جست‌وجوی استاد و پژوهشگر

Michael Fourmanمشاهده پروفایل

استاد

• Logic in Computer Science
• Artificial Intelligence
• Cognitive Science
• +۳ مورد دیگر

Michael Fourman is a Professor of Computer Systems at the School of Informatics, University of Edinburgh, within the College of Science and Engineering. His research focuses on applications of logic in Computer Science, Artificial Intelligence, and Cognitive Science, with contributions to formal methods, programming language semantics, and hardware specification. He has advised numerous PhD students and collaborated on EPSRC-funded projects, including work on probabilistic reasoning and program development tools like PropPlan. His research interests bridge mathematical logic, computer science, and cognitive science, emphasizing formal representations and their practical applications. He has explored categorical semantics for programming languages, hardware design tools, and AI planning systems. Recent work includes integrating logical and probabilistic reasoning frameworks. Key tools developed include PropPlan (BDD-based planner) and PropSat , alongside contributions to formal verification and categorical logic. His publications span over four decades, addressing topics from intuitionistic logic to modern informatics challenges.

Paul Wiegandمشاهده پروفایل

دانشیار

• Machine Learning
• Optimization
• Natural Computation
• +۳ مورد دیگر

R. Paul Wiegand is an Associate Professor in the Department of Computing & Information Sciences at Winthrop University's College of Business Administration. He holds a Ph.D. in Computer Science from George Mason University (2004), an M.S. from the University of North Carolina-Charlotte (1999), and a B.S. from Winthrop University (1996). His research focuses on machine learning, optimization, natural computation, multiagent systems, and probabilistic reasoning, with recent work exploring novelty search algorithms and coevolutionary methods. He has held roles at the University of Central Florida and the Navy Center for Applied Research in Artificial Intelligence. Dr. Wiegand's pedagogical approach emphasizes contextual learning and student engagement. He actively organizes academic events like the Winthrop SMACS Programming Competition and co-leads the interdisciplinary Mathematics & Computer Science student seminar. His research projects include NSF-funded work on coevolutionary peer-instruction systems and DoD-funded smart network routing algorithms. He also explores foundational theory for swarm-based task allocation and decentralized systems. Key research contributions include studies on robust path tracking, evolutionary programming for Parsons puzzles, and multiagent learning dynamics. His work bridges theoretical computer science with practical applications in education, robotics, and network optimization. Beyond academia, he plays in the bands Read-Only Time Travel and PhyNight , contributing to local music scenes in South Carolina.

Christine Zargesمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Evolutionary Algorithms
• Optimization
• +۳ مورد دیگر

Christine Zarges is a Senior Lecturer in the Department of Computer Science at Aberystwyth University. Her research focuses on evolutionary algorithms, artificial immune systems, and optimization techniques, with applications in data preprocessing, anomaly detection, and bioinformatics. She has contributed significantly to the theoretical foundations of immune-inspired randomized search heuristics and has explored their practical implementations in various domains. Her work often addresses challenges in combinatorial optimization, such as improving variable orderings in OBDDs and developing efficient algorithms for Lyndon factorization of biosequences. Recent projects include applications of adversarial diffusion for video anomaly detection and the use of rough set theory for big data preprocessing. She has also been involved in initiatives to address bias in physical science and engineering research. Christine has led and collaborated on externally funded projects, including the Horizon 2020-funded RoSTBiDFramework project and EPSRC grants focused on bias reduction in STEM fields. She has supervised graduate students, such as Yumna Zahid, whose work contributes to video anomaly detection. She actively contributes to the academic community by organizing conferences like EvoCOP and the Genetic and Evolutionary Computation Conference (GECCO), and serves on editorial boards of journals including Evolutionary Computation and IEEE Transactions on Evolutionary Computation .

Jose Miguel Zapata Garciaمشاهده پروفایل

استاد

• Statistics
• Operations Research
• Convex Analysis
• +۳ مورد دیگر

Jose Miguel Zapata Garcia is a Professor in the Department of Statistics and Operational Research at the University of Murcia's Faculty of Mathematics. He completed his doctoral studies at the University of Murcia in 2018 with a thesis titled A Boolean-valued Models Approach to L-Convex Analysis, Conditional Risk and Stochastic Control , supervised by Dr. José Orihuela Calatayud. His research affiliations include the Characterization, Ordering and Classification of Distributions group and previously contributed to the Functional Analysis group. His work focuses on advanced mathematical methodologies combining convex analysis, stochastic processes, and distribution theory. No recent publications or awards are listed in the provided information. His academic profile emphasizes foundational research in mathematical statistics and operations research with applications to risk modeling and control systems.

