جست‌وجوی استاد و پژوهشگر

Rifat Sipahiمشاهده پروفایل

استاد

• Control Systems
• Mechatronics
• Stability Analysis of Dynamical Systems
• +۵ مورد دیگر

Rifat Sipahi is a Professor and Associate Chair for Research Affairs in the Department of Mechanical and Industrial Engineering at Northeastern University. He holds a BS from Istanbul Technical University (2000), and MS/PhD from the University of Connecticut (2002/2005). After a postdoc at Université de Technologie de Compiègne (France), he joined Northeastern in 2006. His research focuses on control systems, time delay dynamics, and mechatronics, with applications to robotics, human-machine systems, and biomedical devices. Education: PhD, 2005: Mechanical Engineering, University of Connecticut MS, 2002: Mechanical Engineering, University of Connecticut BS, 2000: Mechanical Engineering, Istanbul Technical University Research Interests: Stability analysis of time delay systems, network dynamics, human-robot collaboration, and engineering education innovation. His lab has developed novel methods for stability charts and delay-tolerant graph design. Recent Work: Includes studies on firearm acquisition patterns, spinal cord growth modeling, and low-cost Braille devices for the blind. He has authored 79 journal articles and 98 conference papers, with an h-index of 37 (Google Scholar). Awards: 2015 ASME Young Investigator Award, 2011 DARPA Young Faculty Award, 2022 Outstanding Faculty Service Award, and ASME Fellow since 2014. Grants: Funded by NSF, DARPA, DEVCOM, and NIH. Projects include cognitive distributed sensing, graph-based control design, and systems biology collaborations.

• Applied Mathematics
• Statistics
• Strategy
• +۷ مورد دیگر

Prof. Hanqin Zhang is a Professor in the Department of Analytics And Operations at the National University of Singapore (NUS Business School). He holds a Doctor of Science from the Chinese Academy of Sciences (1991) and a Master of Science from Xian Jiaotong University (1985). His research focuses on applied mathematics, statistics, strategy, transportation logistics, control engineering, and numerical methods. He has served as an associate editor for journals like European Journal of Operational Research and TOP , and has reviewed for top-tier journals including Operations Research and Queueing Systems . His recent work addresses optimal inventory policies, queueing systems, and stochastic control, with notable contributions to dual-sourcing strategies, staffing optimization in ticket queues, and fluid models of parallel service systems. He has supervised students in stochastic processes and inventory management, reflecting his expertise in bridging theoretical advancements with practical applications in operations research. Notable research trends include leveraging order-tracking information for inventory systems, analyzing ergodicity in Markov chains, and optimizing multi-source supply chains under uncertainty. His publications span high-impact journals such as Operations Research and Queueing Systems , showcasing a focus on stochastic systems and operations management.

Jay Gopalakrishnanمشاهده پروفایل

استاد

• Scientific computation
• Numerical analysis
• Finite elements
• +۳ مورد دیگر

Jay Gopalakrishnan is a Professor of Mathematics and the Maseeh Distinguished Chair at Portland State University's Department of Mathematics. His research focuses on scientific computation, numerical analysis, finite elements, and multigrid methods with applications in optics and mechanics. He has contributed significantly to the development of hybridizable discontinuous Galerkin (HDG) methods and the Discontinuous Petrov-Galerkin (DPG) framework, emphasizing structure-preserving numerical techniques. His work spans diverse domains including microstructured optical fibers, spacetime tents for hyperbolic systems, and eigenvalue cluster computations. Notable research activities include developing accurate computational tools for leaky modes in fibers, stability analysis of acoustic waveguides, and bone mineralization models. He advises doctoral students at institutions such as Intel Corporation, The MathWorks, and James Madison University. His teaching includes advanced numerical analysis courses and undergraduate mathematical computing. Collaborations with researchers like L. Demkowicz and J. Schöberl highlight his interdisciplinary impact in computational mathematics and engineering.

• Numerical linear algebra
• Matrix polynomials and spectral theory
• Stability and perturbation analysis
• +۳ مورد دیگر

