Find Academic Supervisors

Mohamed-Yahia DabbaghView profile

Associate Professor

• Digital Signal Processing
• Image Processing
• Video Processing
• +6 more

Mohamed-Yahia Dabbagh is an Associate Professor, Teaching Stream in the Department of Electrical and Computer Engineering at the University of Waterloo. He holds a PhD from North Carolina State University (1989), an MSE from the University of Michigan (1981), and a BSE from the University of Aleppo (1976). His research focuses on digital signal processing, image/video processing, and VLSI multiprocessor implementation of algorithms for communication systems and computer vision. He has developed architectures for digital filters and explored video motion estimation, segmentation, and pattern recognition. Dr. Dabbagh has authored numerous articles in IEEE and other venues, including work on wireless sensor anomaly detection, smartphone application monitoring, and FPGA-based digital filter implementations. His teaching includes courses such as Signals and Systems (ECE 207), Linear Circuits (ECE 140), and Probability and Random Processes (ECE 316). His research has spanned VLSI environments, Bayesian classification for video processing, and real-time signal processing techniques. Notable contributions include multiprocessor filter implementations and adaptive motion estimation algorithms. Dr. Dabbagh is a Professional Engineer (PEng) registered in Ontario and has contributed to technical reports on imaging systems and geographic information systems during his tenure at Kuwait-based institutions.

Matthew StreetView profile

Senior Lecturer

• Education
• Foreign Language Teaching
• Project-Based Learning
• +3 more

Professor Matthew Street is a Senior Lecturer in the Department of Spanish at the University of Virginia's College of Arts and Sciences. He specializes in innovative educational methodologies, focusing on ePortfolios, project-based learning, and active learning in foreign language courses. His teaching practices incorporate flipped classrooms and emphasize creating collaborative, interactive learning environments. While his academic career centers on Spanish education, his research portfolio reveals a parallel focus on financial modeling and credit risk analysis dating back to the 1990s. Dr. Street's publications demonstrate expertise in credit scoring systems, economic modeling, and financial risk management. His work spans topics like neural networks in credit assessment, regulatory capital requirements, and energy-efficient mortgage risk. Notably, he combines machine learning approaches with traditional financial modeling techniques in consumer lending contexts. The most recent 15 publications reflect a consistent focus on credit risk frameworks, portfolio optimization, and decision-making under uncertainty. His academic journey includes significant contributions to credit union research, dental practice economics, and hotel market feasibility studies. While no specific awards or students are mentioned in the provided text, his work on educational technologies like ePortfolios and his dual expertise in language education and financial modeling highlight unique interdisciplinary achievements.

Katharina ProkschView profile

Researcher

• Statistics
• Biomedical Imaging
• Data Analysis
• +4 more

Katharina Proksch is a researcher specializing in advanced statistical methodologies and their applications across diverse scientific domains. Her work focuses on regression models, simultaneous inference, and transforms, with notable contributions to nonparametric testing, inverse problems, and quantitative imaging techniques. She explores interdisciplinary applications in biomedical imaging, astrophysics, and biomechanical analysis, emphasizing rigorous statistical frameworks to ensure methodological robustness. Her research interests include developing statistical tools for super-resolution microscopy, fatigue detection through biomechanical data, and analyzing complex datasets from fluorescence microscopy and X-ray astronomy. Proksch's methodologies often address challenges in handling measurement errors, outliers, and multiscale data structures. Key contributions include a two-sample test using Wilcoxon rank sums, quantitative super-resolution microscopy techniques with statistical guarantees, and fatigue detection algorithms leveraging sequential testing. Her work bridges theoretical statistics with practical applications in health monitoring and astrophysical phenomena modeling.

