Mario Berges is an Associate Professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in Electrical and Computer Engineering. He holds leadership roles as Co-Director of the IBM Smart Infrastructure Analytics Lab and Director of the Intelligent Infrastructure Research Lab (INFERLab). His work focuses on applying information/communication technologies to enhance the operational efficiency and resilience of built environments amid evolving resource constraints and climate changes. Education: PhD in Civil & Environmental Engineering from CMU (2010). Research Interests: Berges' research integrates smart infrastructure systems, energy efficiency, and machine learning. Key areas include non-intrusive load monitoring (NILM), structural health monitoring of pipelines, building automation systems, and urban heat risk modeling. He develops data-driven frameworks for energy disaggregation, sensor placement optimization, and real-time infrastructure diagnostics. Awards: Recognized with the 2010 FIATECH Outstanding Early Career Researcher Award and 2015 Dean’s Early Career Fellowship from CMU. Grants & Labs: Leads INFERLab, collaborating with IBM on smart infrastructure projects. His work spans academic-industry partnerships focused on building analytics, smart grid technologies, and sensor networks. Future Directions: Expanding research into AI-driven energy systems, resilient urban infrastructure, and cross-disciplinary solutions for climate adaptation.
Prof. Eleni Chatzi is a Full Professor and Chair of Structural Mechanics at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. She holds a PhD from Columbia University (2010) and has held roles from Assistant to Full Professor at ETH since 2010. Her research focuses on intelligent structural monitoring and data-driven asset management, emphasizing nonlinear dynamics and sensor integration. Affiliations : Institute of Structural Engineering, European Academy of Wind Energy (EAWE President), Swiss Community for Computational Methods (SWICCOMAS Chair) Research interests include Structural Health Monitoring (SHM), system identification, and advanced simulation tools. She pioneered work on data-driven diagnostics and self-aware infrastructure, supported by grants like the ERC Starting Grant (2015). Awards include the 2020 Walter L. Huber Prize and 2024 SHM Person of the Year Award. Her work spans wind energy infrastructure, metamaterials for vibration control, and AI-driven structural analytics. Over 600 publications and 200k+ citations highlight her impact. She teaches computational science and structural dynamics in ETH's programs and collaborates globally on sustainable infrastructure projects.
Desiderio Kovar is a Professor at the University of Texas at Austin holding the BFGoodrich Professorship in Materials Engineering and the Distinguished Teaching Professor title within the Department of Mechanical Engineering at the Cockrell School of Engineering. He is affiliated with the Texas Materials Institute, the Center for Electromechanics, and is a core member of the Center for Additive Manufacturing and Design Innovation. Dr. Kovar currently serves as the Associate Chair for Academics for the Mechanical Engineering Department. Dr. Kovar's research focuses on the interface between materials science and engineering and additive manufacturing, with particular expertise in ceramic processing. His work encompasses Advanced Design and Manufacturing, Advanced Materials Science and Engineering, and Nano and Micro-scale Engineering. He teaches undergraduate and graduate classes in the Materials Engineering area, having developed the Materials Science and Engineering minor in 2018, the first minor in Engineering at UT Austin. His recent publications (2023-2025) demonstrate a strong focus on ceramic additive manufacturing processes, particularly Selective Laser Flash Sintering and Micro-Cold Spray technologies. These works explore fundamental mechanisms of high-velocity particle impact, sintering kinetics, and process optimization for ceramic film and part production, reflecting his pioneering work in direct ceramic additive manufacturing without polymer binders. Dr. Kovar has received numerous prestigious awards for his teaching and research: Engineering Foundation Young Faculty Excellence Award (2000) Teaching Excellence Award from the Student Engineering Council (2000) Cockrell School of Engineering's Jack and Maxine Zarrow Family K-16 Teaching Innovation Award (2014) Lockheed Martin Aeronautics Company Award for Excellence in Engineering Teaching (2016) Mechanical Engineering Department's Teaching Award (2016) University of Texas' Outstanding Graduate Advisor (2012) Inducted into the University of Texas at Austin's Academy of Distinguished Teachers (2019) Dr. Kovar has supervised 47 undergraduate students, 21 MS theses, and 17 Ph.D. dissertations, and currently supervises 12 graduate students and one undergraduate student. His research has been generously funded by the National Science Foundation, Los Alamos National Laboratory, Sandia National Laboratory, the Army Research Laboratory, the Office of Naval Research, the US Department of Energy, and various corporate sponsors. In 2013, he founded the Cockrell School's Longhorn Maker Studio, which evolved into Texas Inventionworks. Dr. Kovar leads the Kovar Research Group which currently includes multiple graduate students and postdoctoral researchers working across three main research thrusts: Additive Manufacturing of Ceramics by Selective Laser Flash Sintering, Additive Manufacturing of Ceramics by Indirect Selective Laser Sintering, and Direct Writing of Patterned Films and Devices using the Micro-cold Spray Process.