Aleksandr Malyshev is Professor of Mathematics at the University of Bergen. His research integrates numerical linear algebra, stability theory, optimisation-based control, and image-processing algorithms, yielding a portfolio of more than 60 peer-reviewed articles and conference contributions. Education & affiliations: Professor, Department of Mathematics, University of Bergen, Norway (present) Previous research and teaching engagements in informatics and applied mathematics at the same university Research interests: Malyshev’s core interest is the theoretical and algorithmic analysis of matrix problems arising in stability, control and imaging. He develops numerically reliable tools for assessing the distance to instability of dynamical systems, constructs preconditioners that accelerate optimisation solvers in real-time model predictive control, and designs variational models for 3-D reconstruction and image denoising. His work frequently combines spectral theory of matrix polynomials with practical issues such as high-performance implementation and medical-image quantification. Across the last decade his articles reveal three dominant strands: (i) stability and perturbation of time-delay and periodic systems, (ii) preconditioned iterative solvers for interior-point and MPC formulations, and (iii) variational and learning-based approaches to depth estimation, surface reconstruction and glenoid-bone assessment. These themes are unified by a common mathematical substrate—exploitation of matrix structure to obtain computationally efficient, numerically trustworthy solutions. Scientific awards & recognition: Regular invited speaker at international workshops on numerical linear algebra and control (e.g., SK Godunov conference 2009, IFAC 2018) Funded principal investigator / co-investigator on Research Council of Norway and EU Horizon Europe grants Advising & grants: Malyshev has supervised numerous MSc and PhD candidates in numerical analysis and scientific computing and currently advises graduate researchers on projects ranging from 3-D machine-vision algorithms to Krylov-subspace preconditioning. Recent grant participation includes EU project 101373 (3-D quantification of glenoid bone loss) and the Norwegian Research Council project 262203 on perfusion-flow simulation. Labs & collaboration: He collaborates closely with the Group for Numerical Methods and Applications at UiB, the Visual Computing cluster at the Department of Informatics, and maintains international partnerships with the Universities of Brest, Lübeck, and several US institutions. These joint efforts feed cross-disciplinary projects combining rigorous matrix analysis with real-world applications in biomechanics, process control, and computer vision.

Lex Schrijverمشاهده پروفایل

استاد

• Discrete Mathematics
• Optimization
• Algorithms
• +۳ مورد دیگر

Lex Schrijver is a Professor of Mathematics at the University of Amsterdam since 1990 and a CWI-Fellow at Centrum voor Wiskunde en Informatica (CWI) since 1989. His research focuses on discrete mathematics, optimization, and algorithms, with significant contributions to graph theory, combinatorics, and coding theory. Research Interests: Discrete Mathematics, Optimization, Algorithms, Graph Theory, Combinatorics, Coding Theory. Awards: EURO Gold Medal (2015) Honorary Doctorate from Eotvos Lorand University (2011) Franz Edelman Award (2008) SIGMA Prize (2008) John von Neumann Theory Prize (2006) Spinoza Prijs (2005) Ridder in de orde van de Nederlandse Leeuw (2005) Lanchester Prize (2004, 1986) Fulkerson Prize (2003, 1982) Van Dantzig Prize - SIAM / MPS (2003) Eredoctoraat from University of Waterloo (2002) Projects: Involved in the Networks project, funded by the Netherlands Organisation for Scientific Research (NWO). Professional Activities: Fellow of the American Mathematical Society (AMS) and SIAM.

Peter Ganglمشاهده پروفایل

استاد پژوهشی

• Topology Optimization
• Shape Optimization
• Computational Mathematics
• +۳ مورد دیگر

Dr. Peter Gangl is a Senior Research Scientist at the Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, where he leads research in optimization and computational mathematics. He holds a Ph.D. (2017) and M.Sc. (2012) from Johannes Kepler University Linz. His research focuses on topology/shape optimization, topological derivatives, and multiphysics simulation of electric machines. Research Interests: Gangl specializes in developing mathematical methods for PDE-constrained optimization, with emphasis on computational electromagnetics, automated sensitivity analysis, and multi-objective design. His work bridges applied mathematics and industrial applications, particularly in electric motor optimization. Research Projects: Principal Investigator for SFB F90 'CREATOR' (2022–2026) on topology optimization under electro-thermal coupling Led FWF project 'Multiphysical Shape Optimization of Electrical Machines' (2020–2024) Awards & Honors: Richard C. DiPrima Prize (SIAM, 2018) Erwin Wenzl Preis (2018) Anile Prize (ECMI, 2018) Promotio sub auspiciis (Austria's highest academic honor, 2017) Students & Collaboration: Supervises PhD candidates (Nepomuk Krenn, Michael Winkler) and collaborates with institutions including TU Graz, TU Darmstadt, and international partners. Organizes workshops/seminars on optimization and computational mathematics.

Aaron Melmanمشاهده پروفایل

دانشیار

• Applied Mathematics
• Linear Algebra
• Numerical Analysis
• +۳ مورد دیگر

Aaron Melman is an Associate Professor and Chair of the Department of Applied Mathematics at the School of Engineering, Santa Clara University. He holds a Ph.D. in Applied Mathematics from the California Institute of Technology (Caltech) and an M.Sc. from the Technion (Israel Institute of Technology). His research focuses on applied mathematics, with primary interests in linear algebra, numerical analysis, matrix theory, polynomial equations, and computational algorithms for root-finding and eigenvalue estimation. His work frequently explores theoretical bounds and efficient numerical techniques for solving complex mathematical problems. Melman's extensive publication record includes over 70 articles, with recent works concentrated on matrix polynomials, eigenvalue localization, and polynomial zero exclusion theorems. His research demonstrates a consistent emphasis on refining classical mathematical theorems and developing practical computational frameworks.

