جست‌وجوی استاد و پژوهشگر

Jeffrey Lyonsمشاهده پروفایل

دانشیار

• Fractional Calculus
• Differential Equations
• Boundary Value Problems
• +۳ مورد دیگر

Dr. Jeffrey Lyons is an Associate Professor in the Department of Mathematical Sciences at The Citadel, part of the Swain Family School of Science and Mathematics. He specializes in fractional calculus, differential equations, and boundary value problems. His teaching spans from foundational courses like College Algebra and Calculus to advanced topics such as Applied Engineering Mathematics and Differential Equations. Dr. Lyons holds a Ph.D. in Mathematics (2011) from Baylor University, with prior positions at Trinity University, University of Hawaii, and Nova Southeastern University. His research focuses on theoretical and applied aspects of fractional boundary value problems, including fixed point theorems and solution differentiation under varying boundary conditions. Notable awards include the 2011 Chancellor’s Award for Excellence in Teaching and several research grants supporting collaborative work across institutions. His recent publications explore topics like positive solutions for fractional BVPs, Caputo derivatives, and dynamic equations on time scales. These contributions highlight advancements in analytical methods and their applications in mathematical modeling. Dr. Lyons actively participates in academic communities, presenting at international conferences such as the 10th AIMS Conference in Madrid, Spain.

• Renewable Energies
• Solar Technology
• Thermoelectrics
• +۴ مورد دیگر

Prof. Dr. Nadine Buczek serves as Professor of Renewable Energies, Nanotechnology and Photonics at the Department of Applied Natural Sciences, Lübeck University of Applied Sciences (TH Lübeck), a position she has held since 2017. She leads the Energy Materials Laboratory and maintains active affiliations with the Climate and Environmental Protection Group, Materials for Storage and Renewable Energy Systems, and Photovoltaics Group. Her research centers on physical principles of renewable energy systems and photonics, with core expertise in solar technology, thermoelectrics, and nanoscale material engineering. She investigates spin wave phenomena in disordered magnetic materials and develops advanced fabrication techniques for silicon nanowires and superlattices using metal-assisted chemical etching, with applications in sustainable energy conversion and storage. Analysis of her 15 most recent publications (2012-2022) reveals consistent focus on condensed matter physics and nanomaterial engineering. Key trends include theoretical modeling of spin dynamics in alloys, structural characterization of etched semiconductor nanostructures, and optimization of nanofabrication processes for renewable energy applications. Her work bridges experimental nanotechnology with computational physics, primarily targeting semiconductor-based energy solutions. The Energy Materials Laboratory under her direction drives interdisciplinary research in photovoltaics and thermoelectric materials, collaborating closely with the Materials for Storage and Renewable Energy Systems group. Current projects emphasize scalable nanofabrication methods and fundamental studies of charge transport in nanostructured materials to advance next-generation renewable energy technologies.

• Partial Differential Equations
• Shape Optimization
• Numerical Analysis
• +۳ مورد دیگر

Arian Novruzi is a Full Professor in the Department of Mathematics and Statistics at the University of Ottawa, Faculty of Science. His expertise lies in partial differential equations (PDEs), shape optimization, numerical analysis, and mathematical modeling. He holds an MSc from the University of Tirana and a PhD from the University of Nancy. His research integrates theoretical and applied mathematics, with a focus on fluid dynamics, biomedical applications, and engineering challenges. Education: MSc in Mathematics, University of Tirana PhD in Mathematics, University of Nancy Dr. Novruzi’s research interests include the analysis and numerical solutions of PDEs, optimization of geometric shapes for engineering systems, and modeling of complex physical phenomena such as blood flow and tumor radiation therapy. His work bridges pure mathematics with practical applications, addressing problems in fluid mechanics, materials science, and biomedical engineering. His recent publications highlight advancements in non-diffusive neural network methods for hyperbolic conservation laws, blood flow modeling using Navier-Stokes equations, and the optimization of convex domains for energy maximization. These studies emphasize both theoretical rigor and computational innovation. Awards: No scientific awards explicitly mentioned in the provided texts. Dr. Novruzi has supervised students such as Terence C. Ngouoko. His grants and collaborations are not detailed here, but his research has implications for energy-efficient engineering designs and medical treatments. He has authored a Springer textbook on PDEs, reflecting his commitment to educational resources in mathematical sciences.

