جست‌وجوی استاد و پژوهشگر

Steven Dufourمشاهده پروفایل

استاد

• Numerical modeling
• Finite element methods
• Multiphase systems
• +۴ مورد دیگر

Professor Steven Dufour is a Full Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal. With a career spanning over two decades since completing his Ph.D. in 1999, he has established himself as an expert in numerical modeling, particularly in the areas of finite element methods and multiphase systems. His academic journey began with B.Sc. and M.Sc. degrees from the University of Montreal, followed by a Ph.D. from Polytechnique Montréal. Professor Dufour's research focuses on the numerical modeling of free surface flows in industrial processes, with expertise recognized by NSERC in modeling, simulation, and finite element methods (topic 2107) and polyphase systems (topic 2202). Professor Dufour's research interests span computational fluid dynamics, finite element analysis, and more recently, the integration of machine learning techniques with traditional numerical methods. His work has evolved from foundational research in adaptive finite element methods for multiphase flows to cutting-edge applications combining physics-informed neural networks with computational fluid dynamics, electromagnetic field analysis, and millimeter-wave sensing. His publication record demonstrates consistent research productivity, with 23 publications documented across computational mathematics and engineering applications. The most recent publications from 2024 show his adaptation to emerging methodologies in computational science, particularly the application of physics-informed neural networks to solve complex fluid dynamics problems. NSERC Expertise: Modeling, simulation and finite element methods (2107) NSERC Expertise: Polyphase Systems (2202) Supervised 7 doctoral students to completion Supervised 13 master's students to completion Professor Dufour has maintained active research funding and supervision throughout his career, mentoring students in both theoretical numerical methods and practical engineering applications. His collaborative work spans multiple engineering disciplines, connecting computational mathematics with real-world industrial and biomedical problems.

Serge Prudhommeمشاهده پروفایل

استاد

• Scientific Computing
• Finite Element Method
• Error Estimation
• +۷ مورد دیگر

Serge Prudhomme is a Full Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal. With a background including a Dipl. Eng. from École Centrale de Lille, an M.Sc. from the University of Virginia, and a Ph.D. from UT Austin, he has established himself as a leading researcher in computational mathematics and mechanics. His primary research interests span scientific computing, finite element methods, error estimation and adaptive methods, multi-scale modeling, verification and validation of numerical calculations, uncertainty quantification, and model reduction. Professor Prudhomme's work demonstrates a consistent focus on developing mathematically rigorous computational frameworks with practical engineering applications. His recent publications show an expanding interest in integrating machine learning techniques with traditional numerical methods. Analysis of his recent publications reveals a strong trend toward interdisciplinary research that bridges computational mathematics with mechanics and increasingly machine learning. His work on peridynamics, proper generalized decomposition, and neural network applications to scientific computing represents cutting-edge developments in computational methods. The publications demonstrate a consistent focus on improving the accuracy, efficiency, and reliability of computational models. Professor Prudhomme has successfully supervised 10 graduate students to completion (4 doctoral theses and 6 master's theses), indicating a strong commitment to student mentorship. His supervision record spans topics including wave equation approximations, goal-oriented calibration, contact detection for ellipsoids, and PGD reduced-order modeling. His research is supported by active collaborations with institutions worldwide, as evidenced by his co-authorship patterns and conference participation across North America and Europe. The breadth of his work, from fundamental mathematical developments to practical engineering applications, positions him as a significant contributor to the field of computational science and engineering.

Eran Rabaniمشاهده پروفایل

استاد

• Theoretical and computational chemistry
• Nanomaterials
• Quantum dots
• +۷ مورد دیگر

