Kamal H. Khayat serves as the Jones Professor of Civil Engineering at Missouri University of Science and Technology and directs the Center for Infrastructure Engineering Studies (CIES), focusing on advancing concrete technology for sustainable infrastructure development. His research spans high-performance concrete (HPC), ultra-high-performance concrete (UHPC), self-consolidating concrete (SCC), and concrete rheology, with specialized expertise in 3D printing applications, fiber reinforcement systems, and shrinkage mitigation techniques. He investigates innovative materials like superabsorbent polymers and alternative binders to enhance durability and sustainability in concrete infrastructure. Analysis of his recent publications reveals dominant trends in digital fabrication of concrete, particularly 3D printing optimization and rheological modeling for structural build-up. His work increasingly integrates machine learning for material property prediction while emphasizing eco-friendly formulations using recycled aggregates and carbon-mineralization techniques. As Director of CIES, Khayat leads multidisciplinary research initiatives in infrastructure materials engineering, overseeing projects related to concrete rehabilitation, sustainable construction methods, and advanced material characterization techniques for civil infrastructure systems.
Professor Moncef Gabbouj is a distinguished academic and researcher currently serving as Professor of Signal Processing at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences, Tampere University, Finland. Previously, he held the same position at Tampere University of Technology before the merger in 2019. He has also held visiting professorships at prestigious institutions including Hong Kong University of Technology and Science, University of Southern California, and Purdue University. Ph.D. and MSc. in Electrical Engineering from Purdue University, USA (1989 and 1986) B.Sc. in Electrical Engineering from Oklahoma State University, USA (1985) Prof. Gabbouj's research spans multiple domains within signal and image processing, with a strong focus on machine learning applications. His primary research interests include artificial intelligence, machine learning, Big Data analytics, multimedia content-based analysis, indexing and retrieval, nonlinear signal and image processing, voice conversion, and video processing and coding. His work bridges theoretical advancements with practical applications across various industries, particularly in multimedia communications and biomedical applications. His extensive publication record demonstrates a clear evolution from traditional signal processing techniques toward more sophisticated machine learning and deep learning approaches. Recent work shows increasing focus on convolutional neural networks for various applications including ECG classification, video processing, financial time-series analysis, and image recognition tasks, reflecting the broader trend in the field toward deep learning methodologies while maintaining strong foundations in signal processing theory. IEEE Fellow (2011) Member, Finnish Academy of Science and Letters (2014) Knight, First Class, of the Order of the White Rose of Finland (2006) Nokia Foundation Recognition Award (2005) Nokia Foundation Visiting Professor Award (2012) Finnish Cultural Foundation for Art and Science Award (2017) TUT Foundation Grand Award (2015) Prof. Gabbouj has supervised 64 doctoral and 72 Master's theses, demonstrating his significant contribution to academic mentoring. His research has been supported by substantial funding, including research grants totaling 8.5 million Euro (2001-2015). He has served as Academy of Finland Professor during 2011-2015 and has been involved in numerous EU research projects including Horizon, ESPRIT, HCM, IST, COST, Tempus and Erasmus programs. As Editor, Guest Editor or member of the Editorial Board of 6 international scientific journals, he has significantly influenced the academic discourse in his field. He leads the Signal Analysis and Machine Intelligence (SAMI) research group at Tampere University and serves as the Finland Site Director of the NSF IUCRC funded Center for Visual and Decision Informatics. His research unit focuses on applying advanced machine learning techniques to solve complex problems in signal processing, computer vision, and multimedia analytics, with applications ranging from healthcare to multimedia communications and financial analysis.
