جست‌وجوی استاد و پژوهشگر

Lionel Pichonمشاهده پروفایل

پژوهشگر

• Electromagnetics
• Electromagnetic Compatibility
• Wireless Power Transfer
• +۴ مورد دیگر

Lionel Pichon is a leading researcher at the Laboratory of Electrical and Electronic Engineering of the University of Paris. His primary affiliations include the Department of Electrical and Electronic Engineering of Paris, where he specializes in advanced electromagnetic research. His work focuses on Electromagnetics , Electromagnetic Compatibility (EMC) , and Wireless Power Transfer , with particular emphasis on composite materials, biomedical applications, and automotive systems. Expertise in numerical methods (FDTD, FIT, DGTD) for electromagnetic simulations Pioneer in shielding effectiveness analysis for composite materials Developer of AI-driven approaches for dielectric property characterization Over 70 publications since 2017 highlight his contributions to fields like inductive power transfer systems, medical device EMC, and GPR imaging techniques. Collaborates extensively with institutions globally, including research on antenna design for implantable medical devices and electromagnetic compatibility in healthcare facilities. Current research trends emphasize machine learning integration with traditional electromagnetic analysis to optimize system performance and safety standards.

Oleg Kitovمشاهده پروفایل

استادیار

• Time-series Econometrics
• Empirical Macroeconomics
• Income Distribution
• +۱ مورد دیگر

Oleg Kitov serves as an Assistant Teaching Professor and Robert Martin Fellow in Economics at Selwyn College, University of Cambridge, where he also acts as Convener of Undergraduate Admissions for the Faculty of Economics. His academic profile centers on rigorous econometric methodology applied to macroeconomic phenomena and distributional economics, with significant contributions to time-series analysis and income inequality research. Kitov's primary research domains include Time-series Econometrics, Empirical Macroeconomics, and Income Distribution and Inequality. His methodological innovations focus on structural break detection in linear models using multiplicative indicator saturation, generative modeling of age-income dynamics, and cross-national Phillips curve analysis. His work bridges theoretical econometrics with empirical applications, particularly examining inflation-unemployment relationships across diverse economies and modeling long-term trends in income distribution using historical datasets. His publication trajectory reveals consistent methodological advancement from 2012-2022, with core themes spanning structural break detection in economic time series, generative income distribution modeling, and comparative Phillips curve analysis across 15+ countries. The research demonstrates increasing sophistication in handling non-stationary economic data while maintaining strong policy relevance for central banking and inequality measurement. Scientific Awards: Cambridge Centre for Teaching and Learning Technology-enabled Learning Prize (2021) As Convener of Undergraduate Admissions, Kitov shapes the academic cohort for Cambridge's Economics program while teaching advanced econometrics. His office hours (Tuesdays 11:15am-12:15pm in Room 79) support student engagement with complex quantitative methods, reflecting his dual commitment to research excellence and pedagogical innovation recognized by the 2021 teaching prize.

Peter Sollichمشاهده پروفایل

استاد

• Non-equilibrium statistical physics
• Soft matter rheology
• Active matter
• +۷ مورد دیگر

Prof. Dr. Peter Sollich is a Professor of Theoretical Physics at Georg-August-Universität Göttingen, affiliated with the Institute for Theoretical Physics. His research spans non-equilibrium statistical physics with applications to soft matter, active systems, and complex networks. He maintains a small part-time appointment at King's College London. His primary research interests focus on non-equilibrium statistical physics , particularly soft and active matter rheology, jamming transitions, glassy dynamics, dynamical phase transitions, and inference from dynamical data. His work bridges theoretical physics with applications in materials science and network theory, emphasizing both fundamental mechanisms and quantitative modeling approaches. Analysis of his recent publications reveals strong thematic consistency in studying glassy dynamics and active matter systems , with increasing integration of machine learning techniques for network analysis. Key methodological threads include coarse-grained modeling, spectral analysis of complex systems, and non-equilibrium thermodynamics frameworks. His 2023-2025 work shows growing emphasis on nonreciprocal interactions in active mixtures and physics-inspired machine learning applications. Prof. Sollich actively supervises Bachelor's, Master's, and PhD students, welcoming thesis inquiries in theoretical physics. His group develops analytical and computational approaches to complex dynamical systems, with recent grants likely supporting work on network dynamics and active matter modeling (specific grants not detailed in source text). His research group operates within the Institute for Theoretical Physics at Göttingen, focusing on computational and analytical modeling of disordered systems. Current projects involve elastoplastic modeling of amorphous solids, spectral analysis of heterogeneous networks, and theoretical frameworks for active matter phase separation.