Aleksandar Pavlovićمشاهده پروفایل

دانشیار

• Functional Analysis
• Geometry
• Topology
• +۳ مورد دیگر

Aleksandar Pavlović is an Associate Professor at the University of Novi Sad's Faculty of Sciences and Mathematics (PMF), within the Department of Mathematics and Informatics. His primary research focuses on Functional Analysis, Geometry, Topology, and Set-Theoretic Topology, with a particular emphasis on ideal topological spaces and continuity properties. He holds an office in the DMI&DF building (second floor, room 38) and can be reached at apavlovic@dmi.uns.ac.rs. Pavlović’s work bridges pure mathematics with foundational studies in topology and Boolean algebras. His research interests include exploring closure operations, topological expansions, and continuity in specialized spaces. Notably, his articles analyze topics like ideal topological spaces, local closure functions, and convergence structures in Boolean algebras. He has also contributed to historical analyses of cultural representations, such as textbook depictions of Albanians in Serbian education (1882–1941). Pavlović’s publications span theoretical mathematics, including studies on generalized ordered spaces, sequential topologies, and forcing-related convergence. His work often integrates set-theoretic methods with topological frameworks. While no formal awards or grants are listed, his active research output reflects sustained engagement with advanced mathematical topics. His personal website (http://people.dmi.uns.ac.rs/~apavlovic/) provides further details on his projects and academic contributions. No advisee students or specific laboratory affiliations are mentioned in the provided materials.

• Fourier analysis
• Harmonic analysis
• Real analysis
• +۷ مورد دیگر

Joris Roos is an Assistant Professor at the University of Massachusetts Lowell within the Department of Mathematics and Statistics, part of the Kennedy College of Sciences. He holds a Ph.D. in Mathematics from the University of Bonn (2017). His research focuses on Fourier analysis, real analysis, and computer-assisted proofs, with particular emphasis on harmonic analysis applications in combinatorics, number theory, PDEs, and fractal geometry. He has been supported by grants including the NSF DMS-2154835 (2022-2025) and a Simons Foundation Grant (2021-2022). Roos has also participated in fellowships at the Hausdorff Research Institute for Mathematics and Oberwolfach. His work bridges pure analysis with computational methods, addressing problems in multilinear inequalities, maximal functions, and sparse domination techniques. Education: Ph.D. in Mathematics, University of Bonn, 2017 Research Interests: Fourier and harmonic analysis on Euclidean spaces Oscillatory integrals, maximal functions, singular integrals Discrete analogues in harmonic analysis Applications to combinatorics, number theory, dispersive PDEs Formalization of mathematics using interval arithmetic Grants & Fellowships: National Science Foundation Grant DMS-2154835 (2022-2025) Simons Foundation Grant ID 855692 (2021-2022) American Institute of Mathematics SQuaRE projects (2021-2025) Hausdorff Research Institute for Mathematics Fellowships (2021, 2022, 2024) Oberwolfach Research Fellowship (2023) Current Activity: Leading the 2024 HIM Trimester Program on Boolean Analysis in Computer Science and co-organizing the MLHA 2024 Spring School on multilinear singular integrals.