Nishant Garg is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign. His research focuses on sustainable construction materials, particularly cement-based systems, leveraging advanced characterization techniques such as X-ray scattering, neutron diffraction, and Raman imaging. His work addresses environmental sustainability through innovations in low-carbon materials, waste utilization, and durability enhancement. Education: Ph.D. in Nanoscience, Aarhus University (2015) M.S. in Civil Engineering Materials, Iowa State University (2012) B.E. and Diploma in Civil Engineering, Thapar Institute of Engineering & Technology and Chandigarh College of Eng. & Tech. (2010, 2007) Research Interests: Sustainable cement chemistry, material characterization, carbonation processes, and development of eco-friendly construction materials. His lab, the Garg Group, emphasizes multi-scale analysis (nano-to-macro) to bridge fundamental science and practical applications. Key Contributions: Innovations include the UR2 test for cement reactivity, SorpVision for automated sorptivity assessment, and VR tools for materials education. These advances aim to reduce costs, improve material performance, and promote circular economy practices. Awards and Roles: Dean’s Award for Excellence in Research (2025) Member, Transportation Research Board AKM 50 Committee (2025–Present) Recipient of American Ceramic Society’s Stephen Brunauer Award (2021) Advising and Grants: Actively recruiting MS/Ph.D. students. Leads initiatives on low-carbon concrete, funded by NSF and industry collaborations. Serves on CEE advisory committees and graduate admissions. Labs/Teams: The Garg Group integrates interdisciplinary approaches, collaborating with materials scientists, engineers, and data scientists to tackle global infrastructure challenges.
Professor David R. Clarke is the inaugural Extended Tarr Family Professor of Materials at Harvard School of Engineering and Applied Sciences. He is a Senior Fellow of the Hong Kong Institute for Advanced Study (HKIAS) and member of the US National Academy of Engineering. PhD in Physics (University of Cambridge) B.Sc. in Applied Sciences (Sussex University) ScD (University of Cambridge) His research spans fundamentals and applications of ceramics, metals, semiconductors, and polymers, focusing on mechanical properties, thermal barrier coatings, dielectric elastomers, oxidation fundamentals, and microelectronics reliability. Recent work explores electro-adhesive forces and nanopore evolution in yttria-stabilized zirconia. With over 500 publications in journals like Nature and Advanced Materials, Clarke's work has been cited >50,000 times (h-index 107). He holds 13 patents and has advised students across MIT, UC Berkeley, and Harvard. 2008 Japanese NIMS Award 1993 Humboldt Senior Scientist Award Distinguished Life Member, American Ceramic Society Teaching includes undergraduate courses on heat transfer and materials design, plus graduate courses on dislocations and composites. His lab recently worked on quantum dot displays and fatigue crack sensing technologies.
Partha P. Mukherjee is a Professor of Mechanical Engineering and Associate Head for Research at Purdue University's School of Mechanical Engineering. His research focuses on energy storage systems (batteries, fuel cells), mesoscale physics, and materials interactions. He holds a Ph.D. from Pennsylvania State University (2007), an M.S. from IIT Kanpur (1999), and a B.S. from North Bengal University (1997). Research Interests include: Energy storage and conversion mechanisms Mesoscale physics and stochastic modeling Reactive transport in materials systems Thermodynamics and heat/mass transfer Notable Awards: Scialog Fellow (2017) Dean of Engineering Excellence Award (2017) Emerging Investigator distinction (2016) Morris E. Foster Faculty Fellowship (2016) His research group operates the Energy and Transport Sciences Laboratory (ETSL), advancing battery safety, solid-state battery architectures, and electrochemical systems. Recent work emphasizes solid-state electrolyte interfaces and fast-charging dynamics.
