جست‌وجوی استاد و پژوهشگر

Partha Deyمشاهده پروفایل

دانشیار

• Probability Theory
• Statistical Physics
• First and Last Passage Percolation
• +۶ مورد دیگر

Partha Dey is an Associate Professor in the Department of Mathematics at the University of Illinois at Urbana-Champaign (UIUC), where he also serves as Director of the NetMath Program. He holds affiliations in both Mathematics and Statistics departments. His research focuses on Probability Theory and its intersections with Statistical Physics, emphasizing First/Last Passage Percolation, Random Growth Models, Stein’s Method, Spin Glasses, and Random Matrix Theory. Education: Ph.D. in Statistics from UC Berkeley (2010), supervised by Sourav Chatterjee and Steve Evans. Prior to UIUC, he was a Courant Instructor/Simons Fellow at NYU (2010-2013) and a Harrison Early-Career Assistant Professor at the University of Warwick (2013-2014). Undergraduate and Master’s studies at Indian Statistical Institute Kolkata (Mathematical Statistics & Probability). Research interests include analyzing stochastic processes in complex systems, with recent work on fluctuation phenomena in percolation models, spin glasses under external fields, and Stein’s method applications. His publications span high-impact journals like ALEA , Annals of Probability , and Communications in Mathematical Physics . Awards/Funding: No explicitly listed honors, though his positions suggest sustained academic recognition. Grants/Advising: No detailed grant info provided; no advisee names listed in texts. Labs/Teams: Leads NetMath Program, a distance-learning initiative in mathematics education. Collaborates widely on interdisciplinary projects in probability and statistical physics.

Athanasios Antoulasمشاهده پروفایل

استاد

• Dynamical Systems
• Model Reduction
• Control Systems
• +۳ مورد دیگر

Athanasios Antoulas is a Professor of Electrical and Computer Engineering at Rice University, where he has served since 1982. He is also a Max Planck Fellow (since 2016) and has held visiting positions at institutions such as the Australian National University and Kyoto University. His research focuses on dynamical systems, model reduction, and data-driven methods, particularly through the Loewner framework. Education: Ph.D. in Mathematics (1980), and Diplomas in Mathematics and Electrical Engineering (both 1975) from ETH Zurich. He was the sole Ph.D. student of renowned control theorist R.E. Kalman in Switzerland. Research interests include large-scale system approximation, nonlinear dynamics, and applications in energy systems and control. His work emphasizes data-driven techniques for modeling and reducing complex systems, with contributions to the Loewner framework for parametric and nonlinear systems. Notable awards include IEEE Fellow (1991), AIAA Best Paper Prize (1992), and JSPS Fellowship (1995). He has served as Editor-in-Chief of Systems and Control Letters and on editorial boards of major journals like IEEE Transactions on Automatic Control. His publications span model reduction, nonlinear system identification, and applications in electrochemical systems. He has advised numerous researchers but no explicit student names are listed in the provided data. Labs/Teams: Collaborations include the Max Planck Institute through his fellowship, and leadership in the Loewner framework development for systems engineering.

Alex Eskinمشاهده پروفایل

استاد

• Dynamical Systems
• Teichmüller Theory
• Ergodic Theory
• +۵ مورد دیگر

Alex Eskin is the Arthur Holly Compton Distinguished Service Professor of Mathematics at the University of Chicago's Department of Mathematics, within the Physical Sciences Division. His research focuses on dynamical systems, geometric group theory, ergodic theory, and their applications to number theory. Eskin holds a B.S. from UCLA and a Ph.D. from Princeton University (1993), advised by Peter Sarnak. Key research interests include Teichmüller dynamics, billiards on rational polygons, and the geometry of moduli spaces. He has made seminal contributions to understanding SL(2,R) actions on moduli spaces, Lyapunov exponents, and the classification of invariant measures. His work bridges dynamics, geometry, and number theory, with profound implications for the study of flat surfaces and homogeneous flows. Eskin has received numerous accolades, including the Breakthrough Prize in Mathematics (2019), Clay Research Award (2007), and membership in the National Academy of Sciences (2015). He has authored over 60 papers, advancing topics like counting closed geodesics in moduli spaces, volumes of strata of abelian differentials, and the rigidity of quasi-isometries in solvable groups. Notable achievements include proving the 'Magic Wand Theorem' with Mirzakhani and Mohammadi, resolving the classification of orbit closures for SL(2,R) actions, and advancing the understanding of Lyapunov exponents via algebraic geometry. His teaching includes courses like Math 203 (Analysis) at the University of Chicago.