• Climate Dynamics
• Statistical Mechanics
• Nonlinear Systems
• +4 more

Valerio Lucarini is a Professor of Climate Dynamics at the University of Reading's Department of Meteorology. His research focuses on the theoretical foundations of climate science, nonlinear dynamics, and statistical mechanics, with particular emphasis on climate tipping points, extreme events, and the application of dynamical systems theory to geophysical flows. He has contributed to understanding the response of climate systems to external forcings and the development of novel methods for climate model evaluation. Key research areas include: Climate sensitivity and predictability Non-equilibrium thermodynamics in atmospheric and oceanic systems Extreme event analysis using large deviation theory Mathematical frameworks for climate variability His recent work investigates multistability in ocean circulation, stochastic parameterization techniques, and the interplay between climate forcings and system response. Lucarini collaborates extensively with international teams and contributes to interdisciplinary projects on climate resilience and Earth system modeling.

Bob JantzenView profile

Professor

• General Relativity
• Cosmology
• Differential Geometry
• +4 more

Robert T. Jantzen is a Professor in the Department of Mathematics and Statistics at Villanova University, affiliated with the College of Arts and Sciences. He holds an A.B. in Physics from Princeton University (1974) and a Ph.D. in Physics from UC Berkeley (1978), specializing in general relativity. His research focuses on mathematical general relativity, cosmology, differential geometry, and Lie groups, with collaborations at institutions like the University of Rome's ICRA. He teaches applied mathematics courses, coordinates the Differential Equations with Linear Algebra course, and advocates for active learning in STEM education. Notable awards include the 2018 Mendel Award. His work bridges mathematics and physics, exploring topics like gravitoelectromagnetism and spacetime splitting. He is an honorary member of the Italian research group G9 and contributes to interdisciplinary projects, including climate change advocacy. Education A.B. in Physics, Princeton University, 1974 Ph.D. in Physics, UC Berkeley, 1978 Research Interests Focuses on general relativity, cosmological models with symmetry, observer-based spacetime analysis, gravitoelectromagnetism, differential geometry, and applications of Lie groups. His work integrates abstract mathematics with physical interpretation, often using computational tools like Maple. Publications & Talks His articles appear in journals like Classical and Quantum Gravity and General Relativity and Gravitation . Recent talks include discussions on geodesics on pasta surfaces and relativity. He has organized international conferences, including Marcel Grossmann Meetings, and co-edited their proceedings. Teaching & Innovation Develops Maple-based educational resources for calculus and differential equations. Emphasizes active learning, problem-solving, and technical communication. Maintains extensive course materials, including quizzes, tests, and grade calculators. Collaborations & Outreach Collaborates with Italian researchers on relativistic astrophysics. Engages in public science communication and progressive activism, supporting independent media and climate change initiatives. Serves as faculty advisor for student groups like the Armenian Student Organization and Villanova Against Sweatshops. Labs & Teams Active in the International Center for Relativistic Astrophysics (ICRA) network and the Vatican Observatory collaboration. Leads interdisciplinary projects blending mathematics, physics, and technology.

Zhu YutingView profile

Assistant Professor

• Operations Research
• Marketing Optimization
• Algorithm Design
• +3 more

Zhu Yuting is an Assistant Professor at the Institute of Operations Research and Analytics (IORA), part of the National University of Singapore's Smart Nation Research Cluster. Their research focuses on optimizing marketing policies, algorithm design, and data-driven decision-making, with applications in e-commerce, ridesharing, and freelance platforms. Key contributions include work on recommender systems for missing data, linear programming in sponsored listings, and understanding algorithm aversion in user communities. Education details are not explicitly provided in the text, but their research portfolio reflects advanced expertise in operations research and machine learning. Research interests are centered around scalable marketing strategies, algorithmic transparency, and behavioral dynamics in digital markets. Publications span topics like dynamic policy optimization, group search strategies, and the impact of algorithms on user trust. While no formal awards are listed, their active participation in field experiments and interdisciplinary projects underscores their scholarly impact. Zhu Yuting’s work is conducted under the IORA framework, which emphasizes Smart Nation applications, and involves collaborations on reinforcement learning and experimental marketing. No specific grants or advising roles are detailed in the provided text.

