Multiscale/Multiphysics Modeling and Simulation Professors and Supervisors in United States

Thomas Rothمشاهده پروفایل

استادیار

Purdue UniversityUnited States

Thomas Roth is an Assistant Professor of Electrical and Computer Engineering at Purdue University , specifically within the Elmore Family School of Electrical and Computer Engineering . His research focuses on quantum and classical electromagnetic systems, with expertise in multiscale modeling and applied electromagnetics. He holds a Ph.D. in Electrical Engineering from the University of Illinois at Urbana-Champaign (2020), following B.S. and M.S. degrees from Missouri University of Science & Technology and Illinois, respectively. Education: B.S. in Electrical Engineering, Missouri University of Science & Technology, 2015 B.S. in Computer Engineering, Missouri University of Science & Technology, 2015 M.S. in Electrical Engineering, University of Illinois at Urbana-Champaign, 2017 Ph.D. in Electrical Engineering, University of Illinois at Urbana-Champaign, 2020 Research Interests: Roth’s work bridges quantum mechanics and electromagnetic theory, emphasizing computational methods for superconducting circuits and quantum devices. His lab develops numerical frameworks for modeling transmon qubits, Josephson parametric amplifiers, and multiphysics systems. Recent efforts include analytical solutions for multi-qubit interactions and robust finite-element methods for quantum systems. Publications: His 2024-2025 work highlights advancements in quantum full-wave solutions, parametric amplifiers, and hybrid modeling techniques. Key themes include improving numerical stability for quantum systems and exploring dielectric loading for optical qubits. Awards/Grants: No specific awards listed, but his work aligns with emerging quantum engineering priorities at Purdue. Lab/Teams: His research group focuses on computational quantum electromagnetics, collaborating on projects involving superconducting circuits and quantum device optimization.

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Frank Liouمشاهده پروفایل

استاد

Missouri University of Science and TechnologyUnited States

Dr. Frank Liou is the Michael and Joyce Bytnar Professor in the Department of Mechanical Engineering at Missouri University of Science and Technology (Missouri S&T). He founded and directs the Manufacturing Engineering Program since 1999 and leads the Intelligent Systems Center. His research focuses on additive manufacturing, including hybrid processes, multiscale modeling, and material fabrication innovations. **Education**: Ph.D., Mechanical Engineering (1987), University of Minnesota M.S., Mechanical Engineering (1984), North Carolina State University B.S., Mechanical Engineering (1980), National Cheng-Kung University, Taiwan **Research Interests**: Dr. Liou's work spans metal additive manufacturing, novel process development, rapid prototyping, and advanced material fabrication. He emphasizes process modeling, remanufacturing automation, and digital materials processing. Notable contributions include collaborations with Siemens and DMG/MORI to commercialize hybrid manufacturing technologies. **Awards**: SME Frederick W. Taylor Research Medal (2020) Fellow of ASME and SME **Advising & Grants**: While specific student names are not listed, Dr. Liou has advised numerous researchers in additive manufacturing. His grants support industry-academia partnerships, such as developing the NX Hybrid Manufacturing module with Siemens. **Labs & Teams**: He oversees the Intelligent Systems Center and Manufacturing Engineering Program, fostering interdisciplinary innovation in digital and additive manufacturing.

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Jason Phipps-Morganمشاهده پروفایل

استاد

Cornell UniversityUnited States

Jason Phipps-Morgan is a Professor in the Department of Earth and Atmospheric Sciences at the College of Engineering, Cornell University. His work bridges geodynamics, computational modeling, and Earth system processes, with a focus on large-scale mantle and crustal dynamics. Research Interests: His research centers on geodynamic modeling of mantle convection, particularly the role of a plume-fed asthenosphere, as well as fluid and melt migration in subduction zones and mid-ocean ridges. He develops advanced 3D parallel computational tools to simulate highly nonlinear interactions between deformation, fluid flow, and chemical reactions. His recent publications reflect a strong trend in multiscale, multiphysics numerical modeling applied to fundamental Earth processes, including hydrothermal circulation, carbon sequestration, and bend-faulting in subducting plates. Scientific Awards: Professeur, College de France (1996) James B. Macelwane Award, American Geophysical Union (1995) Cecil and Ida Green Scholar (1985) Education: Brown University, 1985 Jason Phipps-Morgan has led significant research initiatives in geodynamics and has contributed to major advancements in numerical modeling of Earth systems. His work has been supported by prestigious fellowships and awards, and he continues to develop innovative computational platforms for exploring planetary dynamics. While no formal advising or grant details are listed, his collaborative publications suggest active engagement with national and international research teams.

