professor in the Department of Computer and Information Sciences at Towson University. His academic expertise spans computational complexity , algorithmic information theory , and cryptography . Holding Ph.D.s in both Computer Science (University of Rochester) and Mathematics (University of Bucharest), he contributes to the advancement of randomness extraction and theoretical computer science. Education: Ph.D. in Computer Science (University of Rochester), Ph.D. in Mathematics (University of Bucharest) Zimand's research focuses on transforming low-quality randomness into high-quality randomness through efficient algorithms. His work, supported by NSF grants 0634830 (2006-2009) and 1016158 (2010-2014) , explores randomness extractors' applications in cryptography, error-correcting codes, and data structures, with mathematical implications in Kolmogorov complexity and constructive Hausdorff dimension. His recent publications analyze topics such as time-bounded Kolmogorov complexity , dynamic matching in expanders , and universal coding theorems , reflecting a consistent emphasis on randomness extraction and complexity theory. Awards include Best Paper at CSR'2008 and Best Paper at ICALP 2005, Track C . Professional Service: Editorial Board Member of Journal of Universal Computer Science Grant Reviewer for NSF, National Research Council Canada, ANR France, and US-Israel BSF Zimand's contributions to theoretical computer science bridge mathematical rigor with practical applications, maintaining active research and service roles within the academic community.

Tiantian Chenمشاهده پروفایل

استادیار

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Tiantian Chen is an Assistant Professor in the Department of Mathematics & Computer Science at Santa Clara University, part of the College of Arts and Sciences. Their research focuses on artificial intelligence, machine learning, and social network analysis with applications to cybersecurity, privacy preservation, and algorithmic optimization. Educational background includes B.S. and M.S. from Ocean University of China, followed by M.S. and Ph.D. from the University of Texas, Dallas. Their work emphasizes interdisciplinary approaches to computational problems in social networks and data-driven systems. Recent research trends include deep reinforcement learning for influence maximization, blockchain-based privacy frameworks, and combating cyberbullying using AI. Their publications span topics such as graph representation learning, rumor blocking mechanisms, and budgeted profit maximization algorithms. No scientific awards have been explicitly mentioned in the provided information. Advising activities and grant details are not listed here. Tiantian Chen contributes to the department's academic programs and computational research initiatives.

Emmanuel Stefanakisمشاهده پروفایل

استاد

• Geospatial Data Science
• Digital Earth
• Discrete Global Grid Systems (DGGS)
• +۱۷ مورد دیگر

Emmanuel Stefanakis is a Professor and Department Head of Geomatics Engineering at the Schulich School of Engineering, University of Calgary. He holds a PhD in Electrical and Computer Engineering (National Technical University of Athens, 1997), an MScE in Geodesy and Geomatics Engineering (University of New Brunswick, 1994), and a Dipl.Eng in Rural and Surveying Engineering (National Technical University of Athens, 1992). His research focuses on Geospatial Data Science, Discrete Global Grid Systems (DGGS), GeoAI, and applications of Geomatics in natural hazards, transportation, and climate change . He has led over 140 student projects and authored/co-authored five textbooks and 150+ articles. Notable awards include the 2023 Canadian Cartographic Association’s Award of Distinction and the 2023 UCalgary Teaching Excellence Award. Recent articles emphasize high-performance trajectory analysis, DGGS integration, and geospatial quantum computing . His work bridges theoretical advancements with practical tools for flood modeling, epidemiology, and urban planning. Grants include NSERC Discovery Grants and collaborations with industry partners like McElhanney Ltd. Professional memberships span the Canadian Institute of Geomatics, Canadian Cartographic Association, and APEGA. He served as Editor-in-Chief of Cartographica (2014–2022) and actively contributes to international conferences on geoinformatics. His educational initiatives include innovative course designs in online and distance learning. Current roles include leadership in the HALOS and Geospatial Quantum Computing projects, advancing geomatics engineering education in the digital era.

Simon Coxمشاهده پروفایل

استاد

• Brain and Cognitive Ageing
• Neuroimaging
• Lifecourse Correlates of Brain Structure
• +۳ مورد دیگر

Professor Simon Cox is a leading academic in brain and cognitive ageing at the University of Edinburgh's School of Philosophy, Psychology and Language Sciences. As a Sir Henry Dale Fellow and Director of the Lothian Birth Cohort Studies, he investigates lifecourse determinants of brain structure and cognitive differences using multi-cohort neuroimaging and genomic data. Principal Investigator on Age UK, BBSRC, ESRC, and NIH-funded projects Research focuses on neurodevelopment, epigenetics, and environmental influences on ageing Research Interests span: Brain-cognition relationships across the lifespan Multi-omics approaches to neurodegeneration Environmental and genetic mediators of cognitive decline Neuroimaging methodology development Frailty and multimorbidity in ageing populations Life-course epidemiology of brain health Selected Publications (2023-2025) reveal trends in: Epigenetic biomarkers of brain ageing Genomic structural equation modeling Environmental impacts (air pollution, socioeconomic status) Neuroinflammation and mental health Connectomic analysis of depression Vascular risk and brain structure Scientific Awards : Sir Henry Dale Fellowship National Institute on Aging R01 funding NIH RF1 grant for Alzheimer's research PhD Supervision includes projects on: PRENCOG cohort (preterm birth effects) Wellcome-funded mental health data science Translational neuroscience (15+ students)