• Numerical Methods
• Electromagnetic Theory
• Antenna Design
• +۲ مورد دیگر

Kurt Schab is an Assistant Professor of Electrical Engineering at the School of Engineering, Santa Clara University (SCU), joining the faculty in September 2018. His academic journey includes a dual B.S. in Electrical Engineering and Physics from Portland State University (2011), followed by M.S. and Ph.D. degrees in Electrical Engineering from the University of Illinois at Urbana-Champaign (2013, 2016). From 2016 to 2018, he served as an Intelligence Community Postdoctoral Research Scholar at North Carolina State University. Research Focus: Dr. Schab's work sits at the intersection of numerical methods, electromagnetic theory, and advanced antenna design. He explores fundamental trade-offs in antenna performance, symmetry in computational electromagnetics, and theoretical bounds for electromagnetic systems. Scientific Achievements: Raj Mittra Outstanding Research Award (UIUC, 2016) Publication Trends: His recent work analyzes direct antenna modulation techniques, quality factor optimization, and energy dynamics in radiating systems, reflecting collaborative efforts with researchers at institutions like NCSU and KTH Royal Institute of Technology. Labs & Collaborations: While specific lab affiliations aren't detailed here, his postdoctoral work at North Carolina State University and collaborations with international researchers (e.g., M. Gustafsson at KTH) indicate strong academic partnerships in electromagnetic research.

Yue Zhangمشاهده پروفایل

دانشیار

• Scientific Visualization
• Computer Graphics
• Mathematical Modeling
• +۴ مورد دیگر

Dr. Yue Zhang is an Associate Professor in the School of Electrical Engineering and Computer Science at Oregon State University. She holds appointments in both academic research and teaching roles, with a focus on computer graphics and data visualization. Her work bridges theoretical mathematics and practical applications in material science and ecological modeling. Ph.D. in Applied Mathematics, North Carolina State University B.S. in Mathematics and Physics, University of Tennessee at Knoxville Research interests span scientific visualization , tensor field analysis , and topology-driven modeling of physical and biological systems. She has pioneered techniques for hypergraph simplification, non-Euclidean geometry visualization, and coupled acoustic-structural simulations. Recent publications demonstrate trends in hypergraph visualization (2024), 3D tensor topology (2024-2022), and environmental stressor modeling (2022). Collaborative works with Eugene Zhang and Peter Oliver dominate her publication record. Students under her advisement include: PhD candidates: Shih-Hsuan Kevin Hung MS/MEng students: Kyle Hiebel, Josiah Blaisdell, Avery Stauber Co-advised projects: Peter Oliver, Xiaofei Gao

Karen Gundersonمشاهده پروفایل

دانشیار

• Graph theory
• Combinatorics
• Random graphs
• +۱۰ مورد دیگر

Karen Gunderson is an Associate Professor in the Department of Mathematics at the University of Manitoba's Faculty of Science. Her research spans graph theory, combinatorics, random graphs, percolation, hypergraphs, and extremal combinatorics. Research Focus : Graph theory, combinatorics, random graphs, percolation, hypergraphs, extremal combinatorics Academic Role : Associate Professor, Acting Associate Head Graduate Contact : Karen.Gunderson@umanitoba.ca , karen.gunderson@umanitoba.ca Her work includes bootstrap percolation , random geometric graphs , and extremal hypergraph problems , with applications in network modeling and probabilistic combinatorics. Recent publications focus on adversarial burning densities, Erdos-Ko-Rado robustness, and Turán numbers in switching contexts. Academic Leadership : Co-organizer of the University of Manitoba Combinatorics Seminar and key organizer for the 2023 CanaDAM conference and Movement & Symmetry in Graphs retreat.

Peter Nejjarمشاهده پروفایل

استادیار

• Probability Theory
• Stochastic Processes
• Mathematical Physics
• +۳ مورد دیگر

Peter Nejjar is a Tenure-Track Juniorprofessor for Probability Theory at the University of Potsdam since January 2023. His research addresses fundamental questions of universality in stochastic systems , investigating why identical probability distributions emerge across disparate contexts like random matrices and growth models, with connections to combinatorics, mathematical physics, and numerical analysis. His primary research domains include stochastic particle systems (TASEP/ASEP), KPZ universality class phenomena, and Markov chain mixing behavior —particularly the cutoff phenomenon. Nejjar's work reveals deep structural parallels between shock fluctuations in interacting particle systems and random matrix eigenvalue distributions, leveraging connections to algebraic combinatorics through Schur processes. Recent publications demonstrate evolving focus from shock fluctuation theory (2015-2018) toward dynamical phase transitions in KPZ systems (2020-2022) and emerging interdisciplinary applications like DNA-based molecular tagging (2025). His collaborative network prominently features Patrik Ferrari across 7 publications, reflecting sustained focus on universality in exclusion processes.