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Eric Y. Maمشاهده پروفایل

استادیار

University of California, BerkeleyUnited States

Eric Y. Ma is an Assistant Professor in the Department of Physics and by courtesy in Electrical Engineering and Computer Science (EECS) at UC Berkeley, where he holds the Georgia Lee Chair in Physics. He leads the Ma Lab, focusing on wave-matter interactions in quantum regimes, sub-wavelength scales, and unconventional frequencies (THz to UV). His research combines simulation, optimization, and experimental techniques across microwave to ultraviolet domains. Education 2016: Ph.D. in Applied Physics, Stanford University 2010: B.S. in Physics, Peking University Research Focus Dr. Ma's research explores electromagnetic interactions with condensed matter systems, developing novel tools for nanoscale characterization. His work spans quantum materials, inverse design methodologies, microwave microscopy innovations, and applications in computing, sensing, and mixed reality. The lab maintains a balance between fundamental physics and practical implementation. Publication Trends Recent publications demonstrate strong focus on advancing microwave impedance microscopy techniques for quantum materials characterization, developing physics-agnostic inverse design frameworks, and exploring spin wave dynamics. Significant contributions appear in nanophotonics, quantum measurement, and interdisciplinary applications bridging physics with machine learning. Awards & Honors Hellman Fellow (2024) Google Research Scholar (2024) Amazon Physical Science Fellowship (2022) Georgia Lee Chair in Physics Research Support Moore Foundation: Quantum-Limited Atomic Force Microscope development (2024) NSF: Advanced Inverse Design of Microwave Devices (2024) Google: Parsing Physics Literature with LLMs (2024) Laboratory The Ma Lab specializes in developing experimental platforms spanning microwave to ultraviolet frequencies, emphasizing DIY instrumentation and collaborative research. The team includes postdoctoral researchers, graduate students, and undergraduates working on quantum materials characterization, inverse design algorithms, and novel microscopy techniques.

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Christoph Beckermannمشاهده پروفایل

استاد

University of IowaUnited States

Christoph Beckermann is the University of Iowa Foundation Distinguished Professor of Mechanical Engineering and Director of the Solidification Laboratory at the University of Iowa's College of Engineering. He has been a faculty member since 1987, progressing from Assistant to full Professor in 1996, and holds one of the highest academic honors at the university. His educational background includes a Vordiplom from the University of Hannover and M.S. and Ph.D. degrees in Mechanical Engineering from Purdue University. He served in the German military before pursuing higher education. Beckermann's research focuses on solidification science, metal casting, thermal and fluid sciences , with strong emphasis on computational modeling of multiphase systems, heat transfer, and materials processing. His work spans from fundamental phase-field simulations to industrial-scale casting and additive manufacturing. He integrates numerical methods with experimental validation to understand microstructure evolution, inclusion dynamics, and macrosegregation. The 15 most recent publications reflect a consistent trend in multiscale and multiphysics modeling of solidification phenomena, combining phase-field methods with fluid dynamics, thermomechanics, and granular flow. Keywords include solidification, materials processing, computational modeling, and transport phenomena, with subfields ranging from dendritic growth to residual stress prediction in additive manufacturing. Fulbright Award (1982–84) NSF Presidential Young Investigator Award (1989) Bruce Chalmers Award, TMS (2010) Heat Transfer Memorial Award, ASME (2017) Nagy El-Kaddah Award, TMS (2021) Founders' Choice Award, SFSA (2022) Beckermann has supervised 25 Ph.D. and 23 M.S. students , along with 12 postdocs and 20 visiting scholars. He has secured approximately $20 million in external research funding from federal and industrial sources. His editorial roles include long-term service on Metallurgical and Materials Transactions and the International Journal of Cast Metals Research . He has delivered over 60 invited seminars and 13 plenary lectures globally. He leads the Solidification Laboratory at the University of Iowa, which focuses on computational and experimental studies of solidification processes. The lab develops advanced models for inclusion transport, grain motion, and macrosegregation, with applications in steel casting, additive manufacturing, and aerospace materials.