• Applied Probability
• Insurance Mathematics
• Finance
• +۳ مورد دیگر

Mogens Bladt is a Professor of Applied Probability and Insurance Mathematics at the Department of Mathematical Sciences, University of Copenhagen. He has held positions since 2018 after 24 years as Principal Researcher at the National University of Mexico (1994-2018), with visiting professorships at Technical University of Denmark and University of Copenhagen since 2001. Research: Focuses on time-inhomogeneous phase-type distributions, matrix-oriented life insurance models, heavy-tailed distributions, and diffusion bridge simulation Teaching: Offers graduate/undergraduate courses in Applied Probability, Stochastic Processes, Risk Theory, and Numerical Analysis Scientific Contributions: Developed R packages for Markov jump processes, phase-type distributions, and diffusion bridges. Holds grants from Mexico and Denmark, including Danish Research Council funding (2007–2008). Supervised 5 PhD, 8 Master’s, and 13 Bachelor’s theses Organized academic workshops and served as Associate Editor for Stochastic Models since 1997

Ye Heمشاهده پروفایل

استادیار مهمان

• Mathematical Foundations of Artificial Intelligence
• Machine Learning Theory
• Data Science
• +۳ مورد دیگر

Ye He serves as a Hale Visiting Assistant Professor in the School of Mathematics at the Georgia Institute of Technology, hosted by Prof. Molei Tao. His research bridges mathematical theory and artificial intelligence, focusing on developing rigorous frameworks for machine learning and data science applications. Education: Ph.D. in Mathematics, University of California, Davis (advised by Prof. Krishna Balasubramanian) Research Interests: Dr. He specializes in the mathematical foundations of artificial intelligence , with particular emphasis on scalable inference methods for complex data distributions. His work addresses fundamental challenges in sampling theory , diffusion-based generative modeling , and stochastic optimization , aiming to establish theoretical guarantees for practical machine learning algorithms. Current investigations focus on heavy-tailed distributions, non-log-concave sampling, and discrete data generation mechanisms. Publication Trends: His 11 most recent publications (2020-2025) reveal a concentrated research program advancing theoretical understanding of sampling algorithms and diffusion models. Work spans top venues including NeurIPS, COLT, and IEEE Transactions on Information Theory, with recurring themes in heavy-tailed distribution sampling, convergence analysis of Langevin dynamics, and optimization of generative architectures. The output demonstrates strong interdisciplinary connections between probability theory, statistics, and machine learning. Scientific Awards: No awards were documented in the source materials. Advising and Grants: The provided information contains no details regarding student supervision, research grants, or funding sources. Teaching responsibilities include undergraduate courses in calculus, linear algebra, and differential equations. Research Environment: Dr. He operates within Georgia Tech's School of Mathematics, collaborating closely with Prof. Molei Tao's research group. His office is located in Skiles 016, and his work contributes to the institution's strengths in mathematical data science and computational theory.

Paul Charlesrajمشاهده پروفایل

مدرس ارشد

• Project Management
• Construction Engineering
• Knowledge Management
• +۵ مورد دیگر

Paul Charlesraj is a Senior Lecturer in Construction Project Management at the University of Huddersfield, UK, affiliated with the Department of Design and Architecture within the School of Arts and Humanities. He is a Chartered Surveyor (MRICS), Project Management Professional (PMP®), and Certified Knowledge Manager (CKM). His roles include leading undergraduate and postgraduate courses in Construction and Project Management, and他曾担任MBA-CPM项目主任。他积极参与专业发展计划的开发，并在RICS和相关机构担任监督和评估角色。 教育背景未明确提及，但根据其职业轨迹推断，他拥有建筑或工程管理领域的高级学位。他的研究兴趣集中在技术驱动的施工管理，包括知识管理、数字施工、绩效管理以及灾害管理等领域。他致力于通过基于知识的教育和培训提升项目交付效率和价值创造。 研究方向包括项目管理、施工技术、知识管理、数字转型和领导力变革管理。其近期研究趋势聚焦于数字工具（如无人机、BIM）在施工中的应用，员工心理健康，以及新兴技术的采用障碍。他与VTT Technical Research Centre等机构建立了国际合作，并参与PMI标准委员会。 奖项方面，目前未提及具体科学荣誉。他积极参与学术活动，包括在国际会议上发表演讲（如2025年ICE邀请演讲）并担任同行评审。他的专业活动包括担任英国多家行业组织的会员，如项目管理协会（APM）和机构工程师学会（ICE）。 指导方面，虽然未列学生姓名，但提到他监督了RICS专业能力评估（APC）。实验室和团队包括参与Centre for Urban Design, Architecture and Sustainability及Innovative Design Lab Research Centre。

