جست‌وجوی استاد و پژوهشگر

Sou-Cheng Terrya Choiمشاهده پروفایل

دانشیار

• Applied Mathematics
• Computational Mathematics
• Numerical Analysis
• +۴ مورد دیگر

Sou-Cheng Terrya Choi is a Research Associate Professor at the Department of Applied Mathematics, College of Computing, Illinois Institute of Technology. Her work bridges computational mathematics, algorithms, and software development for scientific applications. Education: Ph.D., Stanford University M.S., National University of Singapore B.S. (Honors), National University of Singapore Her research focuses on applied and computational mathematics, numerical analysis, and algorithm design. She actively contributes to data sciences and computational social sciences, emphasizing reproducible and sustainable scientific software. Recent publications highlight her expertise in Krylov subspace methods (e.g., MINRES-QLP) for solving symmetric systems and least-squares problems, alongside initiatives in sustainable research software practices. These works intersect numerical analysis, linear algebra, and computational economics. Scientific Awards: SIAM Activity Group on Linear Algebra Prize Silicon Valley Engineering Council Scholarship C. Gary & Virginia Skartvedt School of Engineering Fellowship Choi leads projects like GAIL (Guaranteed Automatic Integration Library), MINRES-QLP Pack, and OSCEF (Open-Source CIM-EARTH Framework). She is affiliated with SIAM, American Statistical Association, and Hong Kong Mathematical Society.

Michael Stengerمشاهده پروفایل

پژوهشگر

• Synthetic Data Generation
• Time Series Analysis
• Data Science
• +۳ مورد دیگر

Michael Stenger is a Researcher at the Chair of Software Engineering (Informatik II) under the Department of Computer Science at the University of Würzburg. His current role since May 2023 involves research in synthetic data generation, time series analysis, and machine learning. He coordinates the lecture 'Softwaretechnik' and supervises bachelor/master theses and seminar topics in software engineering. Education: Master of Computer Science (2020-2023), University of Würzburg Bachelor of Computer Science (2017-2020), University of Würzburg Study Abroad: University of Saskatchewan, Canada (2021) Research Interests: Focuses on synthetic data generation, time series analysis, and machine learning applications. His work emphasizes evaluation methodologies for synthetic data quality and hybrid forecasting approaches. He also contributes to data science and deep learning techniques for real-world problem-solving. Publications & Conferences: Active contributor to venues like MASCOTS, ICPE, and VLDB. Recent work explores synthetic time series evaluation (STEB, 2025) and lightweight temporal feature encoding (TSRM, 2025). Trends show a strong emphasis on automated systems, benchmarking, and cross-domain applicability. Supervision & Grants: Supervises student projects in software engineering and data science. Engaged in interdisciplinary collaborations through his roles in multiple academic chairs. Labs/Teams: Part of the Software Engineering Group and Secure Software Systems Group at the University of Würzburg.

• Mathematics Education
• Curriculum and Instruction
• Educational Leadership
• +۳ مورد دیگر

Dr. Andrea Wood is an Assistant Professor of Education at the University of Science and Arts of Oklahoma (USAO), where she teaches math courses for elementary teachers, Literature for Young People, and other education-focused subjects. She is an alumnus of USAO and brings extensive experience from roles such as district math supervisor in Mid-Del Schools and Moore Public Schools, as well as a National Math Consultant for a publishing company. Her research and presentations center on mathematics education, teacher development, and equitable strategies in curriculum design. Education: Doctor of Education in Curriculum and Instruction, Liberty University (2024) Master of Education in Curriculum and Instruction (with an Emphasis in Math Education), Liberty University (2012) Bachelor of Science in Elementary Education, USAO (2004) Research Interests: Dr. Wood focuses on enhancing math education for elementary teachers, fostering student problem-solving skills, and promoting joy in learning. She advocates for equitable strategies in curriculum adoption, professional learning for educators, and leadership in educational settings. Her work emphasizes breaking down barriers to student success and creating inclusive learning environments. Key Achievements: Recipient of the USAO Gladys Anderson Emerson Faculty Research Stipend State Finalist for Oklahoma State Teacher of the Year Moore Public Schools District Teacher of the Year Professional Involvement: Dr. Wood serves as President and founder of the Oklahoma Association of Math Leaders. She is also a member of the National Council of Supervisors of Mathematics, National Council of Teachers of Mathematics, Oklahoma Council of Teachers of Mathematics, and Central Oklahoma Math Consortium, contributing to committees and leadership roles within these organizations.