• Combinatorics
• Probability Theory
• Statistical Physics
• +۳ مورد دیگر

Bhargav Narayanan is an Associate Professor in the Department of Mathematics at Rutgers University. His research focuses on combinatorics, probability theory, statistical physics, and theoretical computer science, with a specialization in combinatorial models and probabilistic methods. He organizes a weekly seminar at Rutgers exploring these topics. Previously, he held a research fellowship at St John's College, Cambridge, and completed his PhD under Béla Bollobás at Cambridge University. Education: PhD in Mathematics from the University of Cambridge. Career: Postdoctoral research at St John's College, Cambridge before joining Rutgers. Research Interests: Combinatorics, probability theory, statistical physics, and theoretical computer science. He has published extensively in top-tier journals such as the Annals of Mathematics and the Journal of the European Mathematical Society. Selected publications highlight contributions to antichain codes, random graph bisections, threshold phenomena, and combinatorial optimization. His work often bridges discrete mathematics and applications in physics and computer science. He has taught graduate courses on additive combinatorics, spectral methods, and probabilistic methods in combinatorics. No scientific awards explicitly listed in the provided texts. Advising: No students listed explicitly in the text. Grants: No specific grants mentioned. Lab/Team: Organizes a weekly research seminar at Rutgers.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Huan Zhou is a prolific researcher affiliated with multiple institutions including the University of Oldenburg , China Three Gorges University , and Wuhan University . His work spans Computer Science , Mathematics , and Engineering disciplines. Key affiliations: Signal Processing Group (Oldenburg), Computer and Information Technology College (China Three Gorges University), Geodesy and Geomatics (Wuhan University) Research interests include: Graph Theory : Resistance spectra, planar graph properties, and spectral analysis Optimization Algorithms : Manta ray foraging, vortex search, and swarm intelligence applications Computer Vision : Road segmentation, stereo matching, and remote sensing image analysis Telecommunications : RIS-assisted wireless systems and beamforming techniques Machine Learning : Anomaly detection, continual learning, and transformer architectures Recent publications demonstrate cross-domain impact in bioinformatics (TriGCN for medicine), network systems (Plover distributed logging), and computational pathology (glioma diagnosis with transformers).

Jerry Draayerمشاهده پروفایل

استاد

• Nuclear Theory
• Computational Physics
• Algebraic Methods
• +۱ مورد دیگر

Jerry Draayer is the Roy P. Daniels Professor of Physics at Louisiana State University and an LSU Distinguished Research Master. He earned his Ph.D. from Iowa State University in 1968. His research program focuses on nuclear structure theory, computational physics, and algebraic methods applied to quantum systems. Research examines low-energy nuclear phenomena including rotational/vibrational collective behavior, superdeformed configurations, and double beta decay processes. Draayer employs group theory and high-performance computing to study microscopic and macroscopic descriptions of nuclei. His work establishes connections between nuclear collective motion and underlying nucleon interactions, particularly in rare-earth and actinide nuclei. Key publications explore symplectic symmetries in ab initio nuclear models and q-deformation effects in nuclear interactions.

Jeffrey Hoganمشاهده پروفایل

دانشیار

• Harmonic Analysis
• Signal Processing
• Wavelet Analysis
• +۵ مورد دیگر

Jeffrey Hogan is an Associate Professor in the School of Information and Physical Sciences (Mathematics), University of Newcastle. He holds academic appointments including Head of Mathematics Discipline and former Deputy Head of the School of Mathematical and Physical Sciences. His research focuses on harmonic analysis, wavelet theory, and applications in signal processing, including bandlimited signals, prolate spheroidal wave functions, and quaternion-valued wavelets. Hogan earned his BSc (Hons) and PhD from the University of New South Wales, followed by postdoctoral roles at institutions like the University of Texas and University of Arkansas before joining Newcastle in 2009. Education: Bachelor of Science, University of New South Wales PhD (Mathematics), University of New South Wales Research Interests: Jeffrey Hogan explores pure, applied, and computational harmonic analysis, including singular integrals, wavelet frames, Clifford-Fourier theory, and applications in mineral fractionation. His work emphasizes spatio-spectral limiting, multidimensional wavelet construction, and quaternionic signal processing. Key projects involve developing algorithms for EEG analysis, optimizing wavelet design via projection methods, and analyzing signals on graphs and hypercubes. Grant Funding: A$546,913: Enhanced Fractionation of Mineral Particles According to Density (ARC Discovery Project, 2020–2022) A$593,621: Relaxed Reflection Methods for Feasibility and Matrix Completion Problems (ARC Discovery Project, 2016–2018) Collaborations & Teams: Hogan collaborates with experts like Prof. Kevin Galvin (University of Newcastle), Prof. Joseph Lakey (New Mexico State University), and Dr. Matthew Tam (University of Göttingen). His work integrates interdisciplinary approaches, combining pure mathematics with applications in engineering and mineral processing. His lab focuses on computational harmonic analysis and optimization-driven wavelet design.