Andrew Wintersمشاهده پروفایل

دانشیار

• Numerical Analysis
• Computational Mathematics
• Partial Differential Equations
• +۱۲ مورد دیگر

Andrew Winters is a Senior Associate Professor in the Department of Mathematics at Linköping University, Sweden. He is affiliated with the Division of Applied Mathematics (TIMA), where he conducts research in computational mathematics and numerical methods for partial differential equations. His research focuses on the design and analysis of high-order numerical schemes, particularly nodal discontinuous Galerkin (DG) methods with summation-by-parts (SBP) properties, for solving hyperbolic and mixed hyperbolic-parabolic PDEs such as shallow water, Euler, Navier-Stokes, and magnetohydrodynamic (MHD) equations. His work emphasizes conservation, entropy stability, and thermodynamic consistency in numerical approximations. The recent publications highlight a strong trend in developing robust, high-order, entropy-stable methods for nonlinear conservation laws, with applications in fluid dynamics and geophysical modeling. His work integrates theoretical analysis with high-performance computing, particularly through the development of the FLUXO and Trixi.jl simulation frameworks. Energy Bounds for Discontinuous Galerkin Spectral Element Approximations Entropy Stable Hydrostatic Reconstruction Efficient Implementation of Entropy Stable DG Methods Adaptive Simulations with Trixi.jl Subcell Finite Volume Shock Capturing Andrew Winters is actively involved in software development and scientific computing education, including an introductory Fortran course for MATLAB users. He contributes to international collaborations, such as a four-way research and exchange program between Linköping University and Washington State University. He has no listed scientific awards in the provided text. He advises students in computational mathematics, though specific names are not mentioned. He is a core developer of the FLUXO (Fortran/MPI), Trixi.jl (Julia), and HOHQMesh.jl projects, which support high-order simulations and mesh generation.

Antonis Stylianouمشاهده پروفایل

دانشیار

• Computational Biomechanics
• Musculoskeletal Modeling
• Multibody Dynamics
• +۳ مورد دیگر

Antonis Stylianou is an Associate Professor in the Department of Mechanical Engineering at the University of Missouri - Kansas City (UMKC). He holds a Ph.D. in Mechanical Engineering from the University of Kansas (2004), along with multiple master's degrees in Mathematics (2012) and Mechanical Engineering (2000), and a B.S. in Mechanical Engineering (1998). His primary affiliation is within the School of Science and Engineering, where he focuses on computational biomechanics, musculoskeletal modeling, and multibody dynamics. Dr. Stylianou's research emphasizes Elbow joint mechanics and ligament deficiency modeling Virtual surgical simulators for pelvic surgery error prevention Pediatric knee anatomy and ACL injury risk analysis Musculoskeletal models of human motion Finite element analysis of cartilage contact pressures His work bridges computational methods with clinical applications, including developing tools for orthopedic surgeons and training paradigms for surgical techniques. Recent studies have explored surgeon kinematics during retropubic trocar insertion and posteromedial rotatory incongruity of the elbow. Teaching responsibilities include advanced dynamics, biomechanics, and experimental methods courses. His contributions underscore the integration of engineering principles with medical challenges, particularly in orthopedic and surgical contexts.

• Machine Learning
• Reinforcement Learning
• Causal Machine Learning
• +۷ مورد دیگر

Dr. Bevan Smith is a Senior Lecturer at the School of Mechanical, Industrial & Aeronautical Engineering at the University of the Witwatersrand (Wits), where he also completed his BIng(Mech), MSc(Eng), and PhD. His research bridges machine learning and engineering systems, with a focus on optimization through simulation and AI. His research interests include: Machine Learning and Reinforcement Learning Causal Machine Learning and Causal Discovery Graph Neural Networks Explainable AI (XAI) Digital Twins Application of AI in Education and Industrial Systems His recent publications demonstrate a strong trajectory in applying causal inference and machine learning to both industrial optimization (e.g., inventory management, air quality monitoring) and educational challenges (e.g., at-risk student prediction, online video interventions). He utilizes simulation-based methods and counterfactual reasoning to evaluate treatment effects and improve decision-making. His work spans journals in industrial engineering, artificial intelligence in education, and computational applications. Notable scientific contributions include: Developing AI-driven solutions for low-cost air quality monitoring (AI_r) Evaluating X-Learner performance under confounding and non-linearity Applying Pearl’s counterfactual framework to assess explanation validity Designing personalized interventions for engineering students using model-agnostic explanations Dr. Smith has contributed to curriculum development through the creation of online educational videos and has explored structural design in mechanical engineering, notably in carbon fibre swingarm development. While no formal advising or grant information is available, his work reflects an interdisciplinary approach combining mechanical engineering principles with cutting-edge AI methodologies. He is actively publishing and remains engaged in both technical and educational research domains.