Li Chenمشاهده پروفایل

دانشیار

• Late Imperial and Modern China
• International Law
• East Asian Legal Cultures
• +۴ مورد دیگر

Li Chen is Associate Professor of History and Global Asia Studies in the Department of Historical and Cultural Studies (UTSC) at the University of Toronto, with cross-appointments to the Graduate Department of History and the Faculty of Law. He served as Chair of the Department of Historical and Cultural Studies (2016–2019) and as President of the International Society for Chinese Law and History (2014–2017). His scholarship focuses on late-imperial and modern Chinese legal history, Sino-Western relations, and comparative legal cultures. Education J.D., University of Illinois, magna cum laude Ph.D., Chinese History, Columbia University Research Interests Chen’s work interrogates the intersection of law, empire, and culture in China from the 15th to the 20th centuries. He explores how legal knowledge was produced and circulated among private specialists in the Qing juridical field, how international law shaped Sino-Western encounters, and how colonial discourses constructed images of Chinese law and sovereignty. His current SSHRC-funded monograph, Invisible Power and Technocratic Governance , offers the first comprehensive study of Confucian-literati-turned-legal-advisors who quietly administered Qing local justice. Publications & Impact Chen’s 2016 monograph Chinese Law in Imperial Eyes received the Joseph Levenson Book Prize (pre-1900 China) and honorable mention for the Peter Gonville Stein Book Award. His articles in Law & History Review , Journal of the History of International Law , and Late Imperial China have been translated into Chinese and Korean, influencing scholarship across East Asia and North America. Awards & Honors Joseph Levenson Book Prize, Association for Asian Studies (2018) Peter Gonville Stein Book Award – Honorable Mention, American Society for Legal History (2017) Law and Society Association Article Prize – Honorable Mention (2011) Grants & Projects He is principal investigator on a multi-year SSHRC Insight Grant supporting archival research in China, Taiwan, Japan, the United Kingdom, and France for his forthcoming book on Qing legal specialists and their role in shaping imperial governance and legal culture.

• Parallel and Distributed Computing
• High-Performance Computing (HPC)
• AI Hardware Acceleration
• +۴ مورد دیگر

Xiaodong Yu is an Assistant Professor in the Department of Computer Science at Stevens Institute of Technology (since 2023), leading the Advanced Parallel and distributEd Computing and Systems (APECS) lab. Previously, he served as an Assistant Computer Scientist at Argonne National Laboratory (2019–2023) and a Scientist-at-Large at the University of Chicago’s Consortium for Advanced Science and Engineering (2022–2023). He holds a Ph.D. in Computer Science from Virginia Tech (2019). His research focuses on parallel/distributed computing systems, next-generation AI hardware, high-performance MLSys for large language models (LLMs), and federated learning communication/privacy. Over 50 peer-reviewed publications appear in top-tier venues like HPDC, ICS, and SC. He leads NSF and DOE-funded projects, including an NSF CRII award (2024–2026) and Argonne LDRD initiatives. Technical leadership roles include serving on conference committees (ICS, SC, IPDPS) and review boards (IEEE TPDS). Key contributions include compressor frameworks for AI accelerators (e.g., DCT-based), MPI collective communication optimizations, and GPU-based ptychographic reconstruction. His work bridges hardware-software co-design for HPC and AI systems. Current advising includes five Ph.D. students at Stevens and prior mentorship of over 10 researchers at Argonne. Professional activities include institutional service (Stevens CS faculty search committee) and roles as finance chair (ISPASS), technical program committee member (DRBSD, IWBDR), and reviewer for journals like Future Generation Computer Systems.