Bo Zhu is an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology. His research focuses on computational approaches for complex physical systems, including fluid dynamics, topology optimization, and robotics control. He holds a Ph.D. from Stanford University and completed postdoctoral research at MIT CSAIL. He has been recognized with the NSF Career Award (2022) and multiple best paper awards at SIGGRAPH conferences. Education: B.E.-M.S., Software Engineering, Shanghai Jiao Tong University Ph.D., Computer Science, Stanford University Postdoc, EECS, MIT Research Interests: Develops numerical algorithms and machine learning techniques to simulate fluidic systems, soft materials, and multi-scale phenomena. His work emphasizes vorticity preservation, real-time simulation, and physics-based AI integration. Key Contributions: Pioneered Particle Flow Map (PFM) methods for fluid simulation, developed open-source libraries like SimpleX and PFM Hub, and contributed to projects like Genesis physics engine. Over 50 peer-reviewed publications in top venues (SIGGRAPH, NeurIPS, IEEE TVCG). Awards: NSF Career Award (2022) Best Paper Honorable Mention (SIGGRAPH 2025) Best Paper Award (SIGGRAPH Asia 2024) Grants & Projects: Leads NSF-funded research on Physical AI Design, collaborating with Sandia National Labs on real-time CFD solvers. Active in open-source software development for computational physics and graphics.
Associate Professor Judy Hart is a materials scientist at the School of Materials Science & Engineering, UNSW Sydney , specializing in the development of semiconducting materials for renewable energy applications. Her work integrates computational (DFT) and experimental approaches to understand composition-property relationships in systems like solid solutions , heterostructures , and doped materials for photocatalysis and solar cells . She leads projects funded by ARC Discovery and Linkage grants , including work on photo-electro-catalysis systems and stabilizing ceramic materials . Education: PhD in Materials Engineering (Monash University, 2007), BEng (Materials) (Monash, 2002) Professional Experience: Senior Lecturer (UNSW, 2017–), Lecturer (UNSW, 2013–2017), University of Bristol (2007–2012) Research Interests Her research focuses on designing materials for renewable energy , particularly photoelectrochemical water splitting and organic oxidation reactions . Key areas include Density Functional Theory (DFT) , defect engineering , band gap tuning , and nanostructured materials . She investigates ferroelectric polarization effects , metal oxide heterostructures , and stability of battery components , with applications in hydrogen production , CO2 conversion , and advanced battery materials . Scientific Awards Ramsay Memorial Fellowship (University of Bristol, 2007–2009) Teaching Contributions She is co-author of the 1st Australian & New Zealand edition of "Materials Science and Engineering: An Introduction" , and teaches courses on computational materials science , corrosion-resistant surfaces , mechanical behavior of metals , and materials design .
Sebastian Kube is an Assistant Professor in the Department of Materials Science & Engineering at the University of Wisconsin-Madison's College of Engineering, with additional affiliation in Mechanical Engineering. His research accelerates alloy development through autonomous discovery methods combining robotics, data science, and advanced characterization. Dr. Kube's educational background includes: Postdoctoral Researcher (2023), University of California Santa Barbara (Tresa Pollock Lab) PhD (2021), Yale University (Jan Schroers Lab) BS (2016), Giessen University His work focuses on refractory multi-principal element alloys for extreme environments (>1300°C) and metallic liquid structure-property relationships. He develops autonomous platforms to navigate complex parameter spaces, targeting improved glass forming ability and rapid solidification processing through B2 precipitation strategies and novel characterization techniques. Recent publications emphasize refractory high-entropy alloys, BCC-B2 systems, and metallic glasses, integrating experimental and computational approaches to decode phase stability, deformation mechanisms, and glass formation for accelerated materials design. Major recognitions include: 2025 DARPA Young Faculty Award 2024 ARPA-E IGNIITE Early Career Award RCSA Scialog Fellowship for Automating Chemical Laboratories He mentors graduate students through thesis courses (M S & E 790/890/990) and leads the Autonomous Alloy Discovery Lab, which develops robotic systems for high-throughput experimentation. Current projects target next-generation turbine alloys and environmentally sustainable materials for aerospace, energy, and defense applications.