Louise Lindbjergمشاهده پروفایل

استادیار

• Firm Innovation
• Pay Dispersion
• Research Equipment
• +۳ مورد دیگر

Louise Lindbjerg is an Assistant Professor at Aalborg University Business School, affiliated with The Strategy, Organization and Management Group within the Faculty of Social Sciences and Humanities. Her research focuses on firm innovation dynamics, pay dispersion effects, and entrepreneurial human capital. She leads multiple research projects including 'Entrepreneurial team composition and startup success' (2022–present) and 'Research equipment and firm innovation' (2018–present). Her work explores how organizational structures, labor market dynamics, and technological investments influence innovation outcomes. Notable contributions include studies on non-linear pay dispersion impacts on technological knowledge production and the role of R&D equipment in fostering collaborative innovation. Received Outstanding reviewer award (2023) and multiple conference nominations Active in peer review and conference participation (over 45 activities since 2018) Led 5 research projects since 2017 including her PhD project 'Three Essays on Firm Innovation' (2017–2022) Lindbjerg's research integrates economic modeling with strategic management insights, addressing topics like fixed effects analysis, Gini coefficients, and machinery utilization patterns. She is part of interdisciplinary teams exploring labor market externalities and horizontal pay structures' impact on organizational innovation.

• Formal Methods
• Satisfiability (SAT)
• Satisfiability Modulo Theories (SMT)
• +۱۱ مورد دیگر

Enric Rodríguez Carbonell is a faculty member at the Department of Computer Sciences within the Faculty of Computer Science at Universitat Politècnica de Catalunya (UPC). He is a key member of the LOGPROG - Lògica i Programació research group, focusing on formal methods, automated reasoning, and combinatorial optimization. Research Interests: His work centers on satisfiability (SAT), satisfiability modulo theories (SMT), and their applications in program verification, constraint solving, and optimization. He investigates techniques such as conflict-driven learning, invariant generation, and Max-SMT for proving termination and safety. His research bridges theoretical foundations with practical applications in software analysis and industrial problem-solving. Publication Trends: His recent publications (2020–2024) show a sustained focus on enhancing SAT and SMT solvers, particularly in pseudo-Boolean reasoning, integer linear programming, and multi-conflict analysis. Earlier works established contributions in non-linear arithmetic, termination proofs, and efficient encodings for cardinality constraints, reflecting a long-term commitment to foundational and applied aspects of automated reasoning. Scientific Awards: Best student paper award at SAT 2024 Advising and Grants: Rodríguez Carbonell has contributed to multiple competitive R+D+i projects under Spain’s State Research Plans, indicating active grant involvement. He has co-authored doctoral theses and educational initiatives like Jutge.org, demonstrating engagement in academic supervision and pedagogical innovation. Labs and Teams: He is a core researcher in the LOGPROG group at UPC, which specializes in logic and programming, with strong collaborations across formal methods, verification, and constraint technologies.

Sonia Corianiمشاهده پروفایل

استاد

• Quantum Chemistry
• Computational Spectroscopy
• Molecular Properties
• +۷ مورد دیگر

Sonia Coriani is a Professor in Physical Chemistry at DTU Chemistry, Technical University of Denmark, since 2017. She leads a research group focused on theoretical chemistry and computational spectroscopy. Her academic journey includes a PhD from Aarhus University (2000), a permanent research scientist position at the University of Trieste (1999-2014), and associate professorship there since 2014. She held an adjunct associate professor position at the Centre for Theoretical and Computational Chemistry in Oslo (2007-2011) and was a Marie Curie IEF fellow (2010-2012) and AIAS-COFUND senior fellow (2015-2016). Education: Chemistry, University of Modena (1993) PhD in Theoretical Chemistry, Aarhus University (2000) Her research centers on developing quantum-chemical methodologies for static and dynamic molecular properties, particularly for systems with high dimensionality, complex environments, or novel spectroscopic phenomena. Key areas include non-linear optical experiments, magnetic circular dichroism, X-ray spectroscopies, and quantum computing applications in chemistry. Her recent publications highlight advancements in quantum linear response theory, polarizable embedding environments, X-ray absorption in water, and quantum algorithms for molecular properties. Collaborative work spans interdisciplinary projects with experimentalists, covering gas-phase molecules to biomolecular systems. Scientific Awards: Marie Curie IEF fellowship AIAS-COFUND senior fellowship Her work addresses challenges in ultrafast dynamics, photoionization, and the intersection of chemistry with physics and computational science, emphasizing accuracy and novel experimental guidance.

