جست‌وجوی استاد و پژوهشگر

Narayana Aluruمشاهده پروفایل

استاد

• Computational Nanotechnology
• Multiscale Methods
• Nanofluidics
• +۶ مورد دیگر

Narayana Aluru is a Professor and Cockrell Family Regents Chair in Engineering at The University of Texas at Austin, holding positions in the Walker Department of Mechanical Engineering and the Oden Institute for Computational Engineering and Sciences. He joined UT Austin in 2021 after a 23-year tenure at the University of Illinois at Urbana-Champaign, where he served as a Professor, Director of Computational Science and Engineering (2012–2017), and held leadership roles in academic and professional organizations. Education: B.E. (Hons), Birla Institute of Technology & Science, Pilani, India (1989) M.S., Rensselaer Polytechnic Institute (1991) Ph.D., Stanford University (1995) Postdoctoral Associate, MIT (1995–1997) Research Interests: Dr. Aluru specializes in computational nanotechnology, focusing on multiscale methods integrating quantum, atomistic, mesoscale, and continuum scales. His work addresses nanofluidics, bionanotechnology, nanomaterials, and soft matter, with applications in water desalination, nanopower generation, DNA sequencing, and energy storage. His group develops advanced simulation techniques to study phenomena such as ion transport, surface interactions, and nanoscale energy conversion. Publications: His recent work highlights advancements in nanofluidics, nanomaterials, and multiscale modeling. Key themes include dielectric behavior in confined fluids, charge inversion in electric double layers, and energy harvesting via MoS₂ nanopores. These studies bridge fundamental physics and engineering applications. Awards: Charles Russ Richards Memorial Award (ASME, 2024) Cockrell Family Regents Chair (UT Austin, 2023) Fellow of AAAS, APS, ASME, and IACM National Science Foundation CAREER Award (1999) Advising & Grants: A dedicated educator, Dr. Aluru has advised numerous graduate students and postdocs. He has led research supported by grants from NSF, DOE, and industry, emphasizing computational methods and nanotechnology. His teaching excellence was recognized repeatedly at UIUC. Labs/Teams: He leads the Multiscale Nanotechnology Group and collaborates with the Oden Institute, advancing interdisciplinary research in computational engineering and nanotechnology.

• Nuclear Energy
• Medical Physics
• Radiation Safety/Security
• +۷ مورد دیگر

Professor Wei Ji holds the William H. Hernstadt '57 Faculty Fellow position in Nuclear Engineering at Rensselaer Polytechnic Institute (RPI), where he also directs the Walthousen Reactor Critical Facility. He leads the Nuclear Computing and Multi-Physics (NuCoMP) Research Group, focusing on advanced computational techniques for nuclear energy, medical physics, and space exploration applications. He earned his B.S. and M.S. from Tsinghua University and his Ph.D. from the University of Michigan. His research addresses challenges in reactor design, radiation therapy, Monte Carlo methods, and rad-hard electronics for space missions, supported by over $14M in funding from agencies like DOE, NASA, and NIH. Education: B.S. in Engineering Physics, Tsinghua University (1999) M.S. in Engineering Physics, Tsinghua University (2002) M.S. in Nuclear Engineering, University of Michigan (2004) Ph.D. in Nuclear Engineering, University of Michigan (2007) Research Interests: Professor Ji’s work bridges computational methods with nuclear applications, including: Neutron transport modeling and reduced-order methods Advanced reactor design and safety analysis Radiation therapy dose computation Space-compatible power device reliability Multiphysics coupling for reactor transient analysis His recent studies emphasize cryogenic propulsion systems, molten salt reactor chemistry, and radiation-hardened electronics for extreme environments. Notable Achievements: Over 160 peer-reviewed publications since 2008 DOE/ANS awards for research excellence 2019 NEAGS Teaching Award and 2018 RPI Education Innovation Award Grants & Advising: Total funding: $14M+ from DOE, NASA, NIH, NRC, and industry Focus areas include NEAMS Program contributions, NRC safety assessments, and NASA ESI-funded space technology Labs & Teams: His NuCoMP Group collaborates with national labs (LANL, ANL) and industry partners to develop next-generation simulation tools and hardware for nuclear systems. Current projects include: Metamodel-driven Monte Carlo workflows Equation-free multiscale fluid modeling Radiation effects on SiC/Si devices