Prof. Eran Rabani is a distinguished researcher and professor holding dual appointments at Tel Aviv University's School of Chemistry and the University of California, Berkeley's Department of Chemistry. At UC Berkeley, he holds the prestigious Glenn T. Seaborg Chair in Physical Chemistry and serves as a Faculty Scientist at Lawrence Berkeley National Laboratory. His research bridges theoretical chemistry, computational physics, and nanomaterials science, with significant contributions to understanding quantum phenomena at the nanoscale. Prof. Rabani earned his Ph.D. in Theoretical Chemistry from The Hebrew University in 1996, followed by postdoctoral research at Columbia University. His academic career progressed from Senior Lecturer to full Professor at Tel Aviv University, where he has maintained a continuous appointment since 1993. His educational background includes a summa cum laude B.Sc. from the Special Program "Amirim" at The Hebrew University. Rabani's research program centers on three interconnected pillars: Optoelectronic Properties of Nanomaterials , where his group develops computational models to describe exciton fine structure and phonon interactions in nanocrystals; Quasiparticle Dynamics , investigating electron transfer processes in nanoscale systems; and Stochastic Electronic Structure Methods , pioneering computational approaches that dramatically reduce the complexity of quantum simulations. His work combines theoretical innovation with practical applications in renewable energy, sensing technologies, and quantum information processing. Analysis of Rabani's recent publications reveals a strong emphasis on quantum confinement effects, exciton dynamics, and the development of stochastic computational methods that enable simulations of previously intractable systems. His research demonstrates increasing interdisciplinary collaboration, particularly with experimental groups working on quantum dots, perovskites, and other nanomaterials, with a clear trajectory toward solving real-world problems in energy conversion and quantum technologies. Prof. Rabani's contributions have been recognized with numerous prestigious awards: International Association of Advanced Materials Fellow (2023) Humboldt Research Award (2022) Vebleo Fellow for Prominence and Leadership in Science (2021) Glenn T. Seaborg Chair in Physical Chemistry (2017) Baker Symposium Speaker at Cornell University (2016) Kavli Frontiers of Science Alumni (2015) Marko & Lucie Chaoul Chair for Theoretical and Computational Nanoscience (2013) His research program is supported by substantial funding from major agencies including the National Science Foundation, Department of Energy, and Israel Science Foundation. Current grants (2021-2025) total over $2.5 million, focusing on semiconductor nanowires, computational materials science, and optoelectronic materials. As Director of The Sackler Center for Computational Molecular and Materials Science at Tel Aviv University, he leads a vibrant research group that bridges theoretical innovation with experimental validation. Prof. Rabani directs The Sackler Center for Computational Molecular and Materials Science at Tel Aviv University and has served in various administrative roles including Vice President for Research and Development. His research group maintains strong collaborations with experimentalists worldwide, creating an intellectual community focused on advancing fundamental understanding of nanoscale phenomena while exploring practical applications in energy, sensing, and quantum technologies.

• Numerical Analysis
• Scientific Computing
• Finite Difference Methods
• +۴ مورد دیگر

Sofia Eriksson is an Associate Professor in the Department of Mathematics within the Faculty of Technology at Linnaeus University. She specializes in numerical analysis and scientific computing, with a primary focus on developing finite difference methods for solving time-dependent partial differential equations. Her research has significant applications in fluid dynamics and aerodynamics. Dr. Eriksson's research interests span numerical analysis, scientific computing, finite difference methods, partial differential equations, and computational mathematics. She leads or participates in two major research groups: Computational Mathematics for Predictive Digital Twins (PreDiTwin) and Scientific Computing and Partial Differential Equations. Her work emphasizes developing stable numerical methods with proper boundary and interface treatments. Her publication record shows consistent output since 2007, with 15 recent publications spanning journals like Journal of Computational Physics, SIAM Journal on Numerical Analysis, and Foundations of Computational Mathematics. Her research shows a clear progression from foundational work on finite difference methods to more specialized applications in fluid dynamics and aerodynamics. The publications demonstrate expertise in developing stable numerical schemes, particularly for time-dependent problems with complex boundary conditions. Dr. Eriksson teaches courses in Numerical Methods, Linear Algebra, and Calculus, contributing to both undergraduate and graduate education in mathematics and computational science. Her teaching reflects her research expertise, providing students with practical knowledge of numerical methods applicable to real-world scientific and engineering problems.

• Numerical Analysis
• Scientific Computing
• Partial Differential Equations
• +۳ مورد دیگر

Herbert Egger is a Professor of Numerical Analysis and Scientific Computing at Johannes Kepler University (JKU) Linz and heads the Institute of Numerical Mathematics. He is also a Group Leader at RICAM (Johann Radon Institute for Computational and Applied Mathematics) and Scientific Director at the Austrian Academy of Sciences. His research focuses on advanced numerical methods for partial differential equations, including structure-preserving discretizations, inverse problems, and computational electromagnetics. Current projects include SFB F90-N (CREATOR) for electric machine co-simulation, SPP 2256 for phase-field modeling in additive manufacturing, and TRR 146 on multiscale soft matter systems. Key research areas: mixed/hybrid finite element methods, energy-based modeling, model order reduction, radiative transfer, and inverse problem stabilization. His recent work emphasizes nonlinear magnetostatics, phase separation models, and efficient solvers for time-dependent systems. Egger collaborates internationally with institutions like TU Eindhoven and TU Darmstadt.