Thomas G. Hansfordمشاهده پروفایل

استاد

• Judicial politics
• Interest group involvement in courts
• Supreme Court precedent
• +۴ مورد دیگر

Thomas G. Hansford is a Professor of Political Science at the University of California, Merced, where he also currently serves as Vice Provost for Academic Personnel. He is affiliated with the School of Social Sciences, Humanities and Arts and the Department of Political Science. Hansford earned his Ph.D. in 2001 from the University of California, Davis and his B.A. in 1993 from St. Mary's College of Maryland. Hansford's research focuses on American politics with particular emphasis on judicial politics, interest group involvement in courts, Supreme Court precedent, public opinion on courts and law, and elections and voting behavior. His work examines how courts interact with other political institutions, how public perceptions of courts are formed, and how legal precedent evolves within judicial hierarchies. He has developed innovative methodologies for measuring interest group ideology through amicus brief analysis and has explored the dynamics of judicial agenda setting across court levels. His research reveals that precedent dynamics operate not just top-down but also bottom-up, with lower court implementation of precedent providing valuable information to higher courts. Hansford's publications span top political science journals including the American Political Science Review, American Journal of Political Science, Journal of Politics, and many others. His research reveals important insights about bottom-up influence in judicial hierarchies, the role of interest groups in Supreme Court decision making, and how public perceptions of the judiciary are shaped by various factors including state court structures. Hansford is the coauthor of "The Politics of Precedent on the U.S. Supreme Court" (Princeton University Press) and is a creator of the Amici Space Project, which develops spatial models of interest group ideology based on amicus briefs filed with the Supreme Court. Throughout his career, Hansford has conducted extensive research using survey experiments to understand public perceptions of courts and has employed sophisticated statistical methods to analyze judicial behavior and precedent dynamics. His work on the informational dynamics of vertical stare decisis has provided new insights into how lower court implementation of precedent informs Supreme Court decision making.

Michael Kunzingerمشاهده پروفایل

استاد

• Generalized Functions
• Differential Geometry
• Partial Differential Equations
• +۳ مورد دیگر

Michael Kunzinger is a Professor at the Department of Mathematics, Faculty of Mathematics, University of Vienna. His research spans generalized functions, differential geometry, and mathematical physics, with a focus on Colombeau algebras, Lorentzian length spaces, and non-smooth geometric structures. His recent work includes stochastic PDEs on manifolds, synthetic curvature bounds, and causality in Lorentzian geometry. Articles highlight applications to conservation laws, sectional curvature analysis, and rigidity theorems. Notably, he explores connections between generalized functions and smooth manifold theory, advancing geometric regularization techniques. 2024: 9 publications on singular limits, Ricci curvature, and synthetic geometry. 2022: Studies on null distance and singularity theorems in low-regularity spacetimes.

Stephen M. Millerمشاهده پروفایل

استاد

• Monetary Economics
• Macroeconomics
• International Finance
• +۵ مورد دیگر

Stephen M. Miller is a Professor of Economics at the University of Nevada, Las Vegas, where he serves as Research Director for the Center for Business and Economic Research. He previously held positions at the University of Connecticut from 1970 to 2001, including serving as Department Head from 1989 to 2001, before joining UNLV as Department Chair from 2001 to 2012. Dr. Miller's research spans monetary, macroeconomic, and international finance theory and policy; economic growth empirics; financial institutions; and real estate lending. His work demonstrates particular expertise in time series analysis, long-memory processes, and econometric modeling of economic phenomena. He has developed significant economic indicators including the CBER-DETR Nevada Coincident and Leading Employment Indexes, which track contemporaneous and future movements in Nevada's employment situation. His extensive publication record includes over 190 journal articles in prestigious outlets such as the Journal of Macroeconomics , Journal of International Money and Finance , Journal of Real Estate Finance and Economics , and Empirical Economics . Recent work shows continued focus on income inequality dynamics, housing markets, monetary policy effects, and financial market interconnections using advanced econometric techniques including wavelet analysis and long-memory modeling. Dr. Miller has also been active in public discourse through numerous op-ed pieces in the Las Vegas Review Journal and other publications addressing economic issues relevant to Nevada and the broader U.S. economy. He has guided numerous graduate students to degree completion, with 16 MA students at UNLV and 18 PhD plus 2 MA students during his tenure at the University of Connecticut. His teaching portfolio includes courses in macroeconomics, money and banking, and mathematical economics at undergraduate, MA, and PhD levels.