Giorgio Borniaمشاهده پروفایل

دانشیار

• Numerical Analysis
• Computational Fluid Dynamics
• Finite Element Methods
• +۲ مورد دیگر

Dr. Giorgio Bornia is an Associate Professor in the Department of Mathematics and Statistics at Texas Tech University. He holds a PhD in Energy Engineering from the University of Bologna and specializes in computational methods for partial differential equations. His research focuses on: Optimal control for fluid dynamics and MHD systems Finite element and boundary element methods Multigrid and domain decomposition algorithms Parallel computing in scientific applications He received the 2018 President's Excellence in Teaching Award and multiple student-nominated teaching awards. Doctoral students supervised include Sureka Pathmanathan (boundary optimal control) and Ali Rezaei (poroelasticity). Grant support includes NSF and Royal Society funding.

Wei Weiمشاهده پروفایل

دانشیار

• Aerospace Engineering
• Unmanned Aerial Vehicles
• Control Systems
• +۳ مورد دیگر

Wei Wei is an Associate Professor at the University of Cincinnati, focusing on aerospace engineering with applications in unmanned systems and energy technologies. Her research integrates computational modeling, control systems, and electrochemistry to advance battery design, electrolysis, and UAV performance. Key research areas include mechano-electrochemical battery models, hydrogen production via electrolysis, and aerospace system optimization. Recent publications emphasize multiphysics simulations for energy devices, with applications in electric vehicles and renewable hydrogen. Articles demonstrate consistent innovation in 3D modeling of electrochemical processes, material degradation analysis, and transport phenomena in energy systems. Computational methods bridge fundamental electrochemistry and industrial applications.

Jayathi Y. Murthyمشاهده پروفایل

استاد

• Nanoscale Heat Transfer
• Computational Fluid Dynamics
• Multiscale Multi-Physics Simulations
• +۱۲ مورد دیگر

Jayathi Y. Murthy is a Professor in the Department of Mechanical and Aerospace Engineering at the UCLA Henry Samueli School of Engineering and Applied Science. She served as the Ronald and Valerie Sugar Dean of the school from January 1, 2016, to July 31, 2022, becoming the first woman to hold this position. Her leadership emphasized transformative growth in areas such as engineering in medicine, artificial intelligence, sustainable urban systems, and advanced materials. Research Interests: Murthy's research spans nanoscale heat transfer , computational fluid dynamics (CFD) , and multiscale multi-physics simulations of micro- and nano-electromechanical systems (MEMS/NEMS). She also investigates uncertainty quantification in simulations, particularly in sub-micron thermal transport. Her work bridges fundamental thermal sciences with industrial applications, including energy systems and microelectronics. The 15 most recent articles reflect a strong focus on thermal modeling at micro- and nanoscales , advanced numerical methods in CFD , and uncertainty-aware simulations . Keywords include nanotechnology, heat transfer, computational engineering, and materials science. Subfields span phonon transport, adaptive mesh refinement, hybrid numerical schemes, and inverse methods, showing a consistent trajectory toward high-fidelity, predictive modeling in thermal systems. Scientific Awards and Honors: National Academy of Engineering (NAE) Member Foreign Fellow, Indian National Academy of Engineering (INAE) Fellow, American Society of Mechanical Engineers (ASME) ASME Heat Transfer Memorial Award (2016) ASME Electronics and Photonics Packaging Division Clock Award Advising and Grants: While no specific students are listed, Murthy has led major research centers, including the $21 million NNSA-supported PRISM Center at UT Austin. She has authored over 330 publications and edited the second edition of the Handbook of Numerical Heat Transfer . Her editorial roles include service on Numerical Heat Transfer and the International Journal of Thermal Sciences . Labs and Research Teams: Murthy led the Center for Prediction of Reliability, Integrity and Survivability of Microsystems (PRISM), a multidisciplinary research hub. Her work involves collaborations across mechanical engineering, materials science, and computational modeling, often integrating industrial and academic partners.