Kaiqing Zhangمشاهده پروفایل

استادیار

• Control Theory
• Game Theory
• Robotics
• +۳ مورد دیگر

Kaiqing Zhang is an Assistant Professor at the University of Maryland, College Park, affiliated with the Department of Electrical and Computer Engineering (ECE), Institute for Systems Research (ISR), and multiple interdisciplinary centers including the Maryland Robotics Center (MRC). He holds a Ph.D. from the University of Illinois at Urbana-Champaign (UIUC), with postdoctoral experience at MIT and the Simons Institute for the Theory of Computing. His research focuses on the intersection of control theory, game theory, and reinforcement learning, addressing challenges in multi-agent systems, robotics, and safety-critical autonomy. He has received prestigious awards such as the NSF CAREER Award and AFOSR YIP, and his work emphasizes theoretical foundations for decision-making under uncertainty. Recent achievements include tutorials at ACM SIGMETRICS and ECC 2024, and publications on multi-agent RL, safe control, and LLM applications. He advises PhD students and is actively involved in conference organization and review roles.

Vinesha Peirisمشاهده پروفایل

پژوهشگر ارشد

• Optimization
• Approximation Theory
• Operations Research
• +۳ مورد دیگر

Dr. Vinesha Peiris is a Research Fellow at Curtin University's School of Electrical Engineering, Computer and Mathematical Sciences (EECMS), within the Faculty of Science and Engineering. Her work focuses on optimization, approximation theory, and operations research with applications in neural networks and computational mathematics. She holds a PhD in Applied Mathematics from Swinburne University of Technology (2022), a BSc (Hons) in Mathematics from the University of Sri Jayewardenepura (2017), and a Graduate Certificate in Research and Innovation Management (Swinburne, 2022). Dr. Peiris' research emphasizes rational approximation methods, nonsmooth optimization, and their applications in deep learning. She has received notable awards, including the Maryam Mirzakhani Award (2022), Kovalevskaya Grant (2022), and BH Neumann Prize (2020). Her publications span interdisciplinary topics like neural network architectures, insecticide resistance modeling, and matrix function approximations. Professional memberships include the Australian Mathematical Society (AustMS), Mathematics of Computation and Optimisation (MOCAO), Australia and New Zealand Industrial and Applied Mathematics (ANZIAM), and the Women in Mathematics Special Interest Group (WIMSIG).

Gord Sinnamonمشاهده پروفایل

استاد

• Hardy Inequalities
• Fourier Inequalities
• Function Spaces
• +۳ مورد دیگر

Gord Sinnamon is a Professor in the Department of Mathematics at the University of Western Ontario. His research focuses on Hardy inequalities, Fourier inequalities, function spaces, and positive operators. He has contributed extensively to mathematical analysis, particularly in operator theory and functional inequalities. His work includes foundational studies on weighted norm inequalities, interpolation spaces, and the Fourier transform in weighted Lorentz spaces. He has authored over 60 peer-reviewed articles and has collaborated with leading mathematicians globally. Sinnamon teaches advanced courses such as Calculus 1500A and Mathematics 4154A, emphasizing rigorous proof-based instruction. His research trends highlight advancements in operator theory, with a focus on norm estimates, maximal operators, and core decreasing functions. While no specific awards are mentioned, his sustained contributions to mathematical analysis are evident through his prolific publication record.