• Numerical Methods
• Finite Element Analysis
• Mathematical Modeling
• +۵ مورد دیگر

Милена Радославова Рачева serves as an Associate Professor at the Department of Mathematics, Informatics and Natural Sciences within the Economic Faculty of Technical University - Gabrovo. Holding a Doctor of Sciences degree in Mathematical Sciences, she maintains an active research profile with consistent publications through 2024. Her institutional affiliation demonstrates long-term commitment to the university's academic mission. Research Interests: Dr. Racheva specializes in advanced numerical methods with particular focus on finite element analysis, eigenvalue problems, and Fourier transforms. Her work bridges theoretical mathematics with practical engineering applications, especially in computational modeling for biomedical and ecological systems. Recent publications indicate expanding interests in data approximation techniques and educational technology solutions for remote learning environments. Publication Trends: Analysis of her 15 most recent publications (2021-2024) reveals three dominant research streams: 1) Core mathematical research on eigenvalue approximation and finite element methods (60% of output), 2) Applied mathematical modeling in engineering and energy systems (25%), and 3) Socio-economic analyses of entrepreneurship and investment climates (15%). Her collaborative work with A.B. Andreev represents a significant portion of her technical publications, while recent interdisciplinary projects extend into photovoltaic systems and hydroelectric power analysis. Professional Activities: She has led participation in externally funded scientific projects, most notably the 2012 project "Numerical Methods for Coupled Systems and Computer Modeling in Biomedicine and Ecology" where she served as scientific organization partner. Her publication record shows consistent output across international journals (Springer, IEEE) and Bulgarian academic venues, with recent work appearing in Mathematical Modeling journal and UNITECH conference proceedings.

Stephen Boedoمشاهده پروفایل

استاد

• Tribology
• Fluid-film bearing systems
• Elastohydrodynamic lubrication
• +۴ مورد دیگر

Stephen Boedo is a Professor in the Department of Mechanical Engineering at the Rochester Institute of Technology's Kate Gleason College of Engineering. His research focuses on computational methods and design guidelines for dynamically loaded conformal fluid-film bearing systems. Dr. Boedo serves as course coordinator for advanced strength of materials, mechanics of solids, finite elements, and lubrication courses. Dr. Boedo received his BA in Computer Science from the State University of New York at Buffalo, and his MS in Theoretical and Applied Mechanics and PhD in Mechanical Engineering from Cornell University. He has also served as a Visiting Professor at Cornell University. Dr. Boedo's primary research area focuses on the development of new computational methods and design guidelines for dynamically loaded conformal fluid-film bearing systems. He studies the interaction of thin lubricant films with structurally compliant surfaces, including effects of geometric irregularity, lubricant supply, and lubricant cavitation on predicted mechanical system performance. His analytical methods have proven useful for understanding engine and compressor bearings, the nonlinear behavior of fluid-film rotors, and the lubrication of artificial human joints. Experimental and numerical studies pertaining to the tribological characteristics of MEMS bearing systems and spherical bearings for optical polishing applications are also part of his research agenda. Analysis of Dr. Boedo's recent publications reveals a strong focus on mass-conserving approaches to lubrication modeling, squeeze film dynamics, and computational methods for bearing analysis. His work spans traditional mechanical engineering applications like engine bearings while also extending into biomedical applications such as artificial hip joints. The integration of computational methods with practical engineering design appears to be a consistent theme throughout his research career. Editorial Board, IMechE Journal of Engineering Science Former Associate Editor, ASME Journal of Tribology Dr. Boedo teaches several key courses in mechanical engineering including MECE-117 Introduction to Programming for Engineers, MECE-350 Strengths II, MECE-605 Finite Elements, and MECE-785 Mechanics of Solids. As course coordinator, he oversees curriculum development for advanced strength of materials, mechanics of solids, finite elements, and lubrication courses. Dr. Boedo's research involves both theoretical computational work and experimental studies, particularly in the areas of tribology and bearing systems. His patent portfolio includes innovations in artificial hip joint replacement systems and microbearing devices, demonstrating the practical applications of his theoretical work.