Jifu Tanمشاهده پروفایل

استادیار

• Fluid-Structure Interaction
• High-Performance Computing
• Multiscale/Multiphysics Modeling
• +۶ مورد دیگر

Jifu Tan is an Assistant Professor in the Department of Mechanical Engineering at Binghamton University. Previously, he served as an Assistant Professor and later Associate Professor at Northern Illinois University (NIU), and completed a postdoctoral fellowship at the University of Pennsylvania. His research focuses on fluid-structure interaction, high-performance computing, multiscale modeling, and machine learning applications in engineering and medicine. He holds a BS in Civil Engineering from Beijing Jiaotong University and MS/PhD in Mechanical Engineering from Lehigh University. Notable recognitions include the 2024 David W. Raymond Award for Teaching Technology Innovation and the 2024 NSF CAREER Award. His research interests span computational fluid dynamics, microfluidic device design for cell separation, blood flow modeling, and thrombosis simulation. He develops open-source codes for multiphysics simulations and has pioneered parallel fluid-structure interaction models for nanoparticle transport and cellular suspensions. His work integrates physics-based machine learning and data-driven models to address challenges in healthcare and engineering. Recent contributions include studies on granular flow dynamics in conveyor systems, biomimetic fish locomotion analysis, and predictive modeling of disease transmission using dynamic mode decomposition. He collaborates with Argonne National Laboratory on multiphysics research and actively mentors students in computational and experimental projects. Scientific achievements include advancements in microfluidic sorting techniques, nanoparticle delivery systems, and computational tools for in situ visualization of blood flow simulations. His lab focuses on translating multiscale simulations into practical applications for drug delivery, medical diagnostics, and sustainable engineering solutions.

Gary D. Seidelمشاهده پروفایل

استاد

• Multiscale Modeling
• Composites
• Structural Health Monitoring
• +۳ مورد دیگر

Dr. Gary D. Seidel is a Full Professor and Assistant Department Head for Academic Affairs at the Virginia Polytechnic Institute and State University's College of Engineering. He earned his Ph.D., M.S., and B.S. in Aerospace Engineering from Texas A&M University (2007, 2002, 1999) and has held academic positions at Virginia Tech since 2008. His research focuses on multiscale modeling of damage evolution in multifunctional composites, particularly those incorporating carbon nanotubes. Ph.D., Aerospace Engineering, Texas A&M University, 2007 M.S., Aerospace Engineering, Texas A&M University, 2002 B.S., Aerospace Engineering, Texas A&M University, 1999 Dr. Seidel's research bridges atomistic and continuum scales to analyze piezoresistivity, fracture mechanics, and multifunctional properties in nanocomposites. He develops computational tools for modeling damage in materials used for hypersonic vehicles, lunar structures, and energetic materials. His work integrates micromechanics with advanced sensor systems and topology optimization for structural health monitoring. His recent publications focus on multiscale modeling of CNT-polymer composites, thermomechanical properties of ultra-high temperature ceramics, and piezoresistive damage sensing networks. These align with keywords like computational mechanics, nanotechnology, and materials science, covering subfields such as peridynamics, interfacial modeling, and stochastic microstructure analysis. Scientific Awards: ASME Fellow (2020) AIAA Associate Fellow (2013) AFRL Summer Faculty Fellow (2017-2021) Oak Ridge Ralph E. Powe Award (2010) ASME/Boeing Best Paper Award (2016) Dr. Seidel serves as Associate Editor for Applied Mechanics Reviews and Smart Materials and Structures , and actively participates in AIAA and ASME technical committees. He co-directs the Aerospace Structures and Materials Lab (ASML) and mentors NASA MUST undergraduate researchers, demonstrating commitment to both academic leadership and student development.

Jun Xuمشاهده پروفایل

دانشیار

• Battery Technology
• Material Science
• Energy Storage Systems
• +۵ مورد دیگر

Jun Xu is an Associate Professor in the Department of Mechanical Engineering at the University of Delaware, part of the College of Engineering. His research focuses on interdisciplinary energy and electrochemistry, particularly battery sustainability, advanced materials for vehicle applications, and crashworthiness analysis. He leads a group exploring electrochemo-mechanical modeling, multiscale computation, and machine learning in energy storage systems. Dr. Xu holds a PhD in Environmental Engineering/Engineering Mechanics from Columbia University. He is an Executive Committee member of the ASME Advanced Energy System Division and serves as Associate Editor for journals like Journal of Electrochemical Energy Conversion and Storage and Batteries . With over 140 peer-reviewed publications and an H-index of 46, he has been recognized in the 2022 and 2023 World Top 2% Scientists lists. His research integrates mechanics, materials science, and energy systems, addressing challenges in battery safety, durability, and lightweight structural design. Recent work emphasizes bioinspired materials for impact protection and model-driven manufacturing of high-energy-density batteries.