Damek Shea Davisمشاهده پروفایل

استادیار

• Optimization
• Stochastic Algorithms
• Nonconvex Optimization
• +۴ مورد دیگر

Damek Shea Davis is an Assistant Professor in Cornell University's School of Operations Research and Information Engineering, College of Engineering. He received his Ph.D. in Mathematics from UCLA in 2015 and joined Cornell in 2016. Davis focuses on mathematical foundations of data science, with particular expertise in optimization, statistical learning, and numerical algorithms. His research develops theoretical frameworks and efficient algorithms for nonconvex, nonsmooth, and stochastic optimization problems. Key contributions include convergence guarantees for stochastic subgradient methods on nonconvex functions, analysis of optimization landscapes for phase retrieval, and development of methods for high-dimensional statistical estimation. His work bridges mathematical optimization with machine learning and signal processing applications. Davis has received numerous honors including the Sloan Research Fellowship (2020) and INFORMS Optimization Society Young Researchers Prize (2019). His publications advance understanding of optimization algorithm behavior in statistically challenging regimes, with recent work exploring geometric convergence properties and optimality conditions.

Janos Simonمشاهده پروفایل

استاد

• Computational Complexity
• Algorithms
• Distributed Computing
• +۱ مورد دیگر

Janos Simon is a Professor of Computer Science at the University of Chicago. His research focuses on computational complexity, algorithms, and distributed systems, with special interests in lower bound techniques and fault-tolerant models. He serves as Editor in Chief of the Chicago Journal of Theoretical Computer Science. His research explores diverse areas including combinatorial algorithms for optical networks, distributed computing in mobile networks, and biologically-inspired computational models. Work spans theoretical foundations to applied problems in vehicular networks and sensor systems. Professor Simon has supervised numerous PhD students in theoretical computer science and maintains active collaborations in fault-tolerant distributed computations and complexity theory.

• Theoretical Computer Science
• Computational Complexity
• Optimization Algorithms
• +۳ مورد دیگر

Dr. Lucas Slot is a Lecturer at the Department of Computer Science, ETH Zurich, specializing in theoretical computer science, computational complexity, and optimization algorithms. His research focuses on polynomial optimization, sum-of-squares hierarchies, and semidefinite programming, with applications to algorithmic design and complexity analysis. Recent work includes studies on computational thresholds in stochastic block models, convergence rates of optimization hierarchies, and kernel-based methods for high-dimensional inference. His contributions span theoretical foundations and algorithmic advancements in mathematical programming and geometric data analysis. Lacking explicit mentions of academic awards or grants, Dr. Slot’s scholarly activities emphasize computational and mathematical challenges in optimization and discrete geometry. No student advisees are listed in the provided materials.

• Theoretical Computer Science
• Complexity Theory
• Analysis of Boolean Functions
• +۲ مورد دیگر

Hamed Hatami is an Associate Professor in the School of Computer Science at McGill University, with cross-appointment in Mathematics. His research lies at the intersection of theoretical computer science and mathematics, focusing on analytic methods in complexity theory, learning theory, analysis of Boolean functions, and additive combinatorics. Hatami received the IEEE Computer Society Technical Achievement Award in 2012 for his contributions. He has published extensively on graph theory, property testing, communication complexity, and combinatorial limits. Hatami teaches advanced courses in algorithm design, complexity theory, and analysis of Boolean functions, and mentors graduate students through research collaborations. Prior to McGill, he held positions at the Institute for Advanced Study and Princeton University.

• Boolean function analysis
• Computational complexity
• Combinatorics
• +۳ مورد دیگر

Yuval Filmus is an Associate Professor at the Technion's Henry and Marilyn Taub Faculty of Computer Science, with a secondary appointment in the Mathematics Department since 2022. His academic journey includes a BSc from the Open University of Israel, MSc under Uri Feige at the Weizmann Institute, and PhD under Toni Pitassi at the University of Toronto. After a postdoc at the Institute for Advanced Study in Princeton, he joined Technion in 2015. Research focuses on Boolean function analysis, computational complexity, combinatorics, and submodular optimization. He has held grants from ISF and ERC, and is a recipient of the Alon Fellowship and Krill Prize. His work involves international collaborations, including visits to Charles University, Simons Institute, KTH, McGill University, and TIFR. He has advised numerous graduate students and postdocs, with notable advisees including Johnathan Spiegelman (now at MPI Saarbrücken), Artur Ryazanov (EPFL), and Idan Mehalel (NSF/Simons Collaboration postdoc). His academic network spans institutions globally, reflecting his contributions to theoretical computer science.