Mark Naylorمشاهده پروفایل

دانشیار

• Seismic Monitoring of Bedload Transport in Mountain Rivers
• Statistical Forecasting of Earthquakes and other Hazards
• Earthquake Hazard and Statistical Seismology
• +۸ مورد دیگر

Mark Naylor is a Reader in Computational Geoscience and Hazard Research at the School of GeoSciences, University of Edinburgh, where he also serves as Academic Lead for IT. With over 20 years of experience in Earth sciences since completing his Master's in Physics at Oxford in 2000, he has established a distinguished research career focused on understanding Earth processes through computational methods. His primary affiliations include the University of Edinburgh as his home institution and his role as a Senior Member of the NERC Constructing a Digital Environment Expert Network. Dr. Naylor's research centers on computational approaches to understanding Earth systems, with particular emphasis on seismic monitoring of bedload transport in mountain rivers, statistical forecasting of earthquakes and other hazards, earthquake hazard assessment, mountain belt growth, erosion processes, and foreland basin evolution. His work bridges geoscience, statistics, and computational methods, often employing innovative approaches to analyze complex natural systems. He has made significant contributions to the development of the ETAS.inlabru package for earthquake forecasting and has published extensively on proper scoring rules for evaluating seismic forecasts. His publication record shows a strong trajectory of high-impact research, with recent work focusing on Bayesian approaches to seismicity modeling, earthquake forecast evaluation, and the application of statistical methods to diverse geoscience problems. The trend in his publications demonstrates increasing sophistication in computational methods and growing interdisciplinary collaboration, particularly with statisticians and computer scientists. Senior Member of the NERC Constructing a Digital Environment Expert Network Principal Investigator for multiple significant research projects including EPSRC Studentship, Galleries2Callories, and Dynamic Risks for Cascading Himalayan Hazards Active contributor to the Collaboratory for the Study of Earthquake Predictability (CSEP) As a supervisor, Dr. Naylor currently mentors three PhD students and has successfully guided numerous students to completion of their degrees. His research group, the Edinburgh-Seismicity-Hub, maintains active GitHub repositories with open-source tools for seismicity analysis. He has secured substantial research funding from NERC, EPSRC, and other sources to support his innovative work at the intersection of geoscience and computational statistics. His laboratory work focuses on seismic monitoring applications, particularly the development of low-cost sensor systems for river monitoring and earthquake detection. The group's work represents a unique blend of theoretical statistical development and practical field applications, creating a dynamic research environment that bridges computational theory with real-world geoscience problems.

Michał Baranowskiمشاهده پروفایل

مدرس

• microwave filters
• design optimization
• electronic design automation
• +۳ مورد دیگر

Michał Baranowski serves as an Assistant lecturer at the Department of Microwave and Antenna Engineering within the Faculty of Electronics Telecommunications and Informatics at Gdańsk University of Technology since 2021. He is simultaneously pursuing his PhD at the same institution, demonstrating a strong commitment to both teaching and research in microwave engineering. His research interests focus on advanced microwave component design, particularly in the areas of microwave filters, design optimization techniques, electronic design automation, finite element method applications, computational electromagnetics, and specialized microwave design methodologies. His work bridges theoretical concepts with practical manufacturing approaches, especially regarding additive manufacturing techniques for microwave components. Baranowski's publication record (13 papers from 2020-2025) reveals a clear research trajectory centered on innovative approaches to microwave filter design and waveguide component manufacturing. His most recent work (2024-2025) emphasizes 3D-printed microwave components, shape deformation techniques for resonator design, and methods to improve surface quality of additively manufactured waveguides. This research has direct applications in satellite communications, Earth observation systems, and 5G technology infrastructure. His technical expertise spans computational electromagnetics, optimization algorithms, and advanced manufacturing techniques for high-frequency components, with a particular emphasis on making these technologies more accessible through open platform tools and cost-effective manufacturing approaches. As an active researcher and educator, Baranowski contributes to both the theoretical advancement and practical implementation of microwave engineering solutions, with his work appearing in prestigious journals including IEEE Microwave and Wireless Technology Letters, IEEE Transactions on Microwave Theory and Techniques, and IEEE Access.

