جستجوی استاد راهنمای دانشگاهی

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

Professor Ekkehard Sachs is affiliated with the Department of Mathematics at the University of Trier . His research focuses on optimization, numerical analysis, control theory, and their applications in fields such as partial differential equations (PDEs), mathematical finance, and engineering. He has made significant contributions to PDE-constrained optimization, Riccati feedback control, and reduced-order modeling techniques. His work spans theoretical developments and computational methods, with a strong emphasis on interdisciplinary applications. Notable areas include the analysis of non-monotone line search algorithms, the study of Ramsey models in economics, and the numerical solution of complex systems such as integro-differential equations. Sachs has also contributed to the calibration of financial market models and the design of efficient numerical algorithms for optimal control problems. His publications highlight advancements in optimization theory, numerical methods for PDEs, and computational techniques for high-dimensional problems. While no specific scientific awards or grants are explicitly mentioned, his extensive publication record reflects a prolific and impactful academic career. His involvement in organizing international conferences and editing proceedings underscores his influence in the optimization community.

Rajkamal Kesharwaniمشاهده پروفایل

استادیار

• Supply Chain Management
• Business Analytics
• Sustainability and Environmental Impact
• +۳ مورد دیگر

Rajkamal Kesharwani is an Assistant Professor of Business Analytics at the Walker College of Business, Mercyhurst University. His academic journey includes a B.E. in Mechanical Engineering from the University of Mumbai, an M.S. in Industrial and Systems Engineering from Virginia Tech, and a Ph.D. in Systems Engineering from Missouri University of Science and Technology. He brings industry experience from the energy sector, focusing on engineering design and manufacturing. His research interests span supply chain sustainability, biofuel production economics, organizational behavior, and innovative educational strategies. He has explored topics like workplace bullying’s impact on bystanders, renewable energy supply chains, and flipped learning effectiveness in STEM education. His publications reflect a focus on bridging theoretical sustainability frameworks with practical supply chain design, while also addressing pandemic-era educational challenges and gender dynamics in sustainable behavior adoption. He has contributed to advancing biofuel production methodologies and optimizing quality control systems using AI. Rajkamal holds no listed scientific awards but has actively engaged in interdisciplinary research across engineering, business, and education domains. His work emphasizes real-world applications of analytical frameworks in both corporate and academic settings.

Anton Freundمشاهده پروفایل

استاد

• Mathematical Logic
• Proof Theory
• Reverse Mathematics
• +۳ مورد دیگر

Prof. Dr. Anton Freund is a tenure-track professor and Emmy Noether group leader at the University of Würzburg’s Department of Mathematics (Mathematical Logic). He holds the Chair of Mathematics III and specializes in proof theory, reverse mathematics, and ordinal analysis. His research focuses on well-ordering principles, dilators, and the logical strength of combinatorial principles. Education & Career: Bachelor/Master (2008–2014): LMU Munich, with a gap year in Paris PhD (2014–2018): University of Leeds under Michael Rathjen Postdoc (2018–2021): TU Darmstadt with Ulrich Kohlenbach Emmy Noether Group Leader (2021–2023): TU Darmstadt Current: Tenure-track professor & Emmy Noether Group Leader at Würzburg Research Interests: Freund investigates foundational aspects of mathematics via proof-theoretic methods. Key themes include ordinal analysis of subsystems of arithmetic, combinatorial principles (e.g., Kruskal’s theorem, Higman’s lemma), and the interplay between computability and set-theoretic reflection principles. His work bridges constructive mathematics and impredicative systems, often employing dilators and ordinal notation systems. Publications: Freund’s recent work explores topics like provable dilators, Bachmann-Howard fixed points, and the logical strength of minimal bad arrays. These contributions advance understanding of reverse mathematics and computational aspects of proof theory. Awards & Grants: He leads an Emmy Noether Research Group funded by the German Research Foundation (DFG), reflecting his role in advancing foundational mathematical research. Lab & Collaboration: His team includes Alexandra Fick and Davide Manca. Collaborations span institutions like Leeds, Darmstadt, and international journals in mathematical logic.

• Calculus of Variations
• Optimization
• Partial Differential Equations
• +۳ مورد دیگر

Ilaria Fragalà is an Associate Professor at the Department of Mathematics, Politecnico di Milano. Her research focuses on calculus of variations, geometric analysis, and partial differential equations, with applications to optimization problems involving shapes, partitions, and nonlocal perimeters. She has contributed to fundamental results in optimal partitioning, eigenvalue optimization, and the honeycomb conjecture. Education: PhD in Mathematics (2000) with a thesis on elliptic approximations in Finsler geometry, and earlier academic work on functional inequalities and measure theory. Research interests include nonlocal perimeters, spectral geometry, free discontinuity problems, and the interplay between geometry and PDEs. Her recent work addresses optimal convex partitions, robustness of geometric structures, and symmetry properties in variational problems. She has organized conferences such as the Vito Volterra Meeting in Calculus of Variations (2025) and participated in workshops like the 'Matter of Shapes' (2025). Her publications emphasize rigorous analytical methods and geometric insights.