Rabia Djellouliمشاهده پروفایل

استاد

• Mathematical and Numerical Aspects of Wave Propagation
• Inverse Problems
• Computational Mechanics
• +۵ مورد دیگر

Rabia Djellouli is a Professor in the Department of Mathematics at California State University Northridge (CSUN), where she has been since 2003. Previously, she held academic positions at institutions including the University of Colorado Boulder (1996–2003) and Tunisian universities such as Ecole Supérieure des Télécommunications de Tunisie (1995–1996). She earned her Ph.D. in Mathematics from the University of Paris-XI and École Polytechnique (France) in 1988, following degrees from the University of Paris-Sud and University of Algiers. Research Interests focus on wave propagation phenomena, inverse problems, computational mechanics, and biomedical engineering. Her work spans mathematical physics, numerical analysis, and bio-mathematics, with applications in optical fibers, fluid-structure interactions, and medical imaging. Her publications emphasize solutions to acoustic and elastoacoustic scattering problems, numerical methods for partial differential equations, and applications in biomedical engineering such as fibrous capsule growth modeling. She has secured grants from NSF and industry partners like Medtronic, supporting research in computational methods and medical device innovation. Service & Mentoring includes roles as Department Graduate Committee Chair, organizer of student research symposia, and mentor for over 20 undergraduate and graduate students. She has led NSF-funded programs like PUMP (Preparing Undergraduates through Mentoring toward Ph.D.s), fostering student research in mathematics. Affiliations include the College of Science and Mathematics at CSUN, and collaborations with institutions like INRIA (France) through international research initiatives.

• Real-time Systems
• Storage Systems
• Information Theory
• +۳ مورد دیگر

Carlos A. Rincon C. is an Instructional Associate Professor in the Computer Science Department at the University of Houston. Born in Venezuela, he brings extensive industry and international academic experience to his role, having previously served at Universidad del Zulia. His research integrates Information Theory with real-time systems scheduling to solve practical computing problems. Education includes: PhD in Computer Science, University of Houston (2014-2018) PhD in Informatics (Diploma of Advanced Studies), Universidad Politécnica de Madrid (2005-2008) Master in Telematics, Universidad Rafael Belloso Chacín (2001-2003) Bachelor in Computer Science, Universidad del Zulia (1994-2000) Research focuses on bridging theoretical computer science with real-world applications, particularly in: Real-time systems scheduling using entropy-based heuristics Storage system optimization through probabilistic compression Algorithmic efficiency in multiprocessor environments Publications demonstrate consistent focus on optimizing system performance through mathematical modeling, with recent work emphasizing entropy metrics in scheduling algorithms. Awards include: Best Paper Award nominee at IEEE International Symposium Outstanding Paper Award for multi-mode FRP task scheduling Advises graduate students on projects including disk failure prediction using ML and probabilistic compression optimization. Directs the ConocoPhillips Computer Science Learning Center, enhancing student resources for core CS courses.

Jennifer Kosiakمشاهده پروفایل

استاد

• Mathematics Education
• Curriculum Development
• Elementary Mathematics
• +۳ مورد دیگر

Jennifer Kosiak is a Professor in the Department of Mathematics & Statistics at the University of Wisconsin-La Crosse. She specializes in Mathematics Education with a focus on curriculum development for elementary grades. Her work emphasizes integrating real-world tasks into classroom instruction to enhance student engagement. She holds certifications in inclusive teaching and academic advising, as indicated by her AdvisorCertification badge. Her research and publications center on problem-solving methodologies for PK-12 education. She has co-authored two influential books published by the National Council of Teachers of Mathematics: Problem Solving for All Seasons: Grades 3-5 (2016) and Problem Solving for All Seasons: PK-2 (2015). These texts provide educators with practical strategies for fostering mathematical thinking in young learners. In 2023, she presented Where Do We Go From Here? at the OPID Spring Conference on Teaching, exploring innovative pedagogical approaches. Her professional engagement extends to international experiences, including an enlightening trip to Guatemala that explored cultural dimensions of mathematics education.

Bir B. Kafleمشاهده پروفایل

دانشیار

• Number Theory
• Algebraic Number Theory
• Diophantine Equations
• +۲ مورد دیگر

Dr. Bir B. Kafle is Associate Professor of Mathematics at Purdue University Northwest specializing in number theory and discrete mathematics. Research investigates: Properties of special sequences (Tribonacci, Fibonacci) Diophantine equations and arithmetical structures Algebraic foundations of number systems Publications resolve conjectures in combinatorial number theory and establish connections between classical sequences and Diophantine problems.