Dr. Muhammad Gulzari is an Assistant Professor at the School of Civil Engineering, University College Dublin (UCD). Previously, he held positions as Lecturer/Assistant Professor at the University of Galway (2023–2024), Adjunct Assistant Professor at Trinity College Dublin (2022–2023), and a Research Fellow at Trinity College Dublin (2021–2023). He earned his Ph.D. in Civil Structural Engineering from City University of Hong Kong (2021) and a B.Sc. in Civil Engineering from the University of Engineering and Technology Lahore (2017). Education: Bachelor of Engineering, Civil Engineering, University of Engineering and Technology Lahore Ph.D., Civil Structural Engineering, City University of Hong Kong Research Interests: His work focuses on structured materials and dynamics, including finite element modeling, phononic crystals, acoustic and mechanical metamaterials, vibration and noise control, and applications in structural health monitoring. He leads the Structured Materials and Dynamics Lab at UCD, exploring nonlinear and nonreciprocal metamaterials. Teaching and Awards: He has taught courses in Fluid Mechanics, Thermodynamics, and Combustion Engineering. Notable recognitions include the Seal of Excellence Award from the EU-Horizon MSCA Postdoctoral Fellowship (2021) and nominations for teaching excellence awards at Trinity College Dublin and University of Galway. Grants: TimberFlow: Enhancing Efficiency in Mass Timber Construction (Enterprise Ireland, 2025) Indoor Acoustic Quality via Acoustic Metamaterials (Enterprise Ireland, 2025) RUBBERPAVE: ELT Integration in Pavement Construction (Enterprise Ireland, 2024–2026) Deep Learning for Metamaterial Design (Irish Research Council, 2021–2023) Labs and Collaborations: His research group collaborates with industry partners like Amplitude Acoustics and G-frame Structures Ltd. Key projects include developing metamaterials for noise/vibration control and sustainable construction materials.
Mohamed Noureldin is an Assistant Professor at the Department of Civil Engineering, Aalto University , Finland, with prior academic roles at Sungkyunkwan University, South Korea (2015–2022). His expertise lies in integrating Artificial Intelligence (AI) with Structural Health Monitoring (SHM) , Structural Digital Twin , Predictive Maintenance , and Seismic Retrofitting . Research Focus : AI-powered sustainable structural design, smart retrofitting, predictive maintenance, structural material innovation, and next-generation performance-based seismic/wind design. Industrial Experience : 20+ years in offshore/onshore structural engineering (Hyundai Heavy Industries, Samsung Engineering, Arab-Swiss Engineering Company, Zuhair Fayez Partnership). Teaching : Courses in structural analysis, seismic design, dynamics, and reinforced concrete at Aalto and Sungkyunkwan Universities. Laboratory : Leads the Structural Design AI Lab (SDAI), focusing on AI-driven resilient infrastructure. Contact : mohamed.noureldin@aalto.fi , +358504544861. His publications explore cutting-edge applications of AI, ML, and DL in seismic retrofitting, structural durability, soil stabilization, and hybrid damping systems. Collaborative work emphasizes life-cycle cost assessment and augmented reality for predictive maintenance.
Suman Datta is a Professor at the Georgia Institute of Technology , holding the Joseph M. Pettit Chair in Advanced Computing and Georgia Research Alliance Eminent Scholar titles. He has a joint appointment with the School of Materials Science and Engineering. Education : B.Tech in Electrical Engineering from IIT Kanpur; Ph.D. in Electrical and Computer Engineering from the University of Cincinnati. Prior Appointments : Stinson Endowed Chair Professor of Nanotechnology at University of Notre Dame (2015–2022); Professor at Penn State (2007–2015); Intel Corporation (1999–2007) in Advanced Transistor Group. Research Interests : His work focuses on high-performance heterogeneous computing using advanced CMOS and beyond-CMOS semiconductors. Key areas include ferroelectric field-effect transistors (FeFETs) , cryogenic computing , in-memory computing , and brain-inspired computing . He explores materials like ferroelectric gate stacks , insulator-to-metal phase transition oxides , and high-mobility oxides for next-generation compute architectures. Recent Article Trends : His group’s publications emphasize BEOL-compatible oxide transistors , negative capacitance , radiation-resilient devices , and machine learning-aided modeling . Subfields include low-voltage memory , 3D Ising machines , dynamic logic at cryogenic temperatures , and monolithic integration of power delivery systems. Scientific Awards : IEEE Fellow (2013) for contributions to transistor technologies NAI Fellow (2016) for societal impact via patents Intel Achievement Award (2003) for high-k/metal gate CMOS Intel Logic Technology Quality Award (2002) for Tri-gate transistors SEMI Award (2012) for high-k dielectrics Penn State Outstanding/ Premier Research Awards (2012, 2015) Advising & Grants : He has mentored students like Wriddhi Chakraborty , Khandker Akif Aabrar , and Sourav Dutta . His research is funded by SRC , DARPA , and NSF , including leadership of the ASCENT and EXCEL centers. Labs & Collaborations : Datta directs the STAR Lab