Michael BardzellView profile

Professor

• Abstract Algebra Visualization
• Cellular Automata
• Undergraduate Research Mentorship
• +3 more

Michael Bardzell is a Professor in the Department of Mathematical Sciences at Salisbury University's Henson School of Science and Technology. With 30 years of service at the institution, he has established himself as an educator deeply committed to undergraduate teaching and mentorship. His research focuses on visualizing abstract mathematical concepts, particularly through the PascGalois Project which explores connections between group theory, cellular automata, and Pascal's Triangle. Bardzell has developed educational software including Celite , a collection of cellular automaton simulators that demonstrates computational universality and emergent behaviors. His scholarly work reveals consistent themes in mathematical visualization, with particular emphasis on making abstract algebra accessible through computational methods. The progression of his presentations shows increasing sophistication in connecting theoretical mathematics with practical educational applications, especially through software development. As an educator, Bardzell has dedicated significant effort to mentoring undergraduate research and software engineering students. His work extends beyond campus through extensive K-12 outreach programs, professional development workshops for public school teachers, and collaborations with neighboring counties on curricular design. His laboratory work centers around the development and application of mathematical visualization tools, particularly the PascGalois Project and Celite software suite, which serve as platforms for both research and education in discrete mathematics and abstract algebra.

Jun ZhuView profile

Professor

• Spatial statistics
• Spatio-temporal statistics
• Markov random fields
• +7 more

Jun Zhu is a Professor of Statistics at the University of Wisconsin-Madison, affiliated with the Department of Statistics and cross-listed in the Department of Entomology, Department of Biostatistics and Medical Informatics, and the Center for Demography and Ecology. His research focuses on spatial and spatio-temporal statistical methodologies, applied to ecological, environmental, agricultural, and health systems. He holds prestigious awards including the Distinguished Achievement Medal from the American Statistical Association and election to the International Statistical Institute. Education: PhD in Statistics (Iowa State University, 2000), MSE in Mathematical Sciences (Johns Hopkins University, 1995), BA in Mathematics and Computer Science (Knox College, 1994). Research emphasizes methodological development for spatial data analysis, with applications in agriculture, ecology, and public health. Key contributions include cluster detection algorithms, spatial regression models, and spatio-temporal analyses of environmental and demographic phenomena. His work bridges theoretical statistics with interdisciplinary collaborations, addressing real-world challenges such as disease mapping and climate change impacts. Scientific Awards: Distinguished Achievement Medal (ASA) Elected Member (International Statistical Institute) Fellow (American Statistical Association) Presidential Award (American Society of Agronomy) Teaching and advising: Leads courses on spatial statistics, time series analysis, and statistical consulting. Advises on methodological and collaborative projects at the intersection of statistics and environmental science. Labs/Teams: Active in interdisciplinary research teams focused on spatial demography, ecological modeling, and statistical ecology.

• Quantitative Spatial Modeling
• Population Abundance and Stock Assessment
• Disease Ecology
• +4 more

Brad Harris, Ph.D., is an Associate Professor of Marine and Environmental Sciences and Director of the Fisheries, Aquatic Science, & Technology (FAST) Laboratory at Alaska Pacific University. He holds adjunct appointments at the University of Massachusetts School of Marine Sciences and an honorary fellowship at Ulster University. Ph.D. in Fisheries Oceanography, University of Massachusetts School of Marine Science M.Sc. in Fisheries Oceanography, University of Massachusetts School of Marine Science B.Sc. in Fisheries and Wildlife Science, Texas A&M University Brad Harris's research spans multidisciplinary studies in marine ecosystems, focusing on spatial dynamics of aquatic species, population ecology, and the impacts of anthropogenic and natural disturbances on biodiversity. His work integrates physical oceanography, habitat mapping, and conservation engineering to address fisheries sustainability and ecosystem management. He also contributes to natural resource law and policy through empirical research and stakeholder engagement. His 15 most recent publications address topics such as spatial closures on Georges Bank, shell growth dynamics of Pacific razor clams, stable isotope trophic analysis, and innovative approaches to fisheries data integration. These works reflect his expertise in quantitative modeling, habitat conservation, and fisheries technology. Honorary Fellow, Ulster University Brad Harris collaborates extensively with commercial fisheries, government agencies, and international councils like ICES and FAO. He leads the FAST Lab, mentoring graduate students and conducting fieldwork across marine systems from the Gulf of Alaska to the Bering Sea. His teaching portfolio includes marine biology, fisheries ecology, and natural resource policy courses.