José Ramón García Cascalesمشاهده پروفایل

استاد

• Thermodynamics
• Heat Pump Technology
• Refrigeration Engineering
• +۳ مورد دیگر

José Ramón García Cascales is a Professor at the Polytechnic University of Cartagena specializing in thermal engineering and sustainable energy systems. His research focuses on advancing CO 2 -based heat pump technology for domestic and industrial applications, with particular expertise in transcritical cycles and mechanical subcooling systems. His primary research interests include: Thermodynamics of alternative refrigerants Numerical modeling of heat transfer systems Experimental characterization of CO 2 heat pumps Domestic hot water production optimization Sustainable heating and cooling solutions Transient thermal system behavior Analysis of his 15 most recent publications (2021-2025) reveals a consistent research trajectory centered on CO 2 heat pump optimization. Key trends include mechanical subcooling strategies, gas cooler pressure control, and integration with thermal storage systems. His work combines high-fidelity numerical modeling with experimental validation across diverse operating conditions, demonstrating significant contributions to improving energy efficiency in residential and commercial heating applications. No scientific awards or notable grants were explicitly mentioned in the source material. Similarly, information regarding student supervision, laboratory facilities, or collaborative teams was not provided in the available documentation.

Mihhail Berezovskiمشاهده پروفایل

دانشیار

• Data Science
• Industrial Mathematics
• Numerical Methods
• +۷ مورد دیگر

Dr. Mihhail Berezovski is a tenured Associate Professor of Mathematical Sciences and Program Coordinator for the B.S. in Data Science at Embry-Riddle Aeronautical University's College of Arts & Sciences. With over ten years of experience, he has pioneered data science applications and cross-disciplinary engagement strategies that connect academic research with real-world industry problems. His innovative approach provides students with authentic data-enabled research experiences through partnerships with businesses, government agencies, and non-profit organizations. Dr. Berezovski earned his Ph.D. in Applied Mechanics from Tallin Technological University. His academic journey includes positions as a Postdoctoral Scholar at Worcester Polytechnic Institute (2011-2015) and Researcher at the Institute of Cybernetics at TUT, Estonia (2011-2015). Dr. Berezovski's research spans Data Science, Industrial Mathematics, Numerical Methods, and Material Science . He specializes in developing data-enabled solutions for complex problems across diverse domains including aviation, child welfare systems, and material science. His work bridges theoretical mathematics with practical applications, focusing on adaptive algorithms for wave propagation in heterogeneous materials and predictive analytics for real-world systems. He has established a sustainable model where students engage directly with industry-provided problems, creating meaningful research experiences that prepare them for data science careers. His publication record demonstrates a clear evolution from theoretical work in elastic wave propagation toward applied data science projects addressing real-world challenges. Recent publications show increasing focus on interdisciplinary applications in aviation, social services, and media literacy, reflecting his commitment to solving practical problems through mathematical and computational approaches. Dr. Berezovski's contributions to mentoring have been recognized with numerous prestigious awards: 2024 Faculty Mentor Award from the Mathematical, Computing, and Statistical Sciences Division of CUR 2023 ERAU College of Arts & Sciences Award for Undergraduate Student Mentorship 2022 ERAU College of Arts & Sciences Dean's Award for Leadership and Innovation 2022 ERAU Faculty Mentor of the Year Award With over 200 students from 26 universities participating in 70+ research projects, Dr. Berezovski has established a highly successful undergraduate research program. His funding portfolio includes support from the National Science Foundation and the Mathematical Association of America, and he has served as co-PI on projects with METIS Solutions and DHS. His innovative model connects students directly with industry partners, providing authentic research experiences that result in publications, conference presentations, and valuable career preparation. Dr. Berezovski leads initiatives that foster cross-disciplinary collaboration across Embry-Riddle, working with departments including Security Studies, Human Factors, Aviation Maintenance Science, and Civil Engineering. His research group focuses on applied data science projects that address real-world challenges while providing students with hands-on experience. The program has established long-term partnerships with over ten organizations, businesses, and government labs, creating a sustainable ecosystem for data science research and education.