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Vivek Bharadwajمشاهده پروفایل

پژوهشگر

National Renewable Energy LaboratoryUnited States

Dr. Vivek Bharadwaj is a Staff Scientist in the Computational Molecular Science department at the National Renewable Energy Laboratory (NREL) , where he has worked since 2018. His research integrates computational molecular modeling , quantum mechanics , and finite element methods to advance bioenergy technologies and chemical conversion systems . PhD (2015): Chemical Engineering, Colorado School of Mines Master's (2011): Chemical Engineering, Colorado School of Mines Bachelor's (2008): Chemical Engineering, Sardar Vallabhbhai National Institute of Technology Surat Vivek's research focuses on: Elucidating biomass biosynthesis mechanisms in plants Investigating the biophysics of plant cell wall pectins Modeling enzymatic biomass deconstruction pathways Developing intrinsic kinetics models for catalytic systems Studying electron transport in biological systems His publications demonstrate expertise in molecular dynamics , machine learning applications in enzyme analysis, and catalyst surface characterization . Key collaborations include work with the Center for Bioenergy Innovation and Consortium for Computational Physics and Chemistry . 2015: American Chemical Society Chemical Computing Group Research Excellence Award 2014: NVIDIA Best GPU Poster Award

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José E. Andradeمشاهده پروفایل

استاد

California Institute of Technology (Caltech)United States

José E. Andrade is the George W. Housner Professor of Civil and Mechanical Engineering at the California Institute of Technology (Caltech), where he has held faculty positions since 2010. His research focuses on multiscale and multiphysical behaviors of porous materials (e.g., soils, rocks, bone) and granular materials (e.g., sand, snow). He leads the COSYMO group , applying computational mechanics to geotechnical and environmental challenges. B.S., Florida Institute of Technology, 2001 M.S., Stanford University, 2003 PhD, 2006 His scientific awards include the ASME Fellowship, Huber Civil Engineering Research Prize, and Thomas J.R. Hughes Young Investigator Award. Current research trends highlight applications in mechanical metamaterials , carbon sequestration , and geotechnical testing via computational methods like DEM and micromorphic mechanics. ASME Fellow (2021) Huber Civil Engineering Research Prize Thomas J.R. Hughes Young Investigator Award Andrade teaches Advanced Topics in Applied Mechanics , Civil Engineering , and Mechanical Engineering , with a focus on multiscale modeling. His work bridges engineering infrastructure , petroleum industry applications, and structural dynamics in energy storage systems.

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Somdatta Goswamiمشاهده پروفایل