Riley CasperView profile

Assistant Professor

• Orthogonal Polynomials
• Integrable Systems
• Spectral Theory
• +4 more

W. Riley Casper is an Assistant Professor of Mathematics at California State University, Fullerton (CSUF). His research focuses on the interplay between noncommutative algebra, algebraic geometry, and integrable systems, with applications to special functions and computational fluid dynamics. He holds a PhD from the University of Washington and dual MS/BS degrees from North Dakota State University. Dr. Casper teaches a wide range of courses at CSUF, including Calculus, Differential Equations, Real/Complex Analysis, Abstract Algebra, and Topology. His work spans both pure and applied mathematics, with recent contributions to matrix-valued differential operators, bispectrality, and prolate spheroidal wave functions. He has collaborated with institutions like Louisiana State University and the University of California, Berkeley on projects blending algebraic methods with computational techniques. Selected publications include studies on fractional differential operators, prolate spheroidal systems, and ocean data assimilation. His research has appeared in journals like Communications in Mathematical Physics and the American Journal of Mathematics. Teaching innovations include advanced problem-solving methodologies and applications of algebraic geometry in undergraduate instruction. Professional service includes organizing conferences (GAP XVI, ICM Satellite) and delivering invited talks at institutions worldwide. His work bridges theoretical mathematics with computational challenges in fluid dynamics and quantum computing.

• Game Theory
• Cooperative Games
• Voting Systems
• +5 more

Francisco Carreras Escobar is a Professor in the Department of Applied Mathematics II at the School of Industrial and Aeronautical Engineering of Terrassa, Polytechnic University of Catalonia (UPC). With an extensive research career spanning over four decades from 1978 to present, he has established himself as a leading scholar in game theory and its applications. His work primarily focuses on cooperative games, coalition structures, voting systems, and power indices, with significant contributions to theoretical foundations and practical applications in political science and economics. His research interests encompass Game Theory, Cooperative Games, Voting Systems, Power Indices, Coalition Formation, Decision Theory, Political Game Theory, and Mathematical Economics. Carreras Escobar's work demonstrates how mathematical game theory can be applied to analyze political decision-making processes, parliamentary systems, and coalition formation in multi-agent environments. His research has evolved from foundational work on power indices in the 1980s to more complex analyses of coalition structures and stability in recent years. Analysis of his 15 most recent publications reveals a consistent focus on coalition structures within cooperative game theory, particularly examining the Shapley value and its variants in partitioned settings. His work bridges theoretical mathematical developments with practical applications in political decision systems, particularly European voting mechanisms. The research shows increasing sophistication in handling complex coalition formations and stability criteria, with recent work focusing on axiomatic characterizations and probabilistic approaches to value allocation. MEDALLA DE L'ETSEIT AL MERIT DOCENT CONCURS DE MATERIAL DOCENT ETSEIT 93 Carreras Escobar has maintained an exceptionally productive research career with 404 documented academic activities. His work demonstrates strong collaborative patterns, particularly with Antonio Magaña (68 collaborations), Josep Freixas (61 collaborations), and Mª Albina Puente (60 collaborations). His research has evolved from early work on parliamentary voting systems in the 1980s to sophisticated analyses of coalition structures and stability in contemporary game theory. The Department of Applied Mathematics II at UPC has served as his primary academic base throughout his career, where he has contributed significantly to both theoretical developments and practical applications of game theory.

