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Farzad MashayekView profile

Professor

• Turbulent Reacting Flow
• Plasma Flow
• Electrostatic Atomization
• +9 more

Farzad Mashayek is a Professor and Department Head of Aerospace and Mechanical Engineering at the University of Arizona, College of Engineering. He is a member of the Graduate Faculty and leads the Computational Multiphase Transport Laboratory. His research integrates high-fidelity simulations, machine learning, and experimental validation across diverse domains in fluid dynamics and energy systems. Educational Background: PhD in Mechanical Engineering, State University of New York at Buffalo, Buffalo, NY MS in Mechanical Engineering, Sharif University of Technology, Tehran, Iran BS in Mechanical Engineering, Sharif University of Technology, Tehran, Iran His research interests include turbulent reacting flows, plasma dynamics, electrostatic atomization, solid-ion and lithium batteries, computational fluid dynamics, and machine learning applications in engineering. He employs high-order spectral element methods, phase-field modeling, and deep neural networks to study complex multiphysics phenomena such as drop impact, battery degradation, and turbulence modeling. The recent publications reflect a strong trend toward integrating machine learning with multiphysics simulations, particularly in battery safety (thermal runaway prediction), materials characterization (STEM image analysis), and fluid dynamics (modal analysis of turbulence). His work often involves collaboration with experimental groups to validate models, especially in dental aerosol suppression and electrohydrodynamics. Scientific Awards: Sustained Service Award, American Institute of Aeronautics and Astronautics (AIAA), Spring 2022 Best Presentation Award, The 20th International Conference on Computational Mathematics, Parallel and Distributed Computing, Summer I 2018 Dr. Mashayek has secured funding from NSF (GOALI program) for controlled coating via charged droplet deposition. He advises graduate students and postdoctoral researchers in computational mechanics and energy systems, fostering interdisciplinary research. He has contributed to engineering education, particularly during the pandemic, with active learning strategies in online instruction. He leads a dynamic research team focused on advancing simulation tools and applying them to real-world challenges in energy, manufacturing, and public health.

Gianluca IaccarinoView profile

Professor

• Scientific Computing
• Uncertainty Quantification
• Turbulence Modeling
• +6 more

Gianluca Iaccarino is a Professor of Mechanical Engineering at Stanford University and the Robert Bosch Chairholder. He serves as Director of the PSAAP Center and leads large-scale computational research initiatives in uncertainty quantification, exascale computing, and multiphysics simulations. His academic journey includes a PhD in Mechanical Engineering from Politecnico di Bari (2005), postdoctoral work at Stanford's Center for Turbulence Research, and progression from Research Engineer to full Professor. Education : PhD (Politecnico di Bari), MS/BS in Aeronautical Engineering (University of Naples) Research : Computational engineering, turbulence modeling, uncertainty quantification, biomedical fluid dynamics, and exascale-ready algorithms Publications : 15+ recent articles focus on turbulence modeling, data-driven simulations, and uncertainty quantification across diverse applications in aerospace, biomedical, and energy systems Awards : PECASE (2010), APS Fellow (2019), multiple best paper awards (AIAA, ASME), Terman Fellow (2007) Students : Advises doctoral and master's students in mechanical engineering and computational methods Leadership : Director of PSAAP Center (2014-present), Chair of Mechanical Engineering Department (2024-present)

Nikolaus A. AdamsView profile

Professor

• Aerodynamics
• Fluid Mechanics
• Numerical Methods
• +5 more

Prof. Dr. Nikolaus A. Adams is a full professor and Chair of Aerodynamics and Fluid Mechanics at the Technical University of Munich (TUM), affiliated with the TUM School of Engineering and Design. Born in 1963, he holds a doctorate from TUM (1993) and habilitation from ETH Zurich (1999). His research focuses on numerical methods, turbulent flows, microfluidics, and multiphase systems. He has held leadership roles, including Dean of the Faculty of Mechanical Engineering since 2023 and Vice Dean (2015–2016). Education: PhD from TUM (1993), habilitation from ETH Zurich (1999) Research interests include aerodynamics, fluid-structure interaction, and numerical techniques for compressible flows. His work spans high-speed aerodynamics and computational fluid dynamics (CFD). Awards include ERC Advanced Grants (GENUFASD 2023, NANOSHOCK 2015), the Gordon Bell Prize (2013), and Fellow of the American Physical Society (2011). Grants and leadership: Spokesperson of DFG SFB/TRR 40 (2008–2020), co-author of 'Large-Eddy Simulation for Compressible Flows' (2009), and editorial roles in J. Comput. Phys.

