جست‌وجوی استاد و پژوهشگر

Shonda Dueckمشاهده پروفایل

دانشیار

• Algebraic Graph Theory
• Algebraic Hypergraph Theory
• Group Actions on Combinatorial Structures
• +۳ مورد دیگر

Shonda Dueck is an Associate Professor in the Department of Mathematics and Statistics at the University of Winnipeg . She holds a Ph.D. in Mathematics from the University of Ottawa, a Master of Mathematics from the University of Waterloo, and a B.Sc. (Honours) from the University of Winnipeg. Her research focuses on algebraic graph and hypergraph theory, particularly on group actions on combinatorial structures, cyclic partitions of hypergraphs, and metric dimension problems. Research Interests include: Algebraic graph theory and hypergraph theory Self-complementary and t-complementary graphs/hypergraphs Hypergraph decompositions using group actions Metric and partition dimension of Cayley hypergraphs Large sets of combinatorial designs Her recent publications analyze metric dimension in circulant graphs, cyclic partitions of hypergraphs, and threshold dimension problems. She has also contributed to understanding Hamiltonian paths in Cayley digraphs and vertex-transitive hypergraph structures. Affiliations: Adjunct Professor, Faculty of Graduate Studies and Research, University of Regina (2017–2022)

Shaoning Hanمشاهده پروفایل

استادیار

• Mathematical Optimization
• Mixed-Integer Nonlinear Programming
• Nonsmooth Optimization
• +۳ مورد دیگر

Shaoning Han is a Presidential Young Professor (Assistant Professor) in the Department of Mathematics and the Institute of Operations Research and Analytics (IORA) at the National University of Singapore (NUS). He previously held a postdoctoral position at the University of Southern California (USC), working under Prof. Jong-Shi Pang. His research focuses on mathematical optimization, including mixed-integer nonlinear programming, nonsmooth optimization, and their applications in operations research and data science. Han earned his Ph.D. in Industrial Engineering from USC under Prof. Andrés Gómez and a B.S. in Mathematics from the University of Science and Technology of China (USTC). His work emphasizes advancing optimization methodologies, particularly for problems involving complementarity constraints, indicator variables, and sparsity. Recent contributions include progressive MIP methods for indefinite QPs, real-time solutions for banded matrix problems, and convexification techniques for nonconvex optimization. Han is actively recruiting PhD students interested in mathematical optimization. Research Highlights: His articles span theoretical advances (e.g., epi-stationarity analysis, parametric variational inequalities) and applied frameworks (e.g., robust SVMs, binarized neural networks). Key themes include polynomial-time solvability of MRFs, convex relaxations for low-rank functions, and sparse signal estimation. Awards: Third Place, INFORMS JFIG Paper Competition (2023) Journal of Global Optimization Best Paper Honorable Mention (2023) Teaching: Courses include MA5243 (Advanced Mathematical Programming) and MA3252 (Linear and Network Optimization). Labs/Teams: Active member of IORA, NUS’s Smart Nation Research Cluster.

• Operations Research
• Optimization
• Mathematical Programming
• +۵ مورد دیگر

Marianna De Santis is an Associate Professor in the Department of Information Engineering (Dipartimento di Ingegneria dell’Informazione) at the University of Florence, Italy. She previously held positions at Sapienza University of Rome and other institutions. Her research focuses on optimization, particularly in multiobjective programming, mixed-integer programming, and algorithm design. She has authored numerous articles in top journals and developed software tools like BBMOQIP and MOMIX for solving complex optimization problems. Education : PhD in Operations Research, Sapienza University of Rome (2012) MSc in Applied Mathematics (2007), BSc in Mathematics (2005) Research Interests : Dr. De Santis specializes in optimization theory and applications, including multiobjective optimization, integer programming, and algorithm design. Her work bridges theoretical advancements with practical implementations, addressing challenges in machine learning, bioinformatics, and operations research. Key areas include semidefinite programming, robust optimization, and exact methods for complex combinatorial problems. Articles Trends : Her recent work emphasizes multiobjective optimization, with contributions to hyperparameter optimization, robust combinatorial methods, and sustainable modeling. Publications span journals like Journal of Global Optimization and Mathematical Programming , reflecting her expertise in algorithmic innovation and mathematical rigor. Grants & Teaching : She leads projects on augmented Lagrangian methods and multiobjective integer optimization. Teaching includes courses on operations research, optimization, and data science at the undergraduate and graduate levels. She has also organized international workshops and served on conference committees. Labs/Teams : Her research group develops optimization software (e.g., BBMOQIP) and collaborates internationally on projects involving algorithm design and real-world applications.