Javier Peñaمشاهده پروفایل

استاد

• Operations Research
• Convex Optimization
• First-Order Methods
• +۵ مورد دیگر

Javier Peña is the Bajaj Family Chair Professor of Operations Research at the Tepper School of Business, Carnegie Mellon University, where he has been a faculty member since 1999. He currently holds the rank of Professor with tenure in the Department of Operations Research. His educational background includes: PhD in Applied Mathematics from Cornell University (1998) MS in Computer Science from Cornell University (1997) MS in Mathematics from Universidad de Los Andes, Bogotá, Colombia (1993) BS in Electrical Engineering from Universidad de Los Andes, Bogotá, Colombia (1991) BS in Mathematics from Universidad de Los Andes, Bogotá, Colombia (1991) Professor Peña's research focuses on the theoretical foundations and practical applications of optimization. His primary research interests include condition numbers for optimization, algorithms for convex optimization (particularly first-order methods), and equilibria computation. He has made significant contributions to understanding the convergence properties of the Frank-Wolfe algorithm and related first-order methods. His work uniquely bridges theoretical analysis with practical applications, particularly in finance and data science. His research demonstrates a consistent pattern of investigating the fundamental mathematical properties of optimization problems while developing practical algorithms with provable convergence guarantees. His extensive publication record shows a clear evolution from foundational work on condition numbers and Hoffman constants toward more applied research on first-order methods and their applications. A notable trend is his recent focus on affine-invariant analysis of optimization algorithms, which provides deeper insights into algorithm behavior independent of coordinate systems. His work frequently appears in top optimization journals like Mathematical Programming and SIAM Journal on Optimization. Professor Peña is also the co-author of the influential textbook 'Optimization Methods in Finance,' now in its second edition, which has become a standard reference in the field. In terms of teaching, Professor Peña regularly instructs courses in Probability and Statistics, Financial Optimization, and Convex Optimization. His teaching approach emphasizes practical applications, with students in Financial Optimization routinely using open-source financial datasets like Alpha Advantage Open Stock API in their projects. He has been actively involved in the academic community through numerous conference presentations, seminar invitations, and committee service at Carnegie Mellon University, including roles on the Faculty Senate, Promotion and Tenure Committee, and various curriculum committees.

Tobias Neckelمشاهده پروفایل

دانشیار

• Uncertainty Quantification
• Random Differential Equations
• Numerical Algorithms
• +۴ مورد دیگر

Tobias Neckel is an Associate Professor at the Institute for Informatics at the Technical University of Munich (TUM), where he leads research projects and coordinates academic programs. He has been the project team leader of the IGGSE Project ExaNIML since 2018, main coordinator of the Ferienakademie since 2014, and Program Coordinator of the Bavarian Graduate School of Computational Engineering (BGCE) since 2009. Diploma in Technomathematik from TU München (2005) Dr. rer. nat. in Informatics from TU München (2009) Neckel's research focuses on Uncertainty Quantification, Random Differential Equations, and High Performance Computing. His work develops efficient numerical algorithms using hierarchic and adaptive methods such as octrees/spacetrees and sparse grids, with applications in fluid-structure interactions and incompressible fluid flow simulation. His research bridges theoretical mathematics with practical computational science, emphasizing robust and efficient implementations. His recent publications demonstrate a strong trajectory in multi-fidelity modeling, uncertainty quantification, and high-performance computing. Neckel has made significant contributions to scalable hierarchical approximation methods, dynamic resource management in HPC, and the application of machine learning techniques to computational science problems. His work spans diverse application domains including plasma physics, hydrology, and computational engineering. Lehrfonds prize of the TUM (2014) Ernst Otto Fischer prize of the TUM (2011) Promotionspreis des Bunds der Freunde der TU München (2009) Neckel has supervised numerous graduate students and has been actively involved in curriculum development and teaching innovation. His book "Bits and Bugs: A Scientific and Historical Review of Software Failures in Computational Science" (2019) represents a significant contribution to understanding software reliability in scientific computing. He has organized minisymposia at major conferences including SIAM CSE and SIAM UQ, and serves on program committees for various computational science conferences. As coordinator of the Ferienakademie and the BGCE, Neckel plays a central role in advanced computational engineering education in Bavaria. His research group develops software for exascale computing and contributes to the Transregional Collaborative Research Centre 89 on Invasive Computing. Neckel also maintains international collaborations, with research stays at institutions including the Australian National University and Tokyo Institute of Technology.