Roman Vershyninمشاهده پروفایل

استاد

• High-Dimensional Probability
• Random Matrices
• Applied Mathematics
• +۴ مورد دیگر

Roman Vershynin is a Professor in the Department of Mathematics at the University of California, Irvine (UCI). His research focuses on high-dimensional probability, random matrices, and their applications in data science, machine learning, and privacy-preserving technologies. He is particularly known for his work on the theoretical foundations of differential privacy, synthetic data generation, and the mathematical underpinnings of neural networks. Vershynin’s contributions bridge probability theory with practical challenges in high-dimensional data analysis. His research interests include random matrix theory, geometric functional analysis, and the interplay between probability and computational complexity. Notable works include developing frameworks for differentially private synthetic data and analyzing the capacity of neural networks. He authored the influential textbook High-Dimensional Probability: An Introduction with Applications in Data Science , which is a key resource in the field. Vershynin’s recent work emphasizes the privacy-utility tradeoff in synthetic data generation, leveraging tools from metric geometry and stochastic processes. He collaborates on projects funded by the National Science Foundation, focusing on mathematical frameworks for high-dimensional data analysis and algorithmic privacy. His research has implications for secure machine learning, compressed sensing, and robust statistical estimation.

Jingjing Mengمشاهده پروفایل

پژوهشگر

• Multimedia
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Jingjing Meng is a Senior Scientist affiliated with the Computer Science and Engineering Department at the University at Buffalo, SUNY, and Amazon. She holds a Ph.D. from Nanyang Technological University (NTU, Singapore), advised by Prof. Yap-Peng Tan, along with an M.S. from Vanderbilt University and a B.E. from Huazhong University of Science & Technology, China. Her research focuses on multimedia, large multimodal models, product recommendation/search, and computer vision applications. Notable contributions include work on surgical triplet recognition, 3D object representation, and video summarization. She has received the 2016 IEEE Transactions on Multimedia Best Paper Award. Service Roles: Technical Program Co-Chair (ICME 2024), Tutorial Co-Chair (ACM MM 2024), Area Chair (AAAI 2021-2025), and Associate Editor for IEEE TMM, Signal Processing: Image Communication, and others. Leadership: Member of IEEE IVMSP TC, VSPC TC, and MSA TC committees, and a Senior Member of IEEE. Teaching includes courses like Multimedia Systems (CSE 534), Computer Graphics (CSE 410/580), and Discrete Structures (CSE 191). Her work bridges theoretical advancements and practical applications in multimedia and AI.

Neal Madrasمشاهده پروفایل

استاد

• Probability Theory
• Discrete Mathematics
• Mathematical Modeling in the Sciences
• +۵ مورد دیگر

Neal Madras is a Full Professor in the Department of Mathematics and Statistics at York University's Faculty of Science. His research focuses on probability theory, discrete mathematics, and mathematical modeling in the sciences. He explores applications in statistical mechanics, theoretical computer science, communications networks, and biological systems. Notable interests include self-avoiding walks, polymer behavior modeling, and disease progression mechanisms. Madras has contributed to interdisciplinary studies, such as HIV dynamics and mosquito population modeling under climate influences. He is also actively involved in mathematics competitions like the Canadian Mathematical Olympiad. His work bridges theoretical rigor and practical applications, with a focus on stochastic processes, combinatorial problems, and computational methods. Publications span topics from graph theory and knot invariants to epidemic control strategies and polymer adsorption. Madras maintains an active research program, engaging with both foundational mathematical questions and real-world problem-solving.

Dimitris Koukoulopoulosمشاهده پروفایل

استاد

• Analytic Number Theory
• Multiplicative Number Theory
• Probabilistic Number Theory
• +۴ مورد دیگر

Dimitris Koukoulopoulos is a Professor of Mathematics at the Department of Mathematics and Statistics, Université de Montréal, where he holds the Chaire Courtois II in fundamental research. He is a member of the Centre de recherches mathématiques and the Montreal Number Theory Group. His research focuses on analytic number theory, with an emphasis on multiplicative and probabilistic aspects, the anatomy of integers and permutations, sieve methods, diophantine approximation, and additive combinatorics. His research explores core questions in number theory, including the distribution of prime numbers, probabilistic properties of integers, and the application of sieve methods to Diophantine problems. Recent work highlights include studies on multiplicative functions, random polynomials, and the Erdős–Hooley Delta function, demonstrating a blend of analytical and combinatorial techniques. Professor Koukoulopoulos actively mentors M.Sc. and Ph.D. students, emphasizing alignment with his research interests. His work contributes to the Montreal Number Theory Group’s collaborative research environment, fostering interdisciplinary advancements in number theory.