Magdalena Nockowska-Rosiakمشاهده پروفایل

استادیار

• Difference equations
• Mathematical modeling
• Integral operators
• +۵ مورد دیگر

Dr. Magdalena Nockowska-Rosiak is a research and teaching assistant professor in the Department of Mathematical Modeling at Lodz University of Technology. With over 15 years of academic career, she has established herself as a prominent researcher in difference equations, integral operators, and mathematical modeling with economic applications. Her work appears in high-impact journals including Journal of Applied Analysis & Computation, Qualitative Theory of Dynamical Systems, and Applied Mathematics and Computation. Her research primarily focuses on: Theoretical analysis of difference equations (neutral, Volterra, Sturm-Liouville types) Discretization methods for integral operators (Fredholm, Hammerstein, Urysohn) Boundary value problems on discrete domains Mathematical modeling of economic phenomena, particularly demand-inventory systems Variational inequalities related to economic equilibrium Dr. Nockowska-Rosiak's publication trajectory shows progression from foundational work on difference equations toward specialized research on discretization methods while maintaining strong connections to economic applications. Her most recent publications (2023-2025) demonstrate continued innovation in numerical methods for integral operators. She has established productive collaborations with researchers including Christian Pötzsche, Janusz Migda, and Ewa Schmeidel. She has supervised PhD student Piotr Hachuła (2018 dissertation on nonlinear systems for microeconomic modeling) and co-authored the book "An analysis of dynamics of demand-inventory model with stock-level-dependent demand" (Lodz University of Technology Publishing House, 2018). Her research has practical applications in understanding stability of equilibrium points and bifurcation phenomena in demand-inventory systems with stock-level-dependent demand.

• Computer Science
• Artificial Intelligence
• Smart Cities
• +۵ مورد دیگر

Sebastian Ernst is a Lecturer at the Department of Applied Informatics, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology in Kraków. His research focuses on Computer Science , Artificial Intelligence , and Smart Cities , with a strong emphasis on Geographic Information Systems (GIS) and Energy Efficiency in urban environments. University: AGH University of Science and Technology Faculty: Electrical Engineering, Automatics, Computer Science and Biomedical Engineering Department: Applied Informatics Position: Lecturer Contact: ernst@agh.edu.pl Office: C-2, 4th floor, room 424 Phone: +48 12 617 51 95 His recent publications highlight trends in Graph-Based Modeling , Smart Lighting Systems , and Robust Algorithm Design for urban infrastructure. He explores Pairwise Comparisons , GIS Applications , and Energy Conservation through computational methods.

• Decision Support Systems
• Operations Research
• Machine Learning
• +۳ مورد دیگر

Konrad Kułakowski is a Professor at the Department of Applied Informatics within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków. His research spans multiple domains including decision support systems, operations research, and robotics, with a focus on pairwise comparisons methods and their applications in optimization problems and automated systems. Affiliation: AGH University of Science and Technology School: Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering Department: Applied Informatics His research interests center on improving accuracy and resilience in pairwise comparisons methods, detecting manipulation in decision-making processes, and optimizing path planning for automated guided vehicles (AGVs) in constrained environments. His work bridges theoretical advancements in decision analysis with practical applications in robotics, real-time systems, and biomedical engineering. Key trends in his recent publications include: Advancements in heuristic algorithms for pairwise comparisons matrices Applications of Monte Carlo simulations for method validation Path planning optimization for AGVs in irregular layouts Detection of manipulation in peer assessment frameworks Resilient aggregation techniques for secure judgments in AHP

• Elementary Particle Physics
• High Energy Physics
• Quantum Mechanics
• +۳ مورد دیگر

Rafael I Nepomechie is a Professor in the Department of Physics at the University of Miami's College of Arts and Sciences. His research focuses on fundamental aspects of quantum theory, including integrable systems and quantum information processing. Nepomechie investigates quantum entanglement, state preparation, and computational methods across diverse physical systems. Key research areas include: Quantum state engineering (Dicke/Bethe states) Entropy dynamics in inhomogeneous systems Quantum algorithm design for spin chains Applications of matrix product states His recent publications (2024-2025) demonstrate consistent focus on quantum state preparation techniques, entanglement quantification, and variational methods for solving integrable models. Work frequently bridges theoretical physics with quantum computing implementations. No awards, students, or grants are explicitly mentioned in available sources.