• Fixed Point Theory
• Nonlinear Functional Analysis
• Operator Theory
• +۷ مورد دیگر

Jesus Garcia Falset is a Full Professor in the Department of Mathematical Analysis at the Faculty of Mathematics, University of Valencia, Spain. He has been an active researcher since the early 1990s, with a primary focus on nonlinear functional analysis and fixed point theory in Banach spaces. Doctorate: University of Valencia (1990), thesis on Banach spaces and fixed point properties. Position: Catedrático de Universidad (Full Professor). Department: Mathematical Analysis. Faculty: Faculty of Mathematics. Email: jesus.garcia@uv.es. Homepage: https://www.uv.es/garciaf/ . His research lies at the intersection of functional analysis, operator theory, and differential equations. Key interests include fixed point theory for nonexpansive and generalized nonexpansive mappings, geometric properties of Banach spaces (such as uniform nonsquareness and normal structure), measures of noncompactness, accretive operators, and nonlinear semigroups. He has made significant contributions to the understanding of conditions under which Banach spaces possess the fixed point property. His work often involves the application of topological and geometric methods to prove existence results for differential and integral equations in infinite-dimensional spaces. The 15 most recent articles highlight a consistent research trajectory in nonlinear functional analysis. They explore fixed point theorems for various classes of mappings (pseudocontractive, multivalued, generalized nonexpansive), the role of measures of noncompactness, and applications to differential equations in Banach spaces, including models for cell population growth. There is a strong emphasis on existence, uniqueness, and well-posedness of solutions using abstract functional-analytic frameworks. While specific scientific awards are not mentioned in the provided text, his extensive publication record (66 publications, including a book), high citation count (over 800 citations in zbMATH), and long-standing professorship indicate significant recognition within the mathematical community. Dr. Garcia Falset has supervised or collaborated with several researchers, including notable co-authors like Enrique Llorens-Fuster, David Ariza-Ruiz, Khalid Latrach, and Simeon Reich. His collaborative work spans topics in fixed point theory, differential equations, and operator theory. No specific grants or funding sources are mentioned in the provided information. He is associated with the research group in Mathematical Analysis at the University of Valencia. His work contributes to the theoretical foundations used in mathematical biology and dynamical systems, particularly through the analysis of evolution equations. His homepage and presence in zbMATH, MGP, and Wikidata reflect an active academic profile.

Corrado Mauriniمشاهده پروفایل

استاد

• Fracture Mechanics
• Damage Mechanics
• Computational Mechanics
• +۵ مورد دیگر

Corrado Maurini is a Professor in Mechanics at Sorbonne University , Paris, France. He leads two international master programs: Mécanique des Solides (Solid Mechanics) and Computational Mechanics .

Haipeng Luoمشاهده پروفایل

دانشیار

• Machine Learning
• Online Learning
• Reinforcement Learning
• +۳ مورد دیگر

Haipeng Luo is an Associate Professor at the Thomas Lord Department of Computer Science, University of Southern California, holding the IBM Early Career Chair. He previously worked as a Postdoctoral Researcher at Microsoft Research, NYC, and has held visiting roles at Google and Amazon. His research focuses on developing practical machine learning algorithms with strong theoretical guarantees, particularly in online learning, bandit problems, reinforcement learning, and game theory. PhD in Computer Science, Princeton University (2011–2016) BSc in Computer Science, Peking University (2007–2011) His work spans adversarial and stochastic environments, addressing challenges in reinforcement learning, game dynamics, calibration, and omniprediction. Recent publications highlight advancements in regret minimization, game equilibrium computation, and robust optimization frameworks. Key contributions include algorithms for zero-sum games, bandit problems with feedback graphs, and theoretical analyses of convergence properties in multi-agent systems. Scientific accolades include Best Paper Awards at COLT 2021, COLT 2018, NeurIPS 2015, and ICML 2015. He has received prestigious grants such as the NSF CAREER Award (2020), Google Faculty Research Award (2020), and NSF CRII Award (2018). His students have secured academic and industry positions, and he actively teaches graduate courses in machine learning and online optimization.

