جست‌وجوی استاد و پژوهشگر

Alexander Dietzمشاهده پروفایل

مدرس

• Geometry and Approximation
• Volumetric Subdivision
• Subdivision Surfaces
• +۴ مورد دیگر

Alexander Dietz is a Lecturer in the Department of Mathematics at Technische Universität Darmstadt. His research focuses on geometry and approximation, with specialized interests in volumetric subdivision, subdivision surfaces, and elliptic PDEs on subdivision surfaces and volumes. He has contributed to isogeometric analysis and geoscience software tools such as standardized Schoeller diagrams. He has presented at conferences including the Rhein-Ruhr-Workshop (2020–2022), the International Conference on Approximation Theory (2023), and the International Geometry Summit (2023). His teaching includes pre-course mathematics for computer scientists and courses on constructive geometry and mathematics for engineering disciplines. Notable achievements include the Higher Education Teaching Certificate (2018–2020), a research stay at USI Lugano (2023), and the 2023 Athene Award for Good Teaching in Mathematics at TU Darmstadt.

Ulrich Reifمشاهده پروفایل

استاد

• Geometric Modeling
• Numerical Analysis
• Approximation Theory
• +۳ مورد دیگر

Ulrich Reif is a Professor in the Department of Mathematics at Technische Universität Darmstadt. His research focuses on geometric modeling, numerical analysis, approximation theory, and computer-aided geometric design. He explores advanced topics such as isogeometric analysis, subdivision algorithms, and spline-based methods. Key research interests include the theoretical foundations of geometric modeling, computational methods for solving complex mathematical problems, and applications in engineering and computer graphics. His work addresses challenges in surface approximation, numerical stability, and algorithm development for geometric problems. Recent publications highlight contributions to Sobolev regularity analysis, subdivision surface techniques, and the application of deep learning in regression tasks on manifolds. His work often bridges pure mathematics and computational engineering, emphasizing practical implementations and theoretical rigor. No scientific awards or grants are explicitly listed in the provided materials. His academic contributions span over three decades, with a focus on advancing numerical methods and geometric modeling theories.

• Machine Learning
• Physics-Informed Neural Networks
• Computational Fluid Dynamics
• +۱۲ مورد دیگر

Dr. Michael Rom is a researcher at the Institute for Geometry and Practical Mathematics (IGPM), part of the Faculty of Mathematics, Computer Science, and Natural Sciences at RWTH Aachen University, Germany. He is actively engaged in applied mathematics and computational engineering, with a strong focus on fluid dynamics, tribology, and machine learning applications in industrial processes. Research Interests: Physics-Informed Neural Networks Transpiration Cooling and Porous Media Flow Hydrodynamic Lubrication and Cavitation Modeling Reduced Basis and Homogenization Methods Grid Generation and B-Spline Surfaces Grinding Wheel and Surface Modeling His recent publications (2021–2025) show a clear trend toward integrating deep learning and data-driven methods into classical engineering problems, particularly in manufacturing, aerospace thermal protection, and tribological systems. He frequently collaborates with experts in mechanical engineering and materials science, bridging disciplines to solve complex multiphysics problems. Scientific Awards: No awards mentioned in the provided text. Dr. Rom has supervised or co-supervised several students, as evidenced by co-authored works with individuals like M. Schultz, F. Brumand-Poor, and V. König. He has also contributed to teaching at RWTH Aachen, offering courses in numerical computation and finite element methods. His research is supported by collaborations with industrial and academic partners, particularly in digital production and thermal spray technologies. Laboratories and Research Teams: Institute for Geometry and Practical Mathematics (IGPM), RWTH Aachen Collaboration with the Chair of Production Metrology and Quality Management (F. Klocke) Part of interdisciplinary projects such as Internet of Production and Monetization of Technical Data

Eva Darulovaمشاهده پروفایل

دانشیار

• Programming Languages
• Software Verification
• Program Synthesis
• +۳ مورد دیگر