Kamil Khanمشاهده پروفایل

دانشیار

• Deterministic Global Optimization
• Process Systems Engineering
• Sensitivity Analysis
• +۶ مورد دیگر

Dr. Kamil Khan is an Associate Professor of Chemical Engineering at McMaster University , part of the Faculty of Engineering . His research focuses on deterministic global optimization, nonsmooth optimization, and dynamic optimization of chemical process systems, integrating applied mathematics and algorithm development. He holds a B.S.E. from Princeton University, M.S. and Ph.D. from MIT, and completed a postdoc at Argonne National Laboratory. He teaches CHEM ENG 4E03/6E03: Digital Computer Process Control , covering digital control systems and model predictive control. His lab, the Khan Research Group , explores topics like convex relaxations, automatic differentiation, and adjoint sensitivity analysis for process optimization. Recent work includes advancements in computational methods for dynamic systems, membrane fouling prediction in water treatment plants, and subgradient evaluation for global optimization. His research bridges theoretical mathematics with practical engineering challenges.

Mark Steyversمشاهده پروفایل

استاد

• Cognitive Science
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Mark Steyvers is a Professor and Chair of Cognitive Sciences at the University of California, Irvine, with a joint appointment in the Computer Science Department and affiliation with the Center for Machine Learning and Intelligent Systems. His research bridges cognitive science, AI, and machine learning, focusing on human-AI collaboration, decision-making, and large-scale cognitive data analysis. He holds editorial roles at journals like Computational Brain and Behavior and Psychological Review . Education: PhD from Indiana University, Postdoctoral Fellowship at Stanford University. His work is funded by NSF, NIH, IARPA, and defense agencies. Awards include New Investigator Awards from APA and the Society of Experimental Psychologists, and recognition for collaborative work with Lumosity. Research interests include: (1) Human-AI systems optimizing interaction and team performance, particularly in mental model development and metacognition; (2) Leveraging Lumosity's cognitive training data to study real-world learning at scale. Recent articles explore AI-assisted decision-making challenges, large language model capabilities, and Bayesian modeling approaches. Grants and collaborations involve government agencies and companies like eBay, Netflix, and Merriam-Webster. He leads the MADLAB, focusing on interdisciplinary cognitive science and machine learning projects.

Zsolt Darvayمشاهده پروفایل

دانشیار

• Optimization
• Operations Research
• Linear Programming
• +۳ مورد دیگر

Zsolt Darvay is an Associate Professor at Babeş-Bolyai University in Cluj-Napoca, Romania. He is affiliated with the Faculty of Mathematics and Computer Science, specifically the Department of Mathematics and Computer Science of the Hungarian Line. His academic career spans over two decades, with roles including Lecturer and Assistant Professor before his current position since 2019. His research focuses on optimization theory, particularly interior-point methods for linear and symmetric cone complementarity problems, algorithm design, and computational mathematics. He has authored numerous publications in top-tier journals and conference proceedings, contributing to the advancement of numerical optimization techniques and their implementations in programming languages like Java. Darvay has presented his work at conferences such as the International Symposium on Operational Research (SOR) and the Hungarian Scientific Days in Transylvania. His teaching activities include courses on advanced programming, optimization techniques, and software design patterns. Despite extensive contributions to academia, no specific scientific awards are explicitly mentioned in the provided information.