Smrutiranjan Parida is a Professor in the Department of Metallurgical Engineering and Materials Science at the Indian Institute of Technology Bombay (IIT Bombay), where he has been serving since May 2021, previously as an Associate Professor from 2016 to 2021. He leads the Corrosion and Advanced Materials Laboratory (CAML), a multidisciplinary research group focused on corrosion science and advanced materials development. Education: Ph.D., University of Saarlandes, Saarbruecken, Germany, 2007 M.Tech, IIT Kharagpur, 2002 His research is centered on corrosion science, electrochemical energy storage, and functional nanomaterials . Key interests include supercapacitors, electrocatalysts, smart multifunctional coatings, corrosion-resistant alloys, and the application of nanotechnology in corrosion mitigation. His work bridges fundamental electrochemistry with practical industrial applications. The recent publications highlight a strong focus on nanomaterials for energy and corrosion protection , including carbon nano-onions, nanoporous metals, graphene composites, and smart inhibitor delivery systems. Themes such as binder-free electrodes, green synthesis, and in-situ characterization are prominent, reflecting a commitment to sustainable and high-performance materials. Scientific Awards: German Academic Exchange Service (DAAD) fellowship, IFW Dresden, Germany, 2002 Prof. Parida has secured significant research funding as Principal Investigator (PI) from agencies like SERB-DST, ONGC, and IIT Bombay's IRCC. He has also contributed as Co-PI in large projects such as the Centre of Excellence in Steel Technology (Ministry of Steel) and the DST-FIST 'Materials for Energy and Sensors' program. His grants span corrosion inhibition in oil pipelines, nanostructured alloys, biomaterials, and advanced laboratory infrastructure development. The Corrosion and Advanced Materials Laboratory (CAML) serves as the primary hub for his research team, fostering innovation in surface engineering and electrochemical devices.
Jinjin Ha serves as an Assistant Professor in the Department of Mechanical Engineering at the University of New Hampshire, with her office located in Kingsbury Hall, Room W101a, Durham, NH. She teaches core mechanical engineering courses including Statics (ME 525), Materials Processing in Manufacturing (ME 742/842), Theory of Plasticity (ME 927), and Doctoral Research (ME 999), demonstrating active engagement in both undergraduate and graduate education. Her research program integrates computational mechanics with advanced manufacturing, focusing on: Machine learning applications for plasticity modeling and fracture prediction Deformation mechanics in incremental sheet forming processes Martensitic phase transformations in stainless steels Anisotropic material behavior and yield function development Ductile fracture characterization of titanium and aluminum alloys Analysis of her 2023-2024 publications reveals a decisive shift toward AI-driven mechanics, where neural networks solve complex constitutive modeling challenges in metal forming. This interdisciplinary approach bridges fundamental material science with industrial manufacturing optimization, particularly in toolpath design and phase transformation control. No scientific awards were documented in the provided profile information. While doctoral research supervision is indicated through ME 999 course listings, specific student names, grant funding details, laboratory facilities, or collaborative team structures were not disclosed in the available text.
Mohsen Taheri Andani is an Assistant Professor in the Department of Mechanical Engineering at Texas A&M University. He holds a Ph.D. in Mechanical Engineering from the University of Michigan (2022), an M.Sc. in Materials Science and Engineering from the University of Michigan (2018), an M.Sc. in Mechanical Engineering from the University of Toledo (2015), and a B.Sc. in Mechanical Engineering from Isfahan University of Technology (2012). His research focuses on the processing-structure-properties relationships of advanced materials, additive manufacturing, physical/ mechanical metallurgy, and mechanical behavior of materials, with a particular emphasis on grain boundary engineering and crystallographic texture control in metals processed via additive manufacturing methods. Dr. Andani has received prestigious awards including the 2022 Robert M. Caddell Memorial Award for Research, the 2021 Richard and Eleanor Towner Prize for Outstanding Ph.D. Research, and the 2020 Ivor K. McIvor Award, all from the University of Michigan. His work bridges fundamental materials science with advanced manufacturing technologies, aiming to optimize material performance through multiscale control of microstructures. His research group, the Multiscale Manufacturing and Mechanics of Materials (M4) Lab, explores the interface between additive manufacturing and materials mechanics. Current projects include the Center for Scientific Machine Learning for Material Sciences (AFSOR), reducing qualification time in additive manufacturing (America Makes), and structural evaluation via non-contact sensors (DARPA). He actively seeks motivated Ph.D. students for Fall 2025 and welcomes undergraduate/master’s students to join his team. Dr. Andani’s publications emphasize experimental and computational studies of microstructural evolution in additively manufactured metals, including grain boundary effects on dislocation dynamics, crystallographic texture control in NiTi alloys, and thermomechanical property optimization of materials like 316L stainless steel and Cu-Cr-Zr alloys. His work integrates in situ characterization techniques with advanced modeling to predict and enhance material performance.