Eva Darulova is an Associate Professor at the Department of Information Technology, Uppsala University, and Adjunct Faculty at Max Planck Institute for Software Systems (MPI-SWS). Previously held tenure-track faculty at MPI-SWS and completed her PhD at École Polytechnique Fédérale de Lausanne (EPFL) under Viktor Kuncak. Current research: Applications in numerical/embedded domains, program synthesis, software verification, approximate computing Key projects: Blossom (fuzzing), Lassie (HOL4 tactics), Pine (floating-point loops), LTLTalk (robot instruction), Incarnate (3D printing), Icing (compiler semantics), Flipper (NLP interface), FloVer (error checking), Daisy (accuracy analysis), Rosa (real compiler) Teaching: Program Design (2021/22), Program Synthesis (2021), Program Analysis (multiple years), Advanced Program Analysis (2019), Static Program Analysis (2017), Approximate Computing seminar (2016) Service: Artifact evaluation chair (ASPLOS'22), PC member (ECOOP'22, ESEC/FSE'22, EMSOFT'21, PLDI'21) Research Trends: Focus on numerical computing verification, approximate computing frameworks, and program synthesis techniques. Publications span TACAS, EMSOFT, ISSTA, POPL, CAV, FMCAD, TOPLAS, with emphasis on floating-point error analysis, mixed-precision optimization, and compiler verification. Scientific Recognition: Nominated for EAPLS best paper award (TACAS'21). Co-advisor for Anastasiia Izycheva and mentor for multiple MSc/BSc students including Mustafa Hafidi, Joachim Bard, Nikita Zyuzin, Youcef Merah, Safya Alzayat, Anastasiia Izycheva. Collaborations: Works with researchers at EPFL, MPI-SWS, University of Saarland, University of Washington, and Saarbrücken/Kaiserslautern institutions.

Chris Mundyمشاهده پروفایل

پژوهشگر ارشد

• Electrolytes
• Solvation Theory
• Interfacial Systems
• +۴ مورد دیگر

Chris Mundy is a Lab Fellow and Physicist at Pacific Northwest National Laboratory (PNNL), specializing in theoretical and computational approaches to complex interfacial systems. His research integrates statistical mechanics and molecular simulations to address fundamental challenges in electrolyte behavior, solvation phenomena, and energy-related materials science under the Department of Energy's Basic Energy Sciences portfolio. His educational background includes a PhD in Chemistry from the University of California, Berkeley (1992) and a BS in Chemistry from Montana State University (1988). Mundy has held significant leadership roles including Chair of the Gordon Research Conference on 'Chemistry and Physics of Liquids' (2025), Chair of the Theoretical Chemistry Subdivision of the American Chemical Society (2022), and Vice Chair (2020-2021). Mundy's research focuses on bridging molecular-scale phenomena to macroscopic outcomes in electrolytes and interfacial systems. His work spans computational modeling of ion hydration, solvation dynamics, and nanoscale assembly processes relevant to energy storage and environmental systems. Recent publications demonstrate strong emphasis on advanced simulation techniques applied to battery electrolytes, biomimetic materials, and aqueous interfaces. His 15 most recent publications reveal consistent focus on computational chemistry methods applied to interfacial phenomena, with growing integration of machine learning and advanced spectroscopy techniques. Key themes include ion-specific effects at interfaces, solvation structure characterization, and predictive modeling of electrolyte behavior across concentration regimes. American Physical Society Fellow (2014) Mundy actively contributes to professional service through leadership in Gordon Research Conferences and ACS subdivisions. His work at PNNL connects fundamental theoretical chemistry to Department of Energy mission areas including energy storage, environmental remediation, and materials science. Current research leverages high-performance computing resources to develop predictive frameworks for complex fluid systems. As a senior researcher at PNNL, Mundy collaborates extensively across national laboratory teams and academic institutions, focusing on theoretical development that informs experimental design in interfacial science and electrochemistry. His group utilizes advanced molecular simulation techniques to probe systems ranging from battery electrolytes to biological interfaces.

• Computer Aided Geometric Design
• Subdivision Methods
• Geometric Modeling
• +۱ مورد دیگر

Prof. Dr. Hartmut Prautzsch serves as Professor of Applied Geometry and Computer Graphics at Karlsruhe Institute of Technology (KIT), where he has held a faculty position since 1990. He concurrently serves on the board of KIT's Institute for Scientific Computing and Mathematical Modelling and acts as co-editor-in-chief of the journal Computer Aided Geometric Design since 2002. His academic foundation includes Mathematics and Computer Science studies at TU Braunschweig (1978-1983) and a 1984 doctorate under W. Boehm. Prior appointments comprised assistant professorship at Rensselaer Polytechnic Institute and IBM Research Lab postdoctoral fellowship. Prof. Prautzsch's research centers on Computer Aided Geometric Design with pioneering contributions to subdivision methods analysis. His work bridges theoretical mathematics and practical applications in geometric modeling, influencing both academic research and industrial CAD systems. Key interests include curve/surface representations, refinement algorithms, and computer graphics foundations. He has mentored several PhD students including professors Leif Kobbelt, Georg Umlauf, and Lars Linsen. His career demonstrates sustained impact through editorial leadership, institutional governance, and fundamental algorithmic contributions that remain relevant in modern geometric processing pipelines. The Applied Geometry Group he leads operates within KIT's mathematical modeling ecosystem, focusing on advancing geometric computation techniques while maintaining connections to real-world design and manufacturing applications.