• Interactive Global Illumination
• Perceptual Graphics
• Non-physical Graphics
• +۱ مورد دیگر

Tobias Ritschel is a Professor of Computer Graphics at University College London . His research spans advanced rendering techniques, perceptual modeling, and data-driven graphics, with a focus on bridging physical accuracy and artistic flexibility in visual computing. Key research themes include: Interactive Global Illumination : Real-time simulation of complex lighting effects on GPUs Perceptual Graphics : Human vision-driven rendering and display optimization Non-physical Graphics : Beyond-photorealistic techniques for artistic expression Data-driven Graphics : Leveraging large datasets for novel rendering and modeling approaches His recent work emphasizes neural rendering , differentiable graphics , and X-ray tomography , with applications in 3D reconstruction , NeRF manipulation , and holographic imaging . Notable scientific achievements include the Eurographics Young Researcher Award 2014 and Eurographics Thesis Award 2011 . He has advised multiple PhD students including Philipp Henzler (EG PhD Award 2024) and Thomas Leimkühler (Otto Hahn Medal 2019), while actively contributing to conference leadership as co-chair for EGSR 2024 and Pacific Graphics 2024 . His team collaborates on X-ray reconstruction with Pablo Villanueva-Perez and works on 3D perception with Anthony Steed.

Oliver Deussenمشاهده پروفایل

استاد

• Visualization
• Computer Graphics
• Digitalization Processes
• +۴ مورد دیگر

Oliver Deussen is a Professor of Visual Computing at the University of Konstanz, recognized by the German Informatics Society (GSI) as a Fellow for his contributions to computer science. His research focuses on visualization, robotics, and environmental modeling, particularly in plant and landscape representation. He has pioneered methods in image manipulation and robotic painting, emphasizing digitalization's societal impacts. His work spans computational biology (e.g., schooling fish behavior) and AI-driven creative technologies. Research Interests: Visualization techniques, swarm behavior analysis, robotic creativity, and interdisciplinary applications of computer science. He explores how computational methods can model natural systems and enhance human-machine interaction. Awards: Fellow of the German Informatics Society (GSI) His research often bridges theory and practice, with contributions to SLAM frameworks, style transfer algorithms, and uncertainty visualization tools. Collaborations in robotics and biology reflect his commitment to applied computational research.

Irwin Youseptمشاهده پروفایل

استاد

• Electromagnetics
• Numerical Analysis
• Optimization
• +۳ مورد دیگر

Prof. Dr. Irwin Yousept is a Full Professor of Mathematics at Universität Duisburg-Essen, leading the research group AG Optimal Control of Partial Differential Equations. His work focuses on the mathematical analysis and numerical solutions of electromagnetic problems, particularly in superconductivity and inverse problems. He holds a PhD from TU Berlin (2008) and has held academic positions at TU Darmstadt and TU Berlin. His research includes PDE-constrained optimization, numerical analysis, and applications in high-temperature superconductivity and electromagnetic shielding. Affiliations: Universität Duisburg-Essen, Fakultät für Mathematik Education: Diplom (2005), PhD (2008) in Mathematics from TU Berlin Research interests span Maxwell's equations, numerical methods for PDEs, and optimal control, with applications in superconductivity, electromagnetic shielding, and induction heating. He has authored over 40 publications and received awards including the Richard-von-Mises-Preis GAMM (2014). Current grants include DFG-funded projects on inverse problems and superconductivity.