• Scientific Computing
• Numerical Linear Algebra
• Parallel Computing
• +۳ مورد دیگر

Michael T. Heath is a Professor and Fulton Watson Copp Chair Emeritus in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC). He holds a Ph.D. in Computer Science from Stanford University (1978). His research focuses on scientific computing, numerical linear algebra, optimization, and parallel computing with notable contributions to sparse matrix computations and parallel algorithm design. Heath has directed major initiatives such as the Computational Science and Engineering Program (1996–2012) and the Center for Simulation of Advanced Rockets (1997–2010), securing over $52M in research funding. He is an ACM Fellow, SIAM Fellow, and European Academy of Sciences member. Teaching excellence defines his career, highlighted by awards including the IEEE Taylor L. Booth Education Award (2009) and UIUC's Campus Award for Excellence in Graduate Teaching (2002). He developed interactive educational modules in scientific computing and teaches courses like CS 450 (Numerical Analysis) and CS 554 (Parallel Numerical Algorithms). His research spans parallel performance visualization, numerical optimization, and mathematical software, with over 50 years of contributions to computational science. Education: Ph.D. Computer Science, Stanford University (1978) Affiliations: Department of Computer Science, UIUC; former Interim Head (2007–2009) Key Roles: Director, Computational Science and Engineering Program; Director, Center for Simulation of Advanced Rockets His publications emphasize parallel algorithms, numerical methods, and computational frameworks for multiphysics simulations. Heath’s work bridges academic research and practical applications, exemplified by his leadership in high-performance computing and rocket propulsion modeling.

Richard A. Regueiroمشاهده پروفایل

استاد

• Computational Multiscale Mechanics
• Geomechanics
• Materials Science
• +۵ مورد دیگر

Richard A. Regueiro is a Professor in the Department of Civil, Environmental, and Architectural Engineering at the University of Colorado Boulder. His research focuses on computational multiscale mechanics for porous and particulate materials, including geomaterials, biomaterials, and multiphase systems. He leads projects funded by DOE, ONR, and other agencies, emphasizing exascale computing and micromorphic modeling. Regueiro holds a PhD from Stanford University (1998) and has been honored with awards such as the R&D 100 Award (2000) and the Sidney Shore Award (1991). Education: Ph.D., Stanford University (1998) S.M., MIT (1993) B.S.E., University of Pennsylvania (1991) Research Interests: Computational multiscale modeling of materials at micro-to-macro scales, including granular materials, geomaterials, and biological tissues. Key areas include poromechanics, damage mechanics, and coupled thermo-mechanical processes. His work bridges particle-level mechanics with continuum models for applications in geotechnical engineering, biomedical systems, and defense. Publications: Over 100 peer-reviewed articles, with recent focus on DEM parallelism, granular localization, and micromorphic constitutive models. His 2018 work on superlinear speedup in DEM simulations exemplifies computational advancements. Grants/Awards: DOE NNSA PSAAP Center (2020–2025), ONR MURI (2011–2021), and multiple industry collaborations. Labs/Teams: Leads the Computational Micromorphic Multiphysics Group, developing codes like Tahoe and ParaEllip3d-CFD. Collaborates with Sandia National Labs, Los Alamos National Lab, and universities globally.