Teng-Fong Wong is a Research Professor in the Department of Geosciences at Stony Brook University, where he has been a faculty member since 1982. His research focuses on the intersection of rock mechanics, earthquake processes, and environmental applications, making significant contributions to understanding deformation mechanisms in geological materials. Education: Sc.B., Brown University, 1973 M.S., Harvard University, 1976 Ph.D., Massachusetts Institute of Technology, 1981 Research Interests: Professor Wong's research centers on rock mechanics with emphasis on earthquake mechanics, energy resources, and environmental applications. He investigates both phenomenological and micromechanical aspects of rock deformation and fluid flow using an integrated approach combining high-pressure deformation experiments, quantitative microstructure characterization, and theoretical analysis. His work spans brittle-ductile transitions in porous rocks, permeability evolution, strength properties of fault zone materials from SAFOD and TCDP drilling projects, and submarine groundwater discharge systems. Publication Trends: Wong's recent publications (2006-2008) demonstrate a consistent focus on strain localization mechanisms in porous rocks, particularly examining compaction bands and deformation bands in sandstones. His work integrates advanced imaging techniques (X-ray radiography, CT scanning) with mechanical testing to understand the micromechanics of rock failure. A significant thread connects his research on fault zone properties from major drilling projects (SAFOD, TCDP) with fundamental rock deformation processes. Scientific Recognition: U.S. Patent 6,874,371 for Ultrasonic Seepage Meter (2005) U.S. Patent 7,107,859 for Ultrasonic Seepage Meter (2006) Co-author of "Experimental Rock Deformation - The Brittle Field" (2nd Edition, Springer-Verlag, 2005) Professional Activities: Professor Wong maintains an active international research profile with numerous visiting appointments including at Australian National University, MIT, ETH Zurich, and institutions in China and France. His work involves extensive collaboration with USGS and international research teams on major fault zone drilling projects. He has developed specialized equipment like the ultrasonic seepage meter for measuring submarine groundwater discharge. Research Infrastructure: Wong's laboratory utilizes advanced capabilities including high-pressure deformation equipment, 3D visualization through laser scanning confocal microscopy and synchrotron microCT, and integrates these with analytic modeling and numerical simulation techniques (finite element and discrete element methods) to investigate micromechanics of dilatant and compactant failure in geological materials.
Professor Iwona M. Jasiuk is a multi-disciplinary academic affiliated with the University of Illinois, holding professorships in Mechanical Science and Engineering, Biomedical and Translational Sciences, Bioengineering, Aerospace Engineering, and other departments. She is also affiliated with the National Center for Supercomputing Applications (NCSA), Beckman Institute for Advanced Science and Technology, and the Carl R. Woese Institute for Genomic Biology. Her research focuses on composite materials, bio-inspired structures, additive manufacturing, and computational mechanics, with a strong emphasis on integrating artificial intelligence into materials science. Her work spans topics such as material characterization, metamaterials design, and radiation effects on materials. Notable research areas include thin-ply composites, lattice structures derived from geometric principles, and the mechanical properties of bio-inspired systems like equine hoof walls. She has pioneered the use of deep learning networks for predicting material behavior in complex systems. Professor Jasiuk has received prestigious awards, including the ASME Fellow, SES Fellow, and Vebleo Scientist Award. Her research is supported by collaborations across engineering, biology, and computational fields, leveraging advanced facilities like NCSA for high-performance computing.