• Optimization and Optimal Control
• Partial Differential Equations
• Inverse Problems
• +۹ مورد دیگر

Prof. Karl Kunisch is the Scientific Director at RICAM (Johann Radon Institute for Computational and Applied Mathematics) and a Full Professor of Mathematics at the University of Graz, Austria. He has held academic positions worldwide, including visiting roles at Brown University, INRIA, and Technical University Berlin. His research focuses on Optimization and Optimal Control, Partial Differential Equations (PDEs), Inverse Problems, and their applications in mathematical imaging, medicine, and computational science. Education: 1975: Diploma Degree, Technical University of Graz, Austria 1975: Master Degree, Northwestern University, Evanston, Illinois, USA 1978: Ph.D. Degree, Technical University of Graz 1980: Habilitation, Technical University of Graz Research Interests: Prof. Kunisch’s work spans theoretical and applied aspects of optimal control, including stabilization of PDEs, infinite horizon control problems, and feedback design. He explores numerical methods for PDE-constrained optimization and their applications in medical imaging, cardiac electrophysiology, and machine learning. His projects also address shape optimization and mathematical models for fluid dynamics and quantum systems. Publications Trends: His recent articles emphasize feedback stabilization for nonlinear systems, sparse control approaches, and the intersection of optimal control with machine learning. Key themes include robust algorithms for uncertainty handling, efficient numerical methods for high-dimensional problems, and applications in biomedical engineering. Awards: Pro Scientia-Scholarship (1974–1977) Research Award of Theodor-Körner-Fonds (1979) Fulbright Travel Scholarship (1979/80, 1985) Max Kade Scholarship (1982–83) Japanese Society for the Promotion of Science Fellowship (1990) Christian Doppler Laboratory Fellowship (1992) Advising & Grants: Prof. Kunisch leads the Optimization and Optimal Control research group at RICAM and has directed projects on mathematical data science and inverse problems. His work involves collaborations with institutions globally and has been supported by grants from NASA, the European Union, and national funding bodies. He has advised numerous researchers, though specific student names are not listed here. Labs/Teams: Group Leader of the Group "Optimization and Optimal Control" at RICAM since 2004, contributing to interdisciplinary research in computational mathematics and its applications.

• Optimization and optimal control
• Inverse problems
• Mathematical imaging
• +۵ مورد دیگر

Karl Kunisch is a Professor at the Department of Mathematics and Scientific Computing at the University of Graz and serves as Scientific Director of the Radon Institute of the Austrian Academy of Sciences in Linz. With a distinguished career spanning several decades, he has established himself as a leading researcher in optimization and control theory. Prof. Kunisch completed his PhD and Habilitation at the Technical University of Graz in 1978 and 1980, respectively. His academic journey includes significant positions at Brown University's Lefschetz Center for Dynamical Systems, INRIA Rocquencourt, Universite Paris Dauphine, and he previously served as a professor of numerical mathematics at the Technical University of Berlin. Research Interests: Prof. Kunisch's research focuses on optimization and optimal control, inverse problems and mathematical imaging, numerical analysis and applications, with current emphasis on life sciences applications. His specific areas include Optimal Control of Partial Differential Equations, Nonsmooth Optimization in Function Spaces, and Applications of Optimization and Control in the Life Sciences. His work bridges theoretical mathematics with practical applications across various scientific domains. His recent publications demonstrate a continued focus on advancing the theoretical foundations of optimal control while developing practical numerical methods. Key trends include work on infinite horizon control problems, feedback stabilization techniques, applications to PDE-constrained optimization, and the integration of machine learning approaches with traditional control theory. His research group actively explores connections between theoretical developments and applications in the life sciences. Scientific Recognition: W.T. and Idalia Reid Prize 2021 SIAM Fellow (2017) European Research Council Advanced Grant (2015) Alwin Walther Medaille (2008) SIAM Outstanding Paper Prize (2006) Prof. Kunisch has made substantial contributions to the mathematical community through his editorial work, serving as editor for prestigious journals including SIAM Journal on Control and Optimization, SIAM Journal on Numerical Analysis, and the Journal of the European Mathematical Society. He leads the Research Group on Optimization and Optimal Control at the Johann Radon Institute for Computational and Applied Mathematics (RICAM) and is involved in the ERC-Project OCLOC "From Open to Closed Loop Control".