Karel Matoušمشاهده پروفایل

استاد

• Computational Mechanics
• Computational Science and Engineering
• Multiscale and Multi-physics Modeling
• +۱۲ مورد دیگر

Karel Matouš is a Professor in the Department of Aerospace and Mechanical Engineering at the University of Notre Dame , where he also serves as the Director of the Center for Shock-Wave Processing of Advanced Reactive Materials (C-SWARM) . His research is centered on computational mechanics and engineering, with a focus on multiscale and multiphysics modeling of heterogeneous materials. Education: Ph.D. in Theoretical and Applied Mechanics, Czech Technical University in Prague (2000) M.S. in Theoretical and Applied Mechanics, Czech Technical University in Prague Research Interests: Matouš’s work spans computational science and engineering , data-driven modeling , high-performance computing , and statistical micromechanics . He develops advanced numerical methods for modeling complex systems such as solid propellants, reactive materials, and particulate composites, often integrating microtomography data for realistic material reconstruction. Publication Trends: His recent publications emphasize reduced-order modeling , image-based simulations , and uncertainty quantification in multiscale systems. Many studies combine experimental data with computational frameworks to predict macroscopic behavior from microstructural features, particularly in reactive and heterogeneous materials. Scientific Awards: Fellow of ASME (2013) Visiting Professor at Eindhoven University of Technology with 10,000 EUR research grant (2016) Rector's Award, Czech Technical University (1999) Academician Z. Bazant's Prize (1996, 1997) Multiple recognitions for high-impact publications (ScienceDirect Top 25 Hottest Articles) Student awards including the Robert J. Melosh Medal and USNCCM9 presentation prize Advising and Grants: He has advised numerous Ph.D. and M.S. students in computational mechanics and materials science. His research is supported by major grants from the Department of Energy (e.g., C-SWARM: $11.6M), NSF , DoD (STTR/SBIR programs), and industry partners like 3M and ATK . These projects focus on adaptive modeling, shock-wave processing, and microstructural characterization of advanced materials. Labs and Teams: He leads the Computational Physics Group and the C-SWARM center, which involves collaboration with institutions including Purdue University, Indiana University, and the University of Illinois. The group utilizes high-performance computing and experimental validation to advance predictive modeling of extreme material behaviors.

Zhen (Leo) Liuمشاهده پروفایل

دانشیار

• Geotechnical Engineering
• Artificial Intelligence
• Numerical Simulation
• +۳ مورد دیگر

Zhen (Leo) Liu is an Associate Professor at the University of Virginia, specializing in geotechnical engineering and interdisciplinary applications of artificial intelligence. His research bridges classical mechanics with modern computational techniques. Multiphysics and Multiscale Modeling Intelligent Infrastructure Systems Geomechanics and Geomaterials Field Instrumentation Energy Geotechnics Geohazards His work focuses on integrating AI into geotechnical challenges, addressing infrastructure safety, energy resources, and environmental protection through innovative numerical simulations and collaborative approaches. The absence of explicit awards, grants, or student advising information in the provided text suggests these details may not be publicly listed or require direct inquiry for full disclosure.

Timothy Trusterمشاهده پروفایل

دانشیار

• Computational Mechanics
• Interface Mechanics
• Composite Material Modeling
• +۷ مورد دیگر

Timothy Truster is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Tennessee, Knoxville, within the Tickle School of Engineering. He leads the Computational Laboratory for the Mechanics of Interfaces (CLMI), focusing on advanced computational modeling of material interfaces, including contact, fracture, and delamination phenomena. Education: PhD in Civil & Environmental Engineering, University of Illinois at Urbana-Champaign, 2013 MS in Civil & Environmental Engineering, University of Illinois at Urbana-Champaign, 2010 BS in Civil & Environmental Engineering, University of Dayton, 2008 His research centers on computational mechanics, particularly the development of robust and stable numerical methods for modeling interfaces in heterogeneous and composite materials. Key areas include stabilized finite element methods, interfacial damage, frictional contact, high-temperature creep in metals, crystallographic texture effects, and high-performance computing. His work bridges theoretical mechanics with practical engineering applications in structural integrity and material performance. The 13 publications listed span from 2011 to 2016 and reflect a consistent focus on interface modeling using advanced computational techniques such as discontinuous Galerkin methods, Nitsche formulations, and variational multiscale approaches. These works emphasize numerical stability, algorithmic robustness, and physical consistency in simulating complex interfacial behaviors under finite strains and multiphysics conditions. Scientific Awards: National Science Foundation Graduate Research Fellowship Best Poster Award from the United States Association for Computational Mechanics Truster advises graduate students through his research group, CLMI, where he mentors work in computational modeling and simulation. He has secured research support through prestigious fellowships and likely external grants, though specific grants are not detailed. His lab, the Computational Laboratory for the Mechanics of Interfaces, develops and applies cutting-edge numerical methods for interfacial mechanics in materials and structures, contributing to advancements in composite systems, mechanical joints, and multiscale material modeling.