• Calculus of Variations
• Partial Differential Equations
• Mathematical Analysis
• +3 more

Edoardo Mainini is an Associate Professor at the University of Genova, specializing in mathematical analysis and applied mathematics. His research focuses on calculus of variations, partial differential equations, elasticity theory, optimal transport, and nonlinear dynamics. He has contributed to studies on fractional equations, material science, and stochastic processes. His work often bridges pure and applied mathematics, addressing problems in mechanics, probability, and geometric analysis. Mainini has collaborated extensively with researchers such as M. Kružík, D. Percivale, and U. Stefanelli, producing influential papers in journals like Calc. Var. Partial Differential Equations and Arch. Ration. Mech. Anal. . His recent articles (2020–2025) address topics ranging from fractional linear equations to Bayesian nonparametric models. Education includes a PhD in Mathematical Analysis from the University of Genova (2010) and a thesis on Infinite-dimensional porous media equations and optimal transportation . He has organized international conferences and seminars on variational methods and geometric structures. His research emphasizes rigorous mathematical frameworks for physical phenomena, including the linearization of elasticity models and the study of ground states in diffusion-dominated systems. Mainini’s contributions to carbon nanotube geometries and optimal transport theory have been recognized through invited talks at major events, such as the International School of Mathematics “Guido Stampacchia” . His work often explores the interplay between discrete and continuous models, with applications to materials science and geometric optimization.

Troels PedersenView profile

Associate Professor

• Wireless Communication
• Radio Channel Modeling
• MIMO Systems
• +5 more

Troels Pedersen is an Associate Professor at the Department of Electronic Systems, Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on stochastic radio channel modeling, MIMO systems, radar signal processing, and positioning technologies. Key projects include WHERE2 and NEWCOM++, addressing wireless hybrid estimators and network excellence in communications. Expertise in reverberant channel modeling, propagation graphs, and Bayesian inference methods Developed models for in-room radio channels using point processes and Galton-Watson trees Contributions to MIMO radar tracking, clutter mitigation, and drone swarm micro-Doppler analysis Active in wireless positioning, cooperative networks, and IoT interference modeling with 99+ publications in journals/conferences. Supervised 1 PhD candidate and contributed to EU-funded research initiatives.

• Mathematical Biology
• Reaction-Diffusion Equations
• Ecological Modeling
• +3 more

Peter van Heijster is a Full Professor at Wageningen University's Mathematical and Statistical Methods group (Biometris). His research focuses on mathematical biology, reaction-diffusion equations, and nonlinear dynamics. He explores topics such as predator-prey systems, tumor invasion models, ecological stability, and pattern formation in biological systems. Key projects include analyzing cyanobacterial bloom control mechanisms, optimizing linear time-invariant systems, and understanding stochastic climate models. He supervises doctoral candidates in areas like AI-driven ecological resilience and soil microbial communities. With over 42 publications, his work spans theoretical and applied mathematics, contributing to both fundamental science and practical applications in agriculture and environmental systems. His research integrates mathematical modeling, stability analysis, and numerical simulations, addressing challenges in ecology, oncology, and systems biology. Collaborations span global institutions, emphasizing interdisciplinary approaches to complex biological and environmental problems.

Pierre HansenView profile

Professor

• Operational Research
• Optimization
• Graph Theory
• +3 more

Pierre Hansen is a Professor at HEC Montréal since 1990, renowned for his contributions to operational research and optimization. He held the Data Mining Chair and directed the GERAD research center from 1996 to 2001. His multidisciplinary work spans over 15 disciplines, focusing on algorithm design, graph theory, and cluster analysis. He is a Fellow of the Royal Society of Canada (1999) and recipient of the Grand Prize for Excellence in Research (2013). Research interests include variable neighborhood search algorithms, graph spectra, and mathematical programming applications. His articles often explore optimization methods such as column generation, integral simplex decomposition, and geometric optimization problems like circle packing. His work impacts fields like data mining, network analysis, and computational geometry, with contributions to AutoGraphiX —a system for generating conjectures in graph theory. Hansen’s research integrates theoretical advancements with practical applications in operations research and decision sciences.