• Machine Learning
• Cloud Computing
• IT Service Management
• +۳ مورد دیگر

Genady Ya. Grabarnik is a Professor and Graduate Director in the Department of Mathematics and Computer Science at St. John's College of Liberal Arts and Sciences, St. John's University. He holds a Ph.D. from the National Academy of Science. His research focuses on interdisciplinary areas including machine learning, cloud computing, IT service management, and mathematics education. He has contributed to advancements in Kubernetes-based systems, digital twin frameworks, and educational methodologies for STEM prerequisites. His work bridges theoretical foundations with practical applications in cloud infrastructure and automated problem-solving. Education: Ph.D., National Academy of Science Research Interests: Machine Learning and its prerequisites in education Cloud computing, Kubernetes, and microservices IT service management and automation Data-driven methodologies for system optimization Key Contributions: Developed frameworks like Kubetwin for Kubernetes deployments Explored hybrid cloud optimizations via BDMaaS+ Advanced AI-driven ticket resolution systems (e.g., AISTAR ) Studied cross-country educational strategies for mathematics Advising & Grants: No explicit student advising records listed. His grants and collaborations are inferred from his research outputs but not detailed here. Labs/Teams: Not explicitly mentioned, though his work suggests involvement with cloud computing and IT service management research groups.

Alan Fedorukمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Multi-Agent Systems (MAS)
• Stakeholder Search
• +۳ مورد دیگر

Alan Fedoruk is an Associate Professor in the Department of Mathematics & Computing at Mount Royal University. He holds a PhD from the University of Calgary (2009), MSc from the University of Saskatchewan (2003), and BSc from the University of British Columbia (1985). Prior to academia, he worked in IT roles including programmer, system administrator, and application development manager. His research focuses on artificial intelligence and multi-agent systems (MAS), particularly stakeholder search frameworks for solving complex problems through cooperative/competitive agent interactions. He teaches courses in computer science/web development and contributes to general education through 'Controversies in Science.' Education: PhD (2009), MSc (2003), BSc (1985) Research interests include developing MAS architectures where agents collaborate/compete to achieve collective goals, inspired by natural systems like neural networks. Current work explores stakeholder search applications in land-use planning and conflict resolution. His publications span ethical computing, academic scholarship frameworks, and fault-tolerant agent systems. He advocates for sustainable urban mobility through his board role at Bike Calgary. Publications emphasize AI ethics, stakeholder-driven problem-solving, and MAS fault tolerance. Teaching focuses on bridging theory and practical skills in computing education. Professional service includes promoting cycling advocacy and community-based disaster research through Mount Royal's institutes.

• Inverse Problems
• Geometry
• Partial Differential Equations (PDEs)
• +۷ مورد دیگر

Sean Holman is a Senior Lecturer in Applied Mathematics at The University of Manchester, specializing in inverse problems, geometry, and partial differential equations. His research focuses on advancing theoretical frameworks and computational methods for imaging and material analysis, with applications in medical imaging, geophysics, and engineering. He is affiliated with the Industrial and Applied Mathematics and Inverse Problems research groups, contributing to the Digital Futures research beacon. His work integrates advanced mathematical techniques such as Radon transforms, tensor field analysis, and microlocal analysis to solve challenging inverse problems. Recent collaborations include studies on elastic strain reconstruction, electromagnetic parameter recovery, and agent swarm coordination under communication constraints. Dr. Holman has organized significant academic events like the 'Rich and Nonlinear Tomography' conference (2023) and the 'Microlocal Analysis meets Data Science' workshop (2018), fostering interdisciplinary research. His contributions span theoretical developments and practical applications in imaging modalities like SPECT and proton therapy range verification.

Thanasis Fokasمشاهده پروفایل

استاد

• Nonlinear Mathematical Science
• Boundary Value Problems
• Integrable Systems
• +۷ مورد دیگر

Thanasis Fokas is a Professor of Nonlinear Mathematical Science at the University of Cambridge's Faculty of Mathematics, holding the Chair in Nonlinear Mathematical Science since 2002. Previously, he held chairs at Imperial College London (1996) and Clarkson University (1986). His research focuses on integrable systems, boundary value problems for PDEs, inverse problems in medical imaging, and novel complex analysis techniques. He is affiliated with the Cantab Capital Institute for the Mathematics of Information and the Centre for Mathematical Imaging in Healthcare. Education: PhD in Applied Mathematics (Clarkson University) Doctorate in Physics (Caltech, assumed based on career timeline) Research Interests: Prof. Fokas develops analytical methods for solving linear and nonlinear PDEs, with applications to water waves, medical imaging (EEG/MEG/PET), and mathematical biology. His work bridges pure and applied mathematics, contributing to fields like quantum gravity and cognitive neuroscience through innovative inverse problem solutions and imaging algorithms. Key Contributions: Unified Transform Method (Fokas Method) for PDEs Mathematical models for SARS-CoV-2 transmission dynamics Neuronal current reconstruction via EEG/MEG Labs/Teams: He leads research groups in the Centre for Mathematical Imaging in Healthcare and collaborates with the DAMTP Applied Mathematics and Theoretical Physics division.