• Differential Equations
• Nonlinear Analysis
• Functional Analysis
• +۴ مورد دیگر

Jorge Rodríguez López is a Professor in the Department of Mathematical Analysis at the University of Santiago de Compostela, Spain. His research focuses on nonlinear analysis, differential equations, and operator theory, with particular emphasis on fixed point theorems and discontinuous systems. He has held a permanent academic position since at least 2021, teaching courses such as Functional Series, Riemann Integration in Several Variables, and Ordinary Differential Equations across multiple bachelor programs including Mathematics, Physics, and Informatics Engineering. His academic activities include tutoring and course coordination for undergraduate programs. Research interests center on theoretical aspects of differential equations, including boundary value problems, existence/uniqueness criteria, and applications of fixed point theory to nonlinear systems. Notable contributions involve hybrid fixed point theorems, Krasnosel’skiĭ-type methods, and analysis of discontinuous operator systems. Publications emphasize innovative applications of functional analysis to problems in mathematical physics and nonlinear dynamics. While no awards are explicitly listed, his extensive publication record indicates sustained research excellence in his field. Current roles involve both teaching foundational mathematical analysis courses and advancing theoretical frameworks for discontinuous differential equations.

Silviu-Iulian NICULESCUمشاهده پروفایل

استاد

• Control Theory
• Time-Delay Systems
• Robust Control
• +۶ مورد دیگر

Silviu-Iulian NICULESCU is a Research Director (Senior Researcher) at the CNRS and a member of the Inria 'Disco' team at CentraleSupélec. He holds affiliations with the Laboratoire de Signaux et Systèmes (L2S) and is a leading expert in control theory and time-delay systems. His academic journey includes degrees from the Polytechnical Institute of Bucharest, Institut National Polytechnique de Grenoble (INPG), and Université de Technologie de Compiègne. He has held key roles, including heading L2S from 2010–2019 and co-founding the Inria DISCO team. His research focuses on delay systems, robust control, and stability analysis, with applications in engineering and biology. Research Interests: His work emphasizes time-delay systems, pole placement methods, control design, and stability optimization. He has contributed extensively to the MID (Multiplicity-Induced Dominancy) approach and software tools like P3δ. Awards and Recognition: IEEE Fellow (2018), CNRS Silver and Bronze Medals, Best Paper Awards, and a Doctor Honoris Causa from University of Craiova (2016). He has organized major conferences and edited influential books and journals. Key Contributions: Over 500 publications, including books on delay systems and control theory. He leads international projects and has developed methodologies for stabilizing systems with delays, impacting fields like robotics, drilling, and networked control.

• Calculus of Variations
• Optimal Transport
• Density Functional Theory
• +۳ مورد دیگر

Guy Bouchitté is a Full Professor at Université du Sud Toulon-Var. His research focuses on Calculus of Variations, Optimal Transport, Density Functional Theory, and Homogenization. He has contributed to theoretical advancements in optimal design, shape optimization, and multi-marginal transport problems. His work bridges mathematical analysis with applications in quantum chemistry, structural mechanics, and material science. Key research areas include asymptotic analysis of variational problems, optimal transport with non-linear costs, and the interplay between geometry and functional inequalities. Recent studies address dissociation limits in Density Functional Theory and quantization effects in many-body systems. He has organized seminars on Geometric Measure Theory and Frontiers of the Calculus of Variations. His contributions span over 35 publications, including works on Monge-Kantorovich duality, compliance sensitivity, and spectral optimization for Schrödinger operators. Professional activities include participation in workshops such as 'Variational Challenges in Materials Science' and 'Calculus of Variations and Applications'.

• Geometric Measure Theory
• Calculus of Variations
• Differential Geometry
• +۳ مورد دیگر

Ulrich Menne is affiliated with the Department of Mathematics at National Taiwan Normal University . His research focuses on geometric measure theory, calculus of variations, and differential geometry, with contributions to topics such as rectifiability, isoperimetric inequalities, and functional inequalities in geometric contexts. He has organized and participated in several academic events, including the NCTS International Geometric Measure Theory Seminar (2020-2021), the Federer Birthday conference (2020), and workshops on geometric measure theory and real analysis. His work bridges theoretical analysis with geometric applications, emphasizing foundational questions in metric spaces and submanifolds. Key contributions include studies on integral chains, second-order rectifiable stratifications, and novel inequalities for diffused surfaces. Menne’s research reflects a deep engagement with both abstract geometric structures and their analytical implications.