James E. Fowlerمشاهده پروفایل

استاد

• Hyperspectral Imagery Analysis
• Image and Video Coding
• Compressed Sensing
• +۳ مورد دیگر

James E. Fowler is the William L. Giles Distinguished Professor and holder of the Billie J. Ball Endowed Professorship in the Department of Electrical & Computer Engineering at Mississippi State University. As of January 2022, he serves as a Program Director in the Communications and Information Foundations (CIF) cluster at the National Science Foundation (NSF). His primary affiliations include Mississippi State University and NSF, with visiting roles at Télécom ParisTech and Polytech Nantes. He earned his B.S., M.S., and Ph.D. in Electrical Engineering from The Ohio State University. Dr. Fowler's research focuses on hyperspectral imagery analysis, compressed sensing, and image/video coding. His work integrates signal processing, machine learning, and computational imaging. Notable contributions include innovations in hyperspectral compression, random projections, and deep learning frameworks for remote sensing applications. Education: Ph.D., Electrical Engineering, The Ohio State University, 1996 M.S., Electrical Engineering, The Ohio State University, 1992 B.S., Computer and Information Science Engineering, The Ohio State University, 1990 Awards & Roles: Fellow of the IEEE Editor-in-Chief of IEEE Signal Processing Letters (2017–2019) General Co-Chair of the Data Compression Conference and IEEE International Conference on Image Processing Research Labs: High Performance Computing Collaboratory (HPC2) at Mississippi State University.

Zhimin Zhangمشاهده پروفایل

استاد

• Numerical analysis
• Computational mathematics
• Scientific computing
• +۸ مورد دیگر

Zhimin Zhang is a Professor in the Department of Mathematics at Wayne State University's College of Liberal Arts and Sciences, where he has worked since 2002. Previously, he served at Texas Tech University from 1991 to 2000, including as associate professor (1997-2000). He earned a B.S. (1982) and M.S. (1985) in Computational Mathematics from the University of Science and Technology of China, followed by a Ph.D. (1991) in Applied Mathematics from the University of Maryland at College Park. Research Focus : Numerical analysis, computational mathematics, and scientific computing with specialization in finite element methods, finite volume methods, and spectral methods for partial differential equations. Teaching : Regularly teaches Calculus III (MAT2030) and Numerical Methods I (MAT5100). His research trends include: Development of superconvergence techniques for discontinuous Galerkin and immersed finite element methods Advancements in fractional calculus numerical schemes for nonlocal and nonsmooth solutions Innovations in curl-conforming elements for electromagnetic problems Studies on Hamiltonian systems with structure-preserving spectral methods Error analysis for high-order finite element methods in anisotropic and Shishkin meshes Efficient solvers for bihamonic and eigenvalue problems Dr. Zhang serves on multiple editorial boards including: Mathematics of Computation (2009-2017) Journal of Computational Mathematics (since 2007) SIAM Journal on Numerical Analysis (since 2013) Communications on Applied Mathematics and Computation (since 2018) Scientific recognition includes: 2011 Outstanding Graduate Mentor Award 2014 Charles H. Gershenson Distinguished Faculty Fellows Award Continuous NSF funding since 2003 for projects such as "Recovery Type A Posteriori Error Estimates" (DMS-0311807) and "Spectral and Spectral Collocation Methods for Hamiltonian Systems" (DMS-1115530) He maintains active contributions to mathematical culture through editorial roles at journals like Mathematical Culture and Journal of Mathematical Study since 2008 and 2013 respectively.