Hrvoje JasakView profile

Professor

• Computational Fluid Dynamics (CFD)
• Continuum Mechanics
• Numerical Simulation Methods
• +5 more

Hrvoje Jasak is a Professor of Continuum Physics at the Department of Physics (Cavendish Laboratory), University of Cambridge. He holds a fellowship at Christ’s College. His academic journey includes a BSc in Mechanical Engineering from the University of Zagreb (1992) and a PhD in CFD from Imperial College London (1996). Prior to academia, he held engineering roles at CD-adapco (now Siemens PLM), Nabla Ltd, and Ansys-Fluent Inc., contributing to CFD software development. His research focuses on numerical simulation methods, continuum physics, multiphase flows, naval hydrodynamics, and software development. He co-created OpenFOAM, chairs its Numerics Technical Committee, and leads the Computational Continuum Mechanics (CCM) research group within the Laboratory for Scientific Computing. His work integrates advanced numerical techniques like the partially rotating grid method, finite volume algorithms, and multiphysics coupling frameworks. Jasak is a seasoned developer with 25+ years of C++ expertise, having authored ~1 million lines of code. His group’s projects include the Naval Hydro Pack , fluid-structure interaction solvers, and the Eulerian multi-fluid model for dense sprays. He actively collaborates on international initiatives like the NUMAP-FOAM Summer School and the OpenFOAM community. His teaching spans MPhil programs, PhD supervision, and specialized CFD courses. Current research explores wave-ice interaction, lubricated contact modeling, and open-source software innovation. The CCM group’s work bridges academia and industry, addressing challenges in marine engineering, energy systems, and computational mechanics.

Iason SiderisView profile

Researcher

• Additive Manufacturing
• Advanced Materials Processing
• Path Planning Optimization
• +3 more

Dr. Iason Sideris is affiliated with ETH Zürich's Department of Neue Fertigungstechnologien (New Manufacturing Technologies), holding a Researcher position within the Professorship for Advanced Manufacturing. His work focuses on advancing additive manufacturing techniques, particularly in path planning optimization, temperature control, and material processing. He contributes to fields like Direct Energy Deposition, Wire-Arc Additive Manufacturing (WAAM), and data-driven finite volume methods. Key Research Areas: Additive Manufacturing, Thermal Modeling, Process Optimization, Materials Science Recent research emphasizes scalable path planning for temperature uniformity in AM processes, with publications addressing challenges in WAAM thermal management and real-time simulation methods. His work combines computational modeling with experimental validation to enhance manufacturing efficiency and material properties.

Peter K. KitanidisView profile

Professor

• Groundwater Flow
• Hydrologic Modeling
• Inverse Problems
• +3 more

Peter K. Kitanidis is a Professor in the Department of Civil and Environmental Engineering and the Institute for Computational and Mathematical Engineering at Stanford University . His research focuses on groundwater flow , hydrologic forecasting , and stochastic inverse modeling , with applications to pollutant remediation and CO₂ storage monitoring . Education : Diploma, National Technical University of Athens (1974) M.S., MIT (1976) Ph.D., MIT (1978) Research Interests : Groundwater modeling and contaminant transport Hydraulic tomography and aquifer characterization Stochastic methods for uncertainty quantification Bioremediation and enhanced in-situ pollutant decay Dilution and mixing processes in heterogeneous media Real-time river flow forecasting Scientific Awards : L.G. Straub Award (1979) W.L. Huber Research Prize (1994) ISI Highly Cited Researcher (2001) AGU Hydrologic Sciences Award (2011) ASCE Pioneers in Groundwater Lecturer (2011) Advising and Grants : Advised 20+ PhD and MS students (1978–2018) Principal investigator on NSF, EPA, and DOE-funded projects Developed software for groundwater data analysis and CO₂ monitoring Contributed to bioremediation protocols and hydraulic tomography algorithms Labs and Teams : Kitanidis Laboratory for groundwater crisis solutions Collaborated with Oak Ridge National Laboratory and Stanford Hydrogeology Group Mentored postdocs (2000–2017) in reactive transport and inverse modeling