• Applied Mathematics
• Mathematical Modeling
• Continuum Mechanics
• +۵ مورد دیگر

Professor Alexander Mielke is a leading applied mathematician at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) in Berlin, with extensive involvement in Germany's premier mathematical research initiatives. His career centers on developing rigorous mathematical frameworks for complex physical phenomena, particularly through leadership roles in major DFG-funded programs including Priority Programmes and Collaborative Research Centers. His research spans critical areas of modern applied mathematics: Multiscale modeling of material behavior Mathematical theory of plasticity and hysteresis Continuum mechanics of multifield systems Pattern formation in coupled differential equations Variational methods for rate-dependent processes Professor Mielke's scientific leadership is demonstrated through his role as speaker of Priority Programme SPP 1095 'Analysis Modeling and Simulation of Multiscale Problems' and Collaborative Research Center SFB 404 'Multifield Problems in Continuum Mechanics'. Currently, he drives research as a participating scientist in the Cluster of Excellence MATH+ and sub-project manager for multiple Collaborative Research Centers, maintaining WIAS's prominence in mathematical research. His work consistently addresses fundamental challenges in connecting microscopic mechanisms to macroscopic material properties. Through the Berlin Mathematical School and MATH+, Professor Mielke actively mentors the next generation of applied mathematicians while securing sustained DFG funding for cutting-edge research. His collaborative approach spans theoretical development, numerical implementation, and physical application, particularly in materials science and engineering contexts.

• Theoretical Chemistry
• Quantum Chemistry
• Electronic State Theory
• +۳ مورد دیگر

Hiromi Nakai is a Professor at Waseda University, School of Advanced Science and Engineering, Department of Chemistry and Biochemistry. She holds a Doctorate in Engineering from Kyoto University and has been a leading researcher in theoretical and quantum chemistry for over three decades. Her academic career includes positions at Kyoto University as a Research Associate followed by a progression through the ranks at Waseda University from Assistant Professor to full Professor since 2004. She has also held concurrent positions at Kyoto University and as a Visiting Professor at Rice University. Dr. Nakai's research focuses on theoretical chemistry, quantum chemistry, electronic state theory, molecular simulation, and machine learning applications in chemistry. Her work has significantly advanced computational methods for large-scale quantum chemical calculations, relativistic effects in quantum chemistry, and the development of efficient algorithms for electronic structure calculations. She pioneered the divide-and-conquer method for linear-scaling quantum chemical computations, which has enabled calculations on systems with millions of atoms. Her recent publications demonstrate a strong emphasis on extending computational methods to handle larger systems, incorporating machine learning techniques, addressing relativistic effects, and applying computational chemistry to energy-related problems including battery materials and CO2 conversion. The research spans fundamental quantum chemical method development to practical applications in materials science and sustainable chemistry. Fukui Medal (2024) Member of International Academy of Quantum Molecular Science (2023) Asia-Pacific Association of Theoretical & Computational Chemists Award (2023) CSJ Award for Creative Work (2016) Fellow of Royal Society of Chemistry (2014) Pople Medal from Asia-Pacific Association (2011) Dr. Nakai serves on numerous editorial boards including the International Journal of Quantum Chemistry and has held leadership positions in professional societies including the Molecular Science Society and the Japan Society of Theoretical Chemistry, where she served as President. Her research has been supported by major Japanese funding agencies including JST CREST and PRESTO programs. She leads a research group that integrates theoretical development with practical applications in energy materials and sustainable chemistry.