• Causal Discovery
• Machine Learning
• Educational Software
• +۳ مورد دیگر

Richard Scheines is a Professor and Dean at Carnegie Mellon University, with affiliations in the Machine Learning Department and the Human-Computer Interaction Institute. His research focuses on causal discovery, particularly through the TETRAD project, which develops algorithms for inferring causal structures from statistical data. He also explores educational technologies, including intelligent tutoring systems and virtual labs for causal reasoning. Scheines’ work bridges computer science, philosophy, and education, emphasizing practical applications of causal inference in biomedical research and policy analysis. His research interests include causal modeling, machine learning, and the development of interactive educational software. Scheines has collaborated extensively on projects like the CSR online courseware and the Center for Causal Discovery. His contributions span theoretical advancements in causal inference, empirical studies on learning strategies, and interdisciplinary applications in healthcare and public policy. Publications highlight his work on measurement error, multidimensional data analysis, and the integration of AI into education. He has also engaged in policy-related research, such as evaluating environmental risk assessment frameworks. Scheines’ academic leadership and innovative approaches to causal discovery and educational technology have positioned him as a key figure in computational and applied philosophy.

Oliver Dunbarمشاهده پروفایل

پژوهشگر ارشد

• Applied Mathematics
• Numerical Analysis
• Partial Differential Equations
• +۳ مورد دیگر

Oliver Dunbar is a Research Fellow at the University of Warwick, affiliated with the MASDOC Centre for Doctoral Training. His research focuses on deterministic and probabilistic solutions to PDE-based inverse problems, including the inverse Eikonal equation and its applications in geophysics. He specializes in diffuse interface modeling of multiphase fluids with surfactants, numerical analysis of Cahn-Hilliard Navier-Stokes systems, and computational methods using the DUNE-FEM toolbox. Education: MMath from the University of Bath, MSc in Mathematics and Statistics (MASDOC, Warwick), and PhD in Mathematics. His PhD research addressed phase-field models for multiphase fluid dynamics, demonstrating second-order accuracy in numerical schemes. He has presented at conferences such as the Warwick Postgraduate Seminar, Micro and Nanoflows Workshop, and SIAM National Student Chapter conferences. His talks often explore surfactant dynamics and phase-field modeling. Oliver has taught Analysis modules and supervised undergraduate mathematics students. He served as treasurer of the SIAM Warwick student chapter, organizing events on statistics, machine learning, and applied mathematics. Research contributions include developing coupled surfactant-Cahn-Hilliard-Navier-Stokes systems and analyzing numerical stability in variable density flows. His work bridges theoretical analysis and computational implementation, with videos of simulations available on his YouTube channel.

Merih Kucuklerمشاهده پروفایل

دانشیار

• Structural Engineering
• Steel Structures
• Fire Behavior and Design
• +۴ مورد دیگر

Dr. Merih Kucukler is an Associate Professor in Civil Engineering at the University of Warwick's School of Engineering. His research focuses on structural stability, steel structures, and fire behavior, contributing to British and European design standards such as Eurocode 3. He leads the EPSRC-funded project 'Behaviour and Design of Stainless Steel Structures in Fire,' which has developed novel fire design methods for stainless steel. His work emphasizes sustainable and resilient steel infrastructure through advanced numerical modeling and machine learning applications. Research Interests: Structural stability, steel-concrete composites, fire design of steel structures, finite element analysis, laboratory testing, and design method development. His group, the Sustainable and Resilient Steel Structures (SRSS) Research Group, addresses steel behavior under extreme conditions and machine-learning-based design tools. Grants: EPSRC New Investigator Award (EP/V034405/1), £403k (2021-2025). Collaborations include major industrial stakeholders and academic partnerships. He serves on CEN/TC250 Subcommittee 3 and ECCS Technical Committee 8. Awards: SSRC Vinnakota Award (2014). Editorial Board Membership: Structures (Elsevier). PhD Supervision: Actively mentoring students and welcoming candidates interested in steel structure research. Office Hours: Fridays 10 AM–12 PM (term time). Labs/Teams: Leads the SRSS Research Group, focusing on advanced analysis and machine learning for steel structure design.