Mohamed Shaat is an Assistant Professor of Mechanical Engineering in the Engineering Department at St. Mary's University, San Antonio, Texas. Holding a Ph.D. from New Mexico State University (2017), he previously served as Assistant Professor at Abu Dhabi University (2019-2021) and held postdoctoral positions at Southern Methodist University (2022-2024) and Boston University (2021-2022). His research bridges energy storage systems, active matter physics, and advanced materials engineering. His educational foundation includes: Ph.D. in Mechanical Engineering, New Mexico State University, 2017 M.Sc. in Mechanical Engineering, New Mexico State University, 2016 M.Sc., Zagazig University (Egypt), 2012 B.Sc., Zagazig University (Egypt), 2007 Dr. Shaat's research program focuses on interdisciplinary innovation in energy storage (SOFCs & ASSBs), mechanics of active matter, nano-confined fluids, chiral metamaterials, and topological/non-Hermitian mechanics. He integrates machine learning with continuum mechanics to optimize electrochemical systems and additive manufacturing, exploring nontraditional phenomena in complex materials for next-generation engineering applications. Analysis of his 60+ journal articles reveals a dominant trajectory in nonlocal elasticity theory and topological mechanics, with increasing integration of machine learning (2020-2024). His work spans nanostructure mechanics, metamaterial design, and energy storage optimization, demonstrating consistent innovation in theoretical frameworks for complex material systems. His scholarly recognition includes: World's Top 2% Scientist (Stanford University, Mechanical Engineering & Transports, since 2019) Outstanding Graduate Award, New Mexico State University (2017) Merit-Based Enhancement Fellowship, New Mexico State University (2017) Best Master's Thesis Award, Zagazig University (2013) Committed to academic service, Dr. Shaat serves on the editorial board of Scientific Reports and as Specialty Associate Editor for Frontiers in Mechanical Engineering. His extensive peer review for Nature, Nature Communications, and Applied Physics Letters reflects his field authority. While specific grant details aren't disclosed, his postdoctoral appointments and publication volume indicate successful research funding. His teaching includes Materials Engineering and Materials Laboratory courses, emphasizing hands-on student mentorship. Though laboratory infrastructure isn't explicitly detailed, his research scope suggests computational modeling expertise and likely collaboration with experimental teams for materials characterization in energy storage and metamaterials development.
Marc De Graef is the John and Claire Bertucci Distinguished Professor of Materials Science and Engineering at Carnegie Mellon University (CMU). He leads the J. Earle and Mary Roberts Materials Characterization Laboratory and is affiliated with the Materials Science and Engineering Department within the College of Engineering. De Graef holds dual roles as a faculty director and researcher, specializing in advanced materials characterization techniques, particularly electron microscopy and microstructural analysis. Education: Ph.D. in Physics, Catholic University of Leuven (1989) M.S. and B.S. in Physics, University of Antwerp (1983) Research Interests: De Graef's work focuses on 3D microstructure analysis, materials informatics, magnetic materials, and advanced characterization methods like Lorentz microscopy. His research emphasizes quantitative electron microscopy techniques, including electron backscatter diffraction (EBSD), and their application to study complex materials systems. He has pioneered software tools for materials characterization, such as orientation mapping algorithms and dictionary-based indexing methods. Key Achievements: Recipient of the 2025 Microscopy Society of America Distinguished Scientist Award Author/co-author of over 350 publications and two textbooks: Introduction to Conventional Transmission Electron Microscopy and Structure of Materials Principal investigator on grants including a $7.5M Air Force-funded Center of Excellence in data-driven materials research Lab & Collaborations: Directs the Materials Characterization Facility at CMU, advancing capabilities in X-ray and electron microscopy. His team collaborates on projects involving additive manufacturing, magnetic domain analysis, and topological magnetic structures. Recent work includes studies on skyrmions in thin films and phase stability in novel alloys.