Ronaldo I. BorjaView profile

Professor

• Theoretical Solid Mechanics
• Computational Solid Mechanics
• Geomechanics
• +6 more

Ronaldo I. Borja is a Professor in the Department of Civil and Environmental Engineering at Stanford University's School of Engineering. His academic career spans decades of research and teaching in theoretical and computational solid mechanics, geomechanics, and geosciences. He teaches undergraduate, graduate, and doctoral level courses including Geotechnical Engineering (CEE 101C), Mechanics and Finite Elements (CEE 281), Computational Poromechanics (CEE 314), and Plasticity Modeling and Computation (CEE 315). Professor Borja's research focuses on theoretical and computational solid mechanics, with particular emphasis on geomechanics and geosciences. His work includes the development of multi-scale discontinuity frameworks for crack and fracture propagation utilizing strong discontinuity and extended finite element methods; solution techniques for multi-physical processes such as coupled solid deformation-fluid diffusion in saturated and unsaturated porous media; stabilized finite element methods for solid/fluid interaction and nonlinear contact mechanics; and nanometer-scale characterization of the inelastic deformation and fracture properties of shales. His research spans multiple projects including shale characterization, poromechanics, and large deformation inelasticity. His recent publications demonstrate expertise across computational mechanics, geomechanics, and materials science, with a focus on finite element methods, constitutive modeling, and multi-scale analysis. His work bridges theoretical developments with practical applications in geotechnical engineering and earth sciences. 2016 ASCE Maurice A. Biot Medal for work in computational poromechanics Professor Borja serves as editor of two leading journals in his field: the International Journal for Numerical and Analytical Methods in Geomechanics and Acta Geotechnica. He has also authored the textbook 'Plasticity Modeling and Computation' published by Springer. His research is supported by multiple projects examining shale mechanics, poromechanics in unsaturated porous media, and large deformation inelasticity in crystalline materials.

• Materials Science
• Computational Materials Science
• Battery Technology
• +6 more

R. Edwin García is a Professor at the School of Materials Engineering at Purdue University, where he has been faculty since 2005. He holds appointments in the Materials Engineering department within Purdue's College of Engineering, specifically in the School of Materials Engineering located in the Neil Armstrong Hall of Engineering at Purdue's West Lafayette campus. His educational background includes: B.S. in Physics from the National University of Mexico (1996) M.S. in Materials Science and Engineering from Massachusetts Institute of Technology (2000) Ph.D. in Materials Science and Engineering with a minor in Applied Mathematics from Massachusetts Institute of Technology (2003) Professor García's research focuses on the design of materials and devices through the development of a fundamental understanding of the solid state physics of individual phases, their short and long range interactions, and associated microstructural properties and time evolution. His current research emphasizes establishing relationships between material properties and resultant performance and degradation in electrochemical systems. He integrates computational approaches ranging from kinetic Monte Carlo, phase field and level set methods, to finite elements, finite volumes, and symbolic computing. His work particularly addresses microstructure design, crystallographic texture, and grain boundary science and engineering to control the topology of underlying phases and establish practical relations between processing, microstructure, and material properties. His recent publications demonstrate a strong focus on lithium-ion battery technology, ferroelectric materials, and computational modeling of material behaviors. The research trends show increasing integration of machine learning with traditional computational methods, exploration of novel sintering techniques like flash sintering, and deeper investigation into the fundamental mechanisms of material degradation in energy storage systems. His work spans multiple length scales from atomistic to continuum modeling, reflecting a comprehensive approach to materials design and analysis. Professor García teaches several courses including MSE 230 (Structure and Properties of Materials), MSE 350 (Thermodynamics of Materials), MSE 597G (Modeling and Simulation of Materials), MSE 597I (Introduction to Computational Materials), and MSE 597N (Physical Properties of Crystals). He mentors graduate students in areas related to computational materials science, battery technology, and microstructural evolution. His research group, the Laboratory of Computational Microstructures, focuses on developing home-grown analytical theories and algorithms to resolve relevant time and length scales in materials systems. The group's work has significant implications for portable power sources, including rechargeable batteries and fuel cells, as well as for ferroelectric ceramic applications.