Pietro Lioمشاهده پروفایل

استاد

• Artificial Intelligence
• Computational Biology
• Graph Neural Networks
• +۶ مورد دیگر

Pietro Liò is a Full Professor in the Department of Computer Science and Technology at the University of Cambridge. He is a member of the Artificial Intelligence group, Cambridge Centre for AI in Medicine, Clare Hall College, ELLIS, Academia Europaea, and VPH-UK. Doctorate in Complex Systems and Non-Linear Dynamics (University of Florence) Doctorate in Theoretical Genetics (University of Pavia) Master of Arts (University of Cambridge) His research focuses on Artificial Intelligence and Computational Biology for disease complexity modeling and precision medicine, particularly using Graph Neural Networks for multi-omics integration, neural signal analysis (fMRI/NMR), and biomedical methodology development across scales from molecular devices to population health. Recent work emphasizes data integration (genomics, radiomics, EHR) and nonlinear disease trajectory modeling with applications in diabetes, Parkinson's, and the COVID-19 pandemic through machine learning models for symptom detection, ICU forecasting, and social contagion analysis. 2020 AIAI Best Student Paper 2018 BITS Bioinformatics Italian Society Award 2016 BYRA First Prize & MCED Second Prize 2013 Lagrange Fellowship 2012 Best Paper (Turing 100) 2011 FET Conference 3rd Prize He teaches Graph Neural Networks (MPhil) and Bioinformatics Algorithms (undergraduate). His grants include EU GO-DS21, PROPAG-AGEING, MIMOmics, MISSION-T2D, MRC CLIMB, and NERC DREAM projects.

• Numerical Linear Algebra
• Differential-Algebraic Equations
• Control Theory
• +۳ مورد دیگر

Prof. Tatjana Stykel is a Professor of Computational Mathematics at the University of Augsburg, affiliated with the Faculty of Mathematics, Natural Sciences, and Materials Engineering. She holds positions in the Institute of Mathematics and leads the Computational Mathematics research group. Her academic journey includes a PhD from Technische Universität Berlin (2002) and a Habilitation (2009), both in numerical mathematics. Prior to her current role, she led a junior research group at TU Berlin’s MATHEON Research Center and held visiting professorships at TU Berlin and Humboldt-Universität zu Berlin. Stykel’s research focuses on Numerical Linear Algebra (e.g., generalized eigenvalue problems, matrix equations), Differential-Algebraic Equations (numerical methods and stability), and Control Theory (descriptor systems, model reduction). She has pioneered energy-adaptive optimization methods and Riemannian geometry techniques for complex systems, including applications in quantum chemistry and electromagnetism. Her awards include the Richard von Mises Prize (2007), Leslie Fox Prize (2003), and multiple fellowships from the Pacific Institute for the Mathematical Sciences and Soros programs. She has led major projects like the EU-funded EU-MORNET (2014–2018) and contributed to BMBF networks in model reduction for coupled systems. Stykel teaches advanced numerical methods, including courses on differential equations, optimization, and model reduction. Her work emphasizes interdisciplinary collaboration, with partnerships in robotics, semiconductor technology, and fluid dynamics. She advises several students, including alumni who have become prominent in applied mathematics and engineering.

Olivier Fercoqمشاهده پروفایل

استاد

• Optimization Algorithms
• Primal-Dual Methods
• Coordinate Descent Methods
• +۴ مورد دیگر

Olivier Fercoq is a Professor at Télécom Paris, affiliated with the Laboratoire Traitement et Communication de l’Information (LTCI). He holds a PhD in Applied Mathematics from École Polytechnique (2012) and has held academic roles including Assistant Professor (2015–2021) and Postdoctoral positions at Télécom ParisTech and the University of Edinburgh. Education: PhD in Applied Mathematics, École Polytechnique (2009–2012) Master of Research in Optimization, Paris 6 University (2008–2009) Engineer's Degree in Mathematical Engineering, ENSTA-ParisTech (2006–2009) Research Interests: First-order optimization algorithms, primal-dual methods, and coordinate descent Applications in machine learning, web ranking, and chemotherapy optimization Key Achievements: Second Prize of the IMA Leslie Fox Prize (2015) PhD Thesis Award from the Gaspard Monge Programme (2013) Developed software tools like APPROX and contributions to Scikit-learn Teaching: Advanced courses on optimization, machine learning, and signal processing at Télécom Paris and IPP Master’s programs

Ludmila Prikazchikovaمشاهده پروفایل

مدرس

• Wave Propagation
• Asymptotic Methods
• Non-local Elasticity
• +۲ مورد دیگر

Ludmila Prikazchikova is a Lecturer in Applied Mathematics at Keele University's School of Computer Science and Mathematics. She holds an MSc in Applied Mathematics from Saratov State University and a PhD from the University of Salford focused on dispersion of elastic waves in pre-stressed compressible layers. Her research explores wave propagation phenomena, asymptotic methods for elastic structures, and non-local elasticity theory, with applications in nano-material modeling and composite structures. She develops mathematical frameworks for analyzing dynamic behavior of inhomogeneous materials and fluid-structure interactions. Publications primarily focus on elastic wave dynamics in complex material systems, featuring advanced asymptotic techniques and non-local continuum formulations. Recent articles analyze vibration behavior in layered composites, seismic metasurfaces, and fluid-loaded structures. Teaching: Dynamics and Differential Equations courses Administrative: Deputy Director of Recruitment for Mathematics