استادیار

Johns Hopkins UniversityUnited States

Somdatta Goswami serves as Assistant Professor in Civil and Systems Engineering and Applied Mathematics and Statistics at Johns Hopkins University, with dual affiliations at the Institute for Data Intensive Engineering and Science (IDIES) and Hopkins Extreme Materials Institute (HEMI). She leads the Centrum IntelliPhysics research group developing AI-driven methodologies for scientific discovery. Her educational trajectory includes: Bachelor's in Civil Engineering from Birla Institute of Technology, Mesra (2011) Master's in Structural Engineering from Indian Institute of Engineering Science and Technology (2013) PhD in Civil Engineering and Structural Mechanics from Bauhaus University-Weimar, Germany (2020) funded by DAAD Dr. Goswami's research pioneers Scientific Machine Learning at the intersection of computational mechanics and AI, focusing on neural operator architectures that accelerate physics-based simulations. Her group develops methods for long-time horizon prediction, multiscale multiphysics modeling, and real-time inference in complex systems through latent space representations and physics-informed learning. Current emphases include cardiac digital twins, structural response under natural hazards, and RNA electrophoresis modeling. Analysis of her 2024-2025 publications reveals dominant trends in latent operator learning, physics-informed neural networks, and hybrid solvers combining traditional numerical methods with deep learning. These innovations enable breakthroughs in computational efficiency across engineering and biological domains, particularly in multiscale modeling and uncertainty-aware simulation. Her scientific recognition includes: National Science Foundation’s National Artificial Intelligence Research Resource (NAIRR) Pilot Johns Hopkins University Discovery Award 2024 Dr. Goswami mentors PhD candidates including Dibakar Roy Sarkar (Creel Family Engineering Fellow), Sharmila, and Maryam. Major research funding comprises: NSF grant for "Cardiac Digital Twins" with Kevrekidis, Trayanova, and Maggioni NSF grant for exascale AI-integrated simulations with UT Austin DOE grant for uncertainty-informed latent operators with Shields, Graham-Brady, and Kevrekidis Johns Hopkins Discovery Award for biological systems modeling The Centrum IntelliPhysics group operates within JHU's Latrobe Hall, collaborating with IDIES and HEMI on interdisciplinary projects spanning computational mechanics, materials science, and biological systems. Their work integrates high-performance computing with novel neural architectures to solve previously intractable scientific problems.

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Xiang Zhangمشاهده پروفایل

دانشیار

University of WyomingUnited States

Xiang Zhang serves as Associate Professor in the Department of Mechanical Engineering at the University of Wyoming, where he has held a faculty position since 2019. He directs the Computations for Advanced Materials and Manufacturing Laboratory (CAMML), focusing on establishing microstructure-processing-performance relationships through advanced computational models. His work bridges material microscale phenomena with structural-scale applications in high-performance materials and manufacturing processes. His educational foundation includes: Ph.D. in Civil Engineering from Vanderbilt University (2017) M.S. in Solid Mechanics from Beihang University (2012) B.S. in Engineering Mechanics from Northeastern University (2009) Dr. Zhang's research centers on multiscale and multiphysics computational modeling, with emphasis on deformation and damage mechanisms in metals and composites. His group develops crystal plasticity finite element models, interface-enriched generalized finite element methods (IGFEM), and reduced-order homogenization techniques. Current projects target frontal polymerization for composite 3D printing, metal additive manufacturing, and microstructure-informed material design. This work integrates computational modeling with experimental validation to solve challenges in structural integrity and manufacturing efficiency. Recent publications (2019-2023) reveal strong thematic continuity in multiscale modeling of composite manufacturing processes, particularly frontal polymerization applications in 3D printing. His work consistently connects microscale material behavior (e.g., crystal plasticity, interface damage) with structural performance through reduced-order modeling frameworks. Key journals include Computer Methods in Applied Mechanics and Engineering , Composite Science and Technology , and Additive Manufacturing , demonstrating cross-disciplinary impact in computational mechanics and materials engineering. His honors include: NSF CAREER Award (2023) for multiscale modeling of hybrid composites Dolling & Scott Faculty Research Award (2022) Multiple national conference awards including Melosh Medal Finalist (2017) Student paper competitions at Engineering Mechanics Institute (2016) Dr. Zhang actively mentors graduate researchers through CAMML, currently advising three PhD students and one MS student, with eight alumni completing degrees under his supervision. His NSF CAREER grant enables integrated research, education, and workforce development partnerships with Idaho National Laboratory, industry collaborators, and university centers including the School of Computing and Advanced Research Computing Center. The lab maintains strong industry connections for technology transfer in advanced manufacturing. The CAMML laboratory operates within the University of Wyoming's R1 research infrastructure, maintaining collaborations with Vanderbilt University, University of Illinois, and national laboratories. Current projects involve metal 3D printing, frontal polymerization composites, and reduced-order modeling frameworks, supported by state-of-the-art computational resources. The team actively recruits graduate students for positions requiring expertise in computational mechanics, materials science, and programming.

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