Johannes Boehmمشاهده پروفایل

استاد

• International Trade
• Development Economics
• Environmental Economics
• +۷ مورد دیگر

Johannes Boehm is a Professor of International Economics at the Geneva Graduate Institute, where he also holds a position in the Department of International Economics. He is a research fellow at the Centre for Economic Policy Research (CEPR) in London and the Centre for Economic Performance (CEP) at the London School of Economics. Previously, he was a professor at Sciences Po, Paris, and has held visiting positions at Princeton University, Harvard University, and INSEAD. His research focuses on international trade, industrial development, growth, and environmental economics, with a particular emphasis on how trade networks influence economic growth and resilience to geopolitical and climate risks. Boehm earned his PhD in Economics from the London School of Economics in 2014. His work explores the interplay between trade policies, firm dynamics, and macroeconomic outcomes, including studies on supply chain fragmentation, climate adaptation, and historical trade patterns. Notable research includes analyzing how extreme weather events impact production networks in Pakistan and investigating the historical shift of economic activity post-antiquity using ancient coin data. His thematic expertise spans trade policy, globalization, development cooperation, climate change, and central bank policies. Geographically, his research covers the Americas, Asia, and Europe. Boehm is also involved in software development for econometric analysis, creating tools like GLFixedEffectModels and Douglass to facilitate high-dimensional fixed-effects modeling and data manipulation.

• Bilevel Optimization
• Numerical Methods
• Nonsmooth and Nonconvex Optimization
• +۷ مورد دیگر

Alain Zemkoho is a Professor of Mathematical Optimization at the School of Mathematical Sciences, University of Southampton. He is affiliated with the OR Group and CORMSIS. His research focuses on bilevel optimization, numerical methods, and applications in transportation, healthcare, cybersecurity, and machine learning. He holds prestigious fellowships including the Alexander von Humboldt Experienced Fellowship (2024-2026) and Alan Turing Institute Fellowship (2019-2023). Research Interests: Bilevel and hierarchical optimization Numerical methods for continuous optimization Nonsmooth and nonconvex optimization Stability/sensitivity analysis Variational analysis Recent Research Trends: His work spans algorithm development for pessimistic/optimistic bilevel problems, cybersecurity applications using game theory and honeypots, and healthcare optimization via deep learning for S-ICD patient screening. Over 15 recent articles (2022-2025) address topics like trajectory optimization for UAVs, adversarial machine learning, and hyperparameter tuning for SVMs. Scientific Awards: Alexander von Humboldt Experienced Fellow Fellow of the Alan Turing Institute Institute of Mathematics & Its Applications Fellow Higher Education Academy Fellow Advising & Labs: Currently supervising 4 PhD students in Mathematical Sciences. Active in the OR Group and CORMSIS research teams, collaborating on interdisciplinary projects.

Hélène Carabinمشاهده پروفایل

استاد

• Epidemiology
• Zoonotic diseases
• One Health
• +۱ مورد دیگر

Hélène Carabin is a Full Professor jointly appointed in the Faculty of Veterinary Medicine and School of Public Health at Université de Montréal, holding the Tier 1 Canada Research Chair in Epidemiology and One Health. She earned her Ph.D. from McGill University in 1998. Research Focus Her work advances the 'One Health' framework, examining intersections between human, animal, and environmental health. Research includes zoonotic disease prevention, climate-health linkages, and sustainable urban ecosystems. Publications Overview Recent articles address climate communication efficacy, pandemic governance, and health equity in vulnerable communities. Work demonstrates consistent integration of epidemiological methods with policy analysis. Awards U.S. National Academy of Medicine Member (2023) L'Oréal-UNESCO For Women in Science Award (2023) Alfort Prize (2020) Leadership Directs multidisciplinary teams investigating disease surveillance systems and health impacts of environmental change. Secured $46.5M in research funding across 32 grants.