Anand N.K.View profile

Professor

• Physics-Informed Neural Networks
• Finite Volume Techniques
• Reduced Order Modeling
• +5 more

N.K. Anand is a Distinguished Professor of Mechanical Engineering at Texas A&M University, holding the James J. Cain III Regents Professorship. He leads research in advanced computational methods and thermal-hydraulic systems, with affiliations to Multidisciplinary Engineering and Nuclear Engineering programs. His work focuses on physics-informed machine learning, finite volume methods, and aerosol transport in nuclear reactor contexts. Education: PhD (Mechanical Engineering, Purdue University, 1983), M.S. (Kansas State University, 1979), and B.E. (Bangalore University, 1978). Awards include the ASME James Harry Potter Gold Medal (2020) and multiple teaching/administrative excellence awards from Texas A&M. Research emphasizes fluid dynamics modeling (e.g., PINNs for periodic flows, turbulent deposition studies), heat pipe systems, and nuclear reactor thermal-hydraulics. His Versatile Test Reactor (VTR) contributions include cartridge loop designs and aerosol transport experiments. Active in high-temperature reactor safety, with facilities studying pebble beds, helical coil exchangers, and HTGR upper plenum dynamics. Publications span physics-informed ML applications, finite volume techniques, and nuclear thermal systems. Grants supported development of advanced CFD tools and reactor safety infrastructure. His lab collaborates on international nuclear energy projects and emerging AI-driven simulation methodologies.

Levent Burak KaraView profile

Professor

• Machine Learning
• Artificial Intelligence
• Computational Design
• +12 more

Levent Burak Kara is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in the Robotics Institute. He is a leading researcher in AI-driven computational design, additive manufacturing, and intelligent engineering systems, leading the Visual Design and Engineering Lab (VDEL) at CMU. Education: B.S., Mechanical Engineering, Middle East Technical University (1998) M.S., Mechanical Engineering, Carnegie Mellon University (2000) Ph.D., Mechanical Engineering, Carnegie Mellon University (2005) His research focuses on integrating machine learning, optimization, and geometric modeling to revolutionize engineering design and manufacturing. Key areas include topology optimization, CAD intelligence, digital twins, generative design, bioengineering, and electronic design automation. His work enables automation of traditionally labor-intensive design processes using deep learning and reinforcement learning. His recent publications reveal a strong trend toward physics-informed surrogate modeling, real-time simulation, manufacturability prediction, and AI-driven automation in mechanical, biomedical, and electronic systems. These works frequently appear in top journals such as Journal of Mechanical Design and Journal of Applied Mechanics , and at premier conferences like NeurIPS and DAC. Scientific Awards: National Science Foundation CAREER Award ASME Design Automation Society Young Investigator Award Google AI for Social Good Impact Scholar Kara advises several Ph.D. students and has secured significant funding from federal agencies such as the NSF and the U.S. Army Research Laboratory, as well as collaborations with industrial leaders including Cadence Design Systems and NVIDIA. His research is also supported by CMU’s NextManufacturing Center and the Critical Technology Initiative. He is actively involved in developing intelligent design systems that leverage AI to automate product design, optimize manufacturing processes, and improve medical diagnostics, particularly in oral cancer screening and organ preservation. His lab, VDEL, is a hub for innovation in AI-enabled engineering.