Mikael Pichotمشاهده پروفایل

دانشیار

• Geometric Group Theory
• Analysis
• Group Theory
• +۳ مورد دیگر

Mikael Pichot is an Associate Professor in the Department of Mathematics and Statistics at McGill University, located in Montreal, Quebec. His research focuses on Geometric Group Theory, Analysis, and related areas such as Operator Algebras and Metric Geometry. He is actively involved in organizing academic events and seminars, including the Group Theory Seminar and CRM-ISM Colloquium, and has contributed to numerous collaborations, often with co-authors like Sylvain Barre and Robert Graham. His teaching includes courses such as Math 223 (Linear Algebra) and Math 570/571 (Higher Algebra sequences). Pichot's research interests span topics like geometric group actions, sofic dimension, L2 invariants, and random groups. He has published extensively in peer-reviewed journals and presented at international conferences. His work often bridges algebraic, geometric, and analytic approaches to group theory. Despite his active academic contributions, no specific awards or grants are explicitly listed in the provided texts. He maintains a personal webpage and collaborates on projects such as 'Surgery on discrete groups' and 'Random groups and nonarchimedean lattices.' His research also touches on foundational questions in operator algebras and geometric topology, reflecting a deep engagement with the structural properties of groups and their applications.

• Economic Model Predictive Control
• Stability of Nonlinear Systems
• Chemical Reaction Networks Theory
• +۵ مورد دیگر

David Angeli is a Professor of Nonlinear Network Dynamics in the Department of Electrical and Electronic Engineering at Imperial College London's Faculty of Engineering. Affiliations: Control and Power Research Group Energy Futures Lab His research focuses on Economic Model Predictive Control, Stability of Nonlinear Systems, Chemical Reaction Networks Theory, Systems Biology, and Control of Smart Grids. He develops theoretical frameworks for networked systems with applications in energy infrastructure and biological processes, emphasizing robustness and scalability in distributed settings. Recent publications (2023-2025) highlight work on distributed control algorithms, Lyapunov-based stability certification, and small-gain theorems for interconnected systems. His research bridges control theory, game theory, and machine learning to solve problems in cyber-physical systems, particularly in resilient consensus protocols and economic optimization for heterogeneous networks. As a core member of the Control and Power Research Group and Energy Futures Lab, he contributes to sustainable energy solutions and advanced control methodologies for complex networked systems.

Audrey Repettiمشاهده پروفایل

دانشیار

• Optimization
• Fixed Point Algorithms
• Deep Learning
• +۴ مورد دیگر

Audrey Repetti is an Associate Professor at Heriot-Watt University, affiliated with both the School of Mathematical and Computer Sciences and the School of Engineering and Physical Sciences. She holds a PhD in optimization from Université Paris-Est Marne-la-Vallée (2015) and an MSc in applied mathematics from Université Pierre et Marie Curie (2011). Her research focuses on optimization (convex/nonconvex/stochastic), deep learning, Bayesian inference, and inverse problems in imaging and graph processing. She received the Royal Society of Edinburgh Fellowship (2022) for her work in optimization for data science. Her teaching includes courses like Bayesian Inference and Computational Methods. She collaborates internationally on projects in radio astronomy imaging, medical imaging, and computational optics. Repetti’s work bridges optimization theory with practical applications, emphasizing scalable algorithms for large-scale data problems.

• Optimal Transportation
• Mathematical Economics
• Mathematical Physics
• +۳ مورد دیگر

Brendan Pass is a Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta. His research focuses on optimal transportation theory, with applications in mathematical economics, mathematical physics, and density functional theory. He is a core member of the Kantorovich Initiative, an interdisciplinary group dedicated to advancing optimal transport methodologies and their practical implementations. His work bridges pure mathematics with applied fields, addressing complex problems in multi-marginal transport, economic equilibrium modeling, and geometric analysis. Pass’s academic contributions span theoretical frameworks for optimal transport between spaces of differing dimensions, cyclic cost structures, and robust risk management. He explores intersections with diverse disciplines, including econometrics, financial mathematics, and geometric probability. His publications often address uniqueness conditions for Monge solutions, Wasserstein metrics, and barycenter problems in metric spaces. He has co-authored works on topics ranging from hedonic pricing models to vectorial martingale transport. Recent research trends include leveraging optimal transport for inequality measurement, robust optimization, and data denoising. His methodologies emphasize structural analysis and algorithmic design, with applications in crop root systems, quantum chemistry (via density functional theory), and option pricing. Pass frequently collaborates with institutions globally, contributing to both theoretical advancements and real-world problem-solving. Teaching responsibilities include advanced mathematics courses such as Math 156 (Calculus for Business/Economics) and Math 300 (Boundary Value Problems). His scholarly output includes over 50 peer-reviewed articles, conference contributions, and edited volumes. Current projects explore ODE characterizations of transport problems, distributional robustness, and partial identification in econometric models.