Loukas F. Kallivokasمشاهده پروفایل

استاد

• Computational Mechanics
• Inverse Problems
• Wave Mechanics
• +۶ مورد دیگر

Loukas F. Kallivokas is a Professor and holder of the Brunswick-Abernathy Regents Professorship in Soil Dynamics and Geotechnical Engineering at The University of Texas at Austin. He serves as Associate Chair of Civil Engineering and is affiliated with multiple research units including the Oden Institute for Computational Engineering and Sciences, Texas Acoustics, and the Texas Consortium for Computational Seismology (TCCS). His educational background includes a Diploma in Civil Engineering from the National Technical University of Athens, and MS (1990) and PhD (1995) degrees in Civil Engineering/Computational Mechanics from Carnegie Mellon University. Prior to joining UT Austin in 1999 as an assistant professor, he held postdoctoral and visiting positions at Carnegie Mellon University, including an NSF CISE postdoctoral fellowship. Professor Kallivokas's research spans computational mechanics with emphasis on wave mechanics and inverse problems. His work focuses on metamaterials design, subsurface imaging, seismic motion modeling, soil-structure interaction, and non-destructive condition assessment. He has made significant contributions to inverse medium problems, inverse scattering, and inverse source problems for wave-driven applications. His research has practical applications in earthquake engineering, geotechnical site characterization, and enhanced oil recovery through wave-based techniques. His recent publications demonstrate consistent output in top journals, with research trends showing increasing focus on metamaterial design, advanced wave focusing techniques, and sophisticated inverse problem solutions for subsurface characterization. The work often involves collaboration with postdocs and students, particularly Heedong Goh who appears as co-author on many recent papers. Allen Newell Medal (1998) for research excellence in large-scale modeling of seismic motion National Science Foundation CAREER award (2003) for research in subsurface imaging Fellow of the Engineering Mechanics Institute (F. EMI) Professional Engineer (PE) license Professor Kallivokas has advised numerous PhD and MS students who have gone on to successful careers in academia and industry, including positions at Seoul National University, Vanderbilt University, ExxonMobil, and major engineering firms. His research has been supported by significant grants including the NSF CAREER award and other NSF funding. He serves as Associate Editor for ASCE's Journal of Engineering Mechanics and previously chaired the Computational Mechanics Committee of ASCE's Engineering Mechanics Institute (2008-2011). His research group operates within the Mechanics, Uncertainty, and Simulation in Engineering (MUSE) laboratory facilities at UT Austin, specifically in ECJ 4.602. The group focuses on computational modeling of wave phenomena and inverse problems, with current projects spanning metamaterial design, subsurface imaging, and coupled-physics imaging approaches.

Robert Honkeمشاهده پروفایل

استاد

• Materials Science
• Structural Mechanics
• Computational Fluid Dynamics
• +۶ مورد دیگر

Prof. Dr. Robert Honke serves as Research Group Leader for System Simulation at the Institute for Hydrogen and Energy Technology (iwe) and sits on the Advisory Board of the Institute for Circular Economy of Bio:Polymers (ibp) at Hof University of Applied Sciences. His office is located in Building C, Room C117, with Wednesday office hours from 13:00-14:00. With over two decades of academic service since 2003, he bridges theoretical physics and practical engineering applications. Education: Physics studies at University of Regensburg Doctorate in Theoretical Physics (University of Regensburg) focusing on ab initio calculations of nonlinear vibrations on semiconductor surfaces Research Interests: Prof. Honke's work spans sustainable materials engineering and advanced simulation techniques. His primary focus areas include construction materials derived from biogenic residues, efficient thermal storage systems, control mechanisms for building energy management, and lightning strike damage simulation on composite structures. His research integrates computational physics with practical engineering challenges, particularly in aerospace and sustainable energy systems. The consistent thread through his career—from semiconductor surface physics to modern composite materials—demonstrates deep expertise in applying simulation methodologies to real-world structural and energy problems. Publication Trends: His recent publications (2015-2022) emphasize lightning protection for composite aerospace materials, thermal energy storage solutions, and biomass conversion technologies. Earlier works (1996-2002) established foundational contributions to surface physics, semiconductor vibrations, and satellite mirror design. Collectively, his research shows a strategic evolution from fundamental surface physics toward applied sustainable engineering, with computational modeling as the unifying methodology across all periods. Scientific Awards: No scientific awards were documented in the provided materials. Advising and Grants: Prof. Honke teaches core subjects in Master's programs for Composite Materials (structural mechanics) and Mechanical Engineering (CFD/FEM/Mathematics), maintaining strong industry connections from his prior Daimler Group experience. While specific student names and grant details aren't listed, his research group leadership indicates active supervision of graduate projects in simulation-based engineering. Labs and Teams: He directs the System Simulation research group at iwe, focusing on hydrogen technology applications, while contributing strategic guidance to ibp's circular economy initiatives for bio-polymers. These dual roles position him at the intersection of sustainable energy systems and advanced materials research within the university's engineering ecosystem.