• Computational Mathematics
• Numerical Analysis
• Tsunami Modelling
• +5 more

Stephen Roberts is a Professor at the Australian National University (ANU) in the College of Science, Department of Mathematics. He is the lead developer of the ANUGA open-source hydrodynamic modeling software, which simulates dam breaks, floods, and tsunamis for governments and engineers. Roberts has made significant contributions to computational mathematics, particularly in numerical methods for partial differential equations, sparse grid data fitting, and finite element approximations scaling to millions of data points. MSc, Flinders University (1980) PhD, University of California, Berkeley (1985) His research interests include: Computational methods for shallow water wave equations Development of Python-based scientific computing frameworks Global sensitivity analysis and uncertainty quantification Adaptive mesh algorithms for fluid dynamics Recent publications focus on energy-stable numerical schemes, multiscale flood simulation, and convergence analysis in sensitivity methods. Roberts actively collaborates with environmental agencies and has led major computational science education programs at ANU. Stephen serves as Treasurer of the Computational Mathematics Group (ANZIAM) and leads projects in: Parallelization of hydrodynamic models CO2 leak detection via atmospheric measurements Optimization of sparse grid combinations His work combines theoretical advancements with real-world applications in disaster risk reduction and climate policy.

Abbas SamaniView profile

Professor

• Biomedical Engineering
• Medical Imaging
• Computational Modeling
• +5 more

Prof. Abbas Samani is a Professor at the Department of Electrical and Computer Engineering and holds a joint appointment in the Department of Medical Biophysics at Western University . He is a core faculty member of the Biomedical Engineering Graduate Program and an Associate Scientist at Imaging Research Laboratories of Robarts Research Institute . His academic journey includes a Ph.D. from the University of Waterloo, an M.Sc. from the University of Tehran, and a B.Sc. from Amirkabir University of Technology. His research focuses on biological tissue computational modeling and its applications in medical imaging, intervention, and image analysis . He develops computer/image-assisted tools for minimally invasive disease diagnosis and therapy , targeting heart disease, cancer, and lung disease . Key projects include myocardium biomechanical modeling , handheld medical devices for breast cancer screening , and lung disease diagnostics via CT image segmentation . His recent publications emphasize ultrasound elastography , finite element modeling , and inverse problems in biomechanics , primarily in journals like IEEE Transactions on Computational Imaging and Translational Oncology . His work spans both computational modeling and medical device development . Selected Graduate Supervision : Ph.D. Candidates : Seyed Hassan Haddad, Elham Karami, Seyed Mohammad Hesabgar Graduated Ph.D. Students : Ali Sadeghi Naini, Seyed Reza Mousavi M.Sc. Students : Cristian Linte, Patrick Courtis, Joseph O'Hagan, Hatef Mehrabian, Hirad Karimi, Hosein Amooshahi, Seyed Mohammad Hesabgar, Nastaran Ghadarghadr, Shadi Shavakh, Ehsan Salamati, Ehsan Omidi Teaching Contributions : Graduate: BME9519B/CAMI9519B/ECE9202B/ECE9022B - Advanced Image Processing and Analysis , MBP9530A - Human Biomechanics and Biomedical Applications Undergraduate: ECE4438B - Advanced Image Processing and Analysis , ES1050 - Introductory Engineering Design and Innovation Studio , MBP3330F - Human Biomechanics and Biomedical Applications Research Affiliations : Robarts Research Institute - Associate Scientist at Imaging Research Laboratories Western University - Core Faculty, Biomedical Engineering Graduate Program

• Computational Fluid Dynamics (CFD)
• Smoothed Particle Hydrodynamics (SPH)
• Multiphase Flow Modeling
• +4 more