• Quantum Physics
• Quantum Information
• Quantum Metrology
• +۳ مورد دیگر

Dr. Matteo Fadel is a Lecturer in the Department of Physics at ETH Zürich, affiliated with the Professur Hybride Quantensysteme (Hybrid Quantum Systems Group). His research focuses on quantum physics, quantum information, and quantum metrology, with particular emphasis on mechanical systems, Bose-Einstein condensates, and spin squeezing phenomena. Fadel explores theoretical and experimental aspects of macroscopic quantum coherence, entanglement dynamics, and quantum gravitational effects. He has contributed to developing protocols for detecting non-locality and Bell correlations in many-body systems, as well as advancing quantum teleportation and remote state preparation techniques. Research Interests : Quantum non-Gaussianity, entanglement quantification, precision measurement, topological quantum systems, and gravity-related quantum effects. His work bridges theoretical studies with experimental implementations, such as parity measurements in circuit quantum acoustodynamics and spin squeezing in atomic ensembles. Fadel’s contributions span both foundational quantum theory and applied quantum technologies, including novel approaches to distributed quantum sensing and metrological complementarity. While no specific grants or awards are listed in the text, his publications reflect sustained engagement with cutting-edge topics in quantum physics. Advising details and lab affiliations are not explicitly provided, but his research group likely focuses on hybrid quantum systems and their applications in sensing and computation. His research also touches on machine learning for bosonic functionals and the quantum marginal problem in many-body systems.

Shihao Zhuمشاهده پروفایل

پژوهشگر

• Insurance Mathematics
• Financial Mathematics
• Stochastic Control
• +۳ مورد دیگر

Dr. Shihao Zhu is a postdoctoral researcher at the Institute of Insurance Science (IVW) at Ulm University since February 2024. He completed his Ph.D. in Mathematics at Bielefeld University, Germany (January 2021 - June 2024), supervised by Prof. Dr. Giorgio Ferrari at the Center for Mathematical Economics (IMW). His academic affiliation at Ulm University involves collaboration with Prof. Dr. An Chen. Education : Ph.D. in Mathematics, Bielefeld University (2021-2024) Current Role : Postdoc Researcher at Ulm University's Institute of Insurance Science (IVW) His research focuses on stochastic control models, insurance mathematics, and financial optimization under uncertainty. Key areas include dividend policies, reinsurance strategies, retirement planning, and health-wealth complementarities. The work often involves Markov-modulated environments and ambiguity modeling. Recent publications demonstrate expertise in solving free-boundary problems, stochastic dynamic programming, and actuarial risk modeling. Topics span optimal consumption, life insurance timing, and irreversible healthcare investment frameworks, reflecting interdisciplinary applications of mathematics in finance and insurance.

Marco Pellicciaمشاهده پروفایل

استادیار

• Microeconomics
• Game Theory
• Economics of Networks
• +۷ مورد دیگر

Marco Pelliccia is an Assistant Professor at the Edinburgh Business School, School of Social Sciences, Heriot-Watt University, United Kingdom. He is actively engaged in research and teaching in economic theory, with a focus on strategic behavior in networked environments. He teaches courses such as Intermediate Economics I, Introduction to Economic and Financial Analysis, and Public Choice and Welfare Economics, and is currently accepting PhD students. His research lies at the intersection of microeconomics, game theory, and network economics. Key interests include mechanism design, defense of network structures, and investment in security within interconnected systems. His work applies theoretical models to real-world problems such as decentralized defense and trade network vulnerabilities. His recent publications explore the economics of network defense and centrality in trade networks, showing trends toward applying game-theoretic tools to security and allocation problems in complex systems. These works emphasize equilibrium behavior, strategic interdependence, and efficiency in decentralized settings. Decentralized Defence of a (Directed) Network Structure (2020) Centrality in Trade Networks and Investment in Security (2016) Marco Pelliccia has delivered multiple invited and oral presentations at international conferences such as Sunbelt 2024, Coalition Theory Network 24, and the Conference on Economic Design. He is actively involved in the academic community, particularly in forums related to economic theory and institutional design. While no grants or specific student names are listed, his supervision of PhD students is explicitly noted, indicating active mentorship. He is associated with the research ecosystem at Heriot-Watt University, contributing to the intellectual life of the Edinburgh Business School through teaching, research dissemination, and participation in academic networks focused on economic design and coalition theory.