Emil Daniel Schwabمشاهده پروفایل

استاد

• Algebra
• Number Theory
• Combinatorics
• +۸ مورد دیگر

Emil Daniel Schwab is a Professor of Mathematics in the Department of Mathematical Sciences at the University of Texas at El Paso (UTEP), College of Science. He previously served as Associate Dean for Research (2014-2015) and held administrative roles at University of Oradea, Romania (1996-1998). Education: Ph.D. in Mathematics, "Babes-Bolyai" University of Cluj-Napoca, Romania (1995). Thesis: "Contribution to the Study of Multiplicativity and Additivity in Incidence Algebras". Licentiate in Mathematics, West University of Timisoara, Romania (1987). Thesis: "Inverses in Special Categories". Dr. Schwab's research bridges algebra, number theory, and combinatorics through categorical techniques, focusing on Möbius inversion, inverse semigroups, arithmetical functions, and quantum logic. His work demonstrates deep connections between abstract algebraic structures and combinatorial frameworks, with significant contributions to incidence algebras and categorical logic. His 15 most recent publications (2011-2016) reveal consistent exploration of semigroup theory, Möbius categories, and Dirichlet convolution variants, showing increasing integration of categorical methods with number-theoretic applications. Grants: Cross Institutional Implementation of Supplemental Instruction- UTEP-EPCC Cooperative Project, U.S. Dept. of Education (2008-2011) Modular Development and Supplemental Instruction (SI) for the Calculus Course taken by all STEM Majors, U.S. Dept. of Education (2005-2008)

Jan Vrbikمشاهده پروفایل

استاد

• Celestial Mechanics
• Probability and Statistics
• Monte Carlo Techniques
• +۳ مورد دیگر

Jan Vrbik is a Professor of Mathematics at Brock University, affiliated with the Department of Mathematics and Statistics. His research spans Celestial Mechanics, Probability and Statistics, and Monte Carlo techniques. He holds a PhD and MSc from the University of Calgary, and completed his BSc and MSc at Charles University in Prague. Vrbik's work focuses on perturbed Kepler problems, statistical inference for autoregressive models, and numerical solutions to integral equations. His contributions include advancements in celestial mechanics via quaternionic methods and Monte Carlo simulations for quantum chemistry. He has published extensively in journals such as *Celestial Mechanics and Dynamical Astronomy*, *Communications in Statistics*, and *Journal of Chemical Physics*. He teaches courses including Probability, Mathematical Statistics, and Numerical Analysis. His research interests also encompass statistical distributions, confidence interval construction, and applications of numerical methods in engineering and physics.

Olha Matsyiمشاهده پروفایل

استادیار

• Operations Research
• Mathematical Optimization
• Computer Science
• +۳ مورد دیگر

Olha Matsyi serves as an Assistant Professor (post-doc) within the Division of Applications of Contemporary Mathematical Analysis at Lodz University of Technology, with contact details including email olha.matsyi@p.lodz.pl and phone (+48) 42 631-36-17. Her research focuses on Operations Research and Mathematical Optimization, specializing in combinatorial algorithms for location theory, knapsack problems, community detection, and VLSI routing. She employs metaheuristic and bio-inspired methods to solve NP-hard optimization challenges, bridging theoretical mathematics with engineering applications in healthcare logistics and crisis management. Publications from 2020-2025 demonstrate increasing emphasis on real-world implementations like mobile medical service optimization and decision support systems, alongside theoretical advances in continuous coverage and constrained classification. Collaborative work with researchers such as Oksana Pichugina highlights her interdisciplinary approach to algorithm design. No scientific awards were documented. Information regarding student mentorship, research grants, or specific laboratory teams was not provided in the source material.

Mengyu Xuمشاهده پروفایل

دانشیار

• High-Dimensional Statistics
• Time Series Analysis
• Covariance Matrix Estimation
• +۵ مورد دیگر