Fabian Fritz holds an M.Sc. degree and works at the Technical University of Munich (TUM) within the Chair of Aerodynamics and Fluid Mechanics . His research focuses on computational fluid dynamics (CFD) and numerical simulation of multiphase flows, particularly using Smoothed Particle Hydrodynamics (SPH) . He collaborates on projects like PBF-LB/M (additive manufacturing) and contributes to Lagrangian fluid mechanics benchmarking frameworks. Research Trends: His publications emphasize numerical methods (SPH, level-set, finite-volume), multiphase flow modeling , heat transfer , and thermoacoustic stability . Recent work includes hardware-agnostic code optimization and adaptive mesh refinement techniques. Education: Completed a master’s thesis on Diffusive-Interface Modeling of Multiphase Flows with Surface-Tension Effects , supervised by P.D. Dr.-Ing. habil. Stefan Adami.

Dan JiaoView profile

Professor

• Computational Electromagnetics
• Computational Multiphysics
• Electronic Design Automation (EDA)
• +8 more

Prof. Dan Jiao is the Synopsys Professor of Electrical and Computer Engineering at Purdue University's Elmore Family School. She leads the Rapid-Heterogeneous Integration (Rapid-HI) Design Institute and serves as Editor-in-Chief of the IEEE Journal on Multiscale and Multiphysics Computational Techniques. Her research focuses on computational electromagnetics, multiphysics modeling, and AI-driven design automation for advanced integrated circuits and quantum systems. She has held academic positions since 2005, progressing from Assistant to Full Professor, and has extensive industry experience at Intel Corporation (2001–2005). Education: PhD in Electrical Engineering, University of Illinois at Urbana-Champaign (2001) Senior Staff Engineer at Intel Corporation (2001–2005) Research Interests: Fast numerical methods for large-scale electromagnetic analysis AI/ML integration in design automation (EDA/MDA) Quantum circuits and spin qubit systems Heterogeneous integration and advanced packaging Multiphysics co-simulation for nano-scale devices Signal/power integrity in high-speed systems Key Projects: Leads the NSTC AIDRFIC program (first NSTC R&D Jump Start project), the DARPA NGMM Rapid-HI Design Institute, and the GENIE-RFIC generative design tool initiative. Also directs the Consortium for Electromagnetic Science and Technology. Awards & Honors: 2022 ACES Computational Electromagnetics Award IEEE Fellow (2016) Intel Outstanding Researcher Award (2019) MTT-S Distinguished Microwave Lecturer (2020–2023) 2013 Schelkunoff Prize Paper Award Advising & Grants: Advised over 30 PhD/master's students and led projects funded by NSF, DARPA, Intel, SRC, and industry partnerships. Key grants include NSF CAREER (2008), ONR Young Investigator (2006), and multiple industry-sponsored initiatives. Labs & Teams: Rapid-HI Design Institute (DARPA NGMM) Quantum device co-design group Multiphysics modeling team

Dond Asha KisanView profile

Assistant Professor

• Numerical Analysis
• Computational Mathematics
• Finite Element Methods
• +4 more

Dond Asha Kisan is an Assistant Professor at the School of Mathematics , Indian Institute of Science Education and Research Thiruvananthapuram (IISER TVM). His research focuses on numerical analysis and computational mathematics , particularly in finite element methods for partial differential equations. He can be contacted at ashadond@iisertvm.ac.in or via phone at +91 (0)471-2778247. PhD : Mathematics, Indian Institute of Technology Bombay M.Sc. : Mathematics, K.T.H.M. College, Nashik Kisan's research spans adaptive finite element methods , stabilized formulations for convection-diffusion problems , and optimal control governed by Stokes equations . His work includes convergence analysis, nonconforming discretizations, and hybrid numerical schemes. Recent publications (2023-2025) address stochastic modeling in liquid crystal physics, advanced WENO schemes, and adaptive algorithms for control problems. Scientific Awards : No explicit awards mentioned in the data, though he held prestigious postdoctoral fellowships including National Post-Doctoral Fellowship and NBHM Post-Doctoral Fellowship. Kisan has extensive teaching experience , including MATLAB workshops and undergraduate course assistantships. He has presented at major international conferences like ICIAM and Hyperbolic Problems, demonstrating global engagement in computational mathematics.