• Mathematical Biology
• Partial Differential Equations
• Chemotaxis Models
• +۵ مورد دیگر

Prof. Johannes Lankeit is a Professor at the Institute for Applied Mathematics (IfAM) within the Faculty of Mathematics and Physics at Leibniz University Hannover. His research focuses on mathematical analysis of chemotaxis models, partial differential equations, and their applications in biological and biomedical contexts. Research Interests: Models of mathematical biology Chemotaxis systems and their qualitative properties Partial differential equations (PDEs) and nonlinear analysis Blow-up phenomena in parabolic systems Reaction-diffusion systems with chemotaxis Recent work includes analysis of chemotaxis-consumption interaction, tuberculosis granuloma formation, and cancer invasion models. His articles frequently address global solvability, asymptotic behavior, and critical mass thresholds in PDE systems. Teaching: Responsible for advanced courses in applied mathematics and PDEs at the undergraduate and graduate levels. Publications: Over 50 peer-reviewed articles in top journals like Nonlinear Analysis , Journal of Differential Equations , and SIAM Journal on Mathematical Analysis .

Yamuna Baburajمشاهده پروفایل

دانشیار

• Strategic Management
• Organizational Behavior
• International Business
• +۳ مورد دیگر

Yamuna Baburaj, PhD, is an Associate Professor in the Department of Management at Widener University's School of Business Administration. Her research focuses on strategic management, organizational behavior, and international business. She holds a PhD in Strategic Management from Drexel University (2014). Dr. Baburaj is affiliated with programs including International Business (BSBA), Management (BSBA), Business Administration (MBA), and dual-degree programs combining Clinical Psychology with Business. Her work emphasizes career-preparedness curricula integration, global learning alternatives to study abroad, and strategic use of star employees. She has co-authored studies on product complementarity's impact on governance decisions and R&D team optimization. Education: PhD in Strategic Management, Drexel University (2014) Research interests span strategic alliances, human capital management, and innovation governance. Recent collaborations include articles on career-readiness programs and cross-cultural learning models. Active in professional networks like the Academy of Management.

Giancarlo Bigiمشاهده پروفایل

دانشیار

• Operations Research
• Optimization
• Equilibrium Problems
• +۷ مورد دیگر

Giancarlo Bigi is an Associate Professor of Operations Research in the Department of Computer Science at the University of Pisa, Italy. He has been a faculty member since 2000, advancing from Assistant Professor to Associate Professor in 2017. He holds a Ph.D. in Mathematics from the University of Pisa and has achieved national habilitations for both full and associate professorship in Operations Research and Mathematical Methods of Economics. His research is centered on optimization and equilibrium problems, with a strong focus on variational inequalities, game theory, multiobjective optimization, and nonlinear programming. He develops theoretical frameworks and algorithmic solutions for complex equilibrium models, including applications in economics and energy markets. The recent publications highlight a consistent trend in developing and analyzing gap functions, descent algorithms, and penalization techniques for equilibrium and hierarchical programming problems. His work bridges theoretical optimization with practical applications, particularly in modeling oligopolistic markets and decentralized energy systems. Associate Professor, Department of Computer Science, University of Pisa (2017–present) Assistant Professor, Department of Computer Science, University of Pisa (2000–2017) Ph.D. in Mathematics, University of Pisa (1997–2003) Bigi has no explicitly listed scientific awards in the provided material. He has not published any acknowledgments of grants, but his sustained research output suggests ongoing funding support. He collaborates extensively with researchers such as Mauro Passacantando, Marco Castellani, and Massimo Pappalardo. He is affiliated with the Operations Research Group within the Department of Computer Science at the University of Pisa, contributing to a collaborative research environment focused on optimization and decision-making models.