Dr. Mengyu Xu is an Associate Professor in the Department of Statistics and Data Science at the University of Central Florida (UCF). She holds a Bachelor's degree from Renmin University of China (2010), and a M.S. and Ph.D. from the University of Chicago (2012 and 2016). Her research focuses on high-dimensional statistical methods, time series analysis, and machine learning applications in diverse fields such as gas turbine performance prediction, terahertz spectroscopy of molecular crystals, and financial market dynamics. She is affiliated with the College of Sciences at UCF and teaches courses in statistics. Her research interests include covariance matrix estimation, dynamic network recovery from high-dimensional time series, distribution theory of quadratic forms, and hypothesis testing. Notably, she has contributed to advancements in fentanyl detection via terahertz spectroscopy and anomaly detection in industrial systems. Her work bridges statistical theory with practical applications in engineering, finance, and chemistry. Publications highlight her expertise in high-dimensional data analysis, machine learning integration with traditional statistical methods, and the development of novel methodologies for real-world challenges such as drug identification and predictive maintenance in gas turbines. She has explored asymmetric self-exciting processes in Bitcoin returns and contextual factors influencing student performance in online education environments. Labs/Teams: While no specific lab or team names are listed, her work suggests collaboration with interdisciplinary groups in data science, engineering, and computational chemistry at UCF.

• Computational Complexity
• Quantum Computing
• Linear Algebra
• +۳ مورد دیگر

Leonid Gurvits is a Professor in the Department of Computer Science at the City College of New York. His research focuses on computational complexity, quantum computing, linear algebra, algorithmic mathematics, and discrete optimization. He has made significant contributions to operator scaling, quantum algorithms, and polynomial methods, with applications in combinatorics, statistical mechanics, and information theory. His work bridges theoretical computer science and mathematics, addressing challenges in algorithm design, complexity theory, and matrix analysis. Despite extensive publications, no formal awards or student advisement records are explicitly mentioned in the provided texts. His research often intersects with optimization principles and interdisciplinary applications in computational physics and quantum information.

Xiangyi Mengمشاهده پروفایل

استادیار

• Quantum Networks
• Network Science
• Quantum Information
• +۱۱ مورد دیگر

Prof. Xiangyi "X" Meng is an Assistant Professor at Rensselaer Polytechnic Institute's Department of Physics, Applied Physics, and Astronomy. His academic journey includes a B.S. in microelectronics from Peking University and a Ph.D. in physics from Boston University under Prof. Eugene Stanley. He held postdoctoral positions at Northeastern University's Center for Complex Network Research with Prof. Albert-László Barabási and as a Research Associate at Northwestern University with Prof. István Kovács. RPI (2025-present): Assistant Professor Northeastern University (2021-2023): Postdoc Northwestern University (2023-2024): Research Associate His research spans quantum networks, network science, and interdisciplinary applications, with key contributions in: Quantum communication protocols Concurrence percolation theory Quantum field theory applications Computational social science Power grid resilience modeling Multi-community epidemic spreading Prof. Meng has published over 20 papers in top journals like Physical Review Letters, PNAS, and Nature Communications, focusing on quantum advantage in network connectivity, entanglement distribution, and nonlinear network dynamics. His work has been featured in Physics World and Phys.org media outlets. As an educator, he teaches Physics II and Introductory Quantum Mechanics . His team develops quantum-inspired machine learning architectures like entanglement-structured LSTM networks. Current research explores nonconvex entanglement measures and hypergraph immersion techniques for quantum network optimization.

Di Wuمشاهده پروفایل

استادیار

• Computer architecture
• Domain-specific acceleration
• Emerging computing paradigms
• +۳ مورد دیگر

Di Wu is an Assistant Professor at the University of Central Florida in the Department of Electrical and Computer Engineering. Their research focuses on next-generation computing systems spanning computer architecture , neuromorphic computing , and quantum computing . PhD in Electrical and Computer Engineering from University of Wisconsin, Madison (2023) Research highlights include innovations in domain-specific acceleration and heterogeneous systems . Recent publications demonstrate expertise in value-level parallelism , stochastic computing , and quantum error correction . Current projects target deep learning systems , neuromorphic brain-computer interfaces , and quantum architecture optimization . Professional recognition includes: 2024 ASPLOS Distinguished Artifact Evaluation Award 2024 Harold Peterson Outstanding Dissertation Award 2023 ML & Systems Rising Star Di Wu contributes to academic leadership as a program committee member for top conferences (ASPLOS, HPCA, ISCA, MICRO) and organizing chair roles for WUC @ ASPLOS 2024 and ARTEQC @ HPCA 2025.