Benjamin Wheatleyمشاهده پروفایل

دانشیار

• Orthopaedic biomechanics
• Musculoskeletal modeling
• Soft-tissue mechanics
• +۲ مورد دیگر

Benjamin Wheatley is an Associate Professor of Mechanical Engineering at Bucknell University, where he leads the Mechanics and Modeling of Orthopaedic Tissues Laboratory (MMOT Lab) . His research integrates experimental and computational biomechanics to understand soft-tissue and musculoskeletal mechanics, with applications spanning orthopaedics, rehabilitation engineering, and bio-inspired design. Education B.S. in Engineering, Trinity College, 2011 Ph.D. in Mechanical Engineering, Colorado State University, 2017 Research Interests Wheatley’s work centers on finite-element modeling and experimental characterization of biological soft tissues, particularly skeletal muscle, tendon, and bone. He investigates structure–function relationships in orthopaedic tissues, neuromuscular biomechanics, and bio-inspired protective structures such as bighorn sheep horns. Applications include improving prosthetic gait, understanding knee-joint loading, and designing impact-mitigating materials. Publication Trends Across more than 30 peer-reviewed articles since 2015, Wheatley’s scholarship exhibits two dominant trajectories: (1) high-fidelity computational modeling of skeletal muscle and orthopaedic tissues under multiaxial loading, and (2) experimental biomechanics studies combining motion capture, EMG, imaging, and mechanical testing. Recent work increasingly couples optimal-control theory with gait simulations to predict clinical outcomes for individuals with limb loss. Scientific Awards & Honors (none explicitly listed in provided text) Advising & Funding Wheatley actively mentors undergraduate and graduate researchers in the MMOT Lab; interested students are invited to attend weekly lab meetings after contacting him via email. Grant and funding details are not provided in the supplied text. Laboratory & Team He directs the Mechanics and Modeling of Orthopaedic Tissues Laboratory located in Academic East 302, Bucknell University. The lab emphasizes student-led collaborative research that bridges mechanical engineering, orthopaedics, and biology.

George Em Karniadakisمشاهده پروفایل

استاد

• Scientific Machine Learning
• Fractional PDEs
• Uncertainty Quantification
• +۷ مورد دیگر

George Em Karniadakis is the Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics and Professor of Engineering at Brown University. He holds joint appointments in the Department of Applied Mathematics and Engineering, with affiliations at PNNL and MIT as Visiting Professor. His research focuses on Scientific Machine Learning, fractional PDEs, uncertainty quantification, and biophysics, with notable contributions to computational fluid dynamics, neurovascular coupling, and multiscale modeling. Education: Ph.D. (1987) and S.M. (1984) from MIT. Prior roles include Assistant Professor at Princeton, Visiting Professorships at Caltech and Stanford's Center for Turbulence Research. Research Interests: Karniadakis pioneers Scientific Machine Learning to solve PDEs without grids, leveraging gappy data. His work spans fractional calculus applications, stochastic multiscale methods, and biological systems modeling (e.g., sickle cell anemia, malaria). Recent efforts include neurovascular coupling in the brain and fractional PDE theory. Articles Trends: His work bridges computational mathematics and biomedical applications, emphasizing fractional calculus, fluid-structure interaction, and high-performance computing. Notable work includes modeling cerebral aneurysms and red blood cell dynamics. Awards: SIAM Fellow (2010), APS Fellow (2004), ASME Fellow (2003), SIAM Kleinman Award (2015), and the inaugural J. Tinsley Oden Medal (2013). He holds an h-index of 102 and ~55,500 citations. Grants & Leadership: Lead PI of MURI projects on Fractional PDEs and Uncertainty Quantification. Directed DOE centers PhILMs and CM4. Advises on multiscale modeling and parallel computing. Labs/Teams: Directs the CRUNCH Group at Brown, focusing on fluid dynamics, biophysics, and high-performance computing. Collaborates internationally on projects like blood flow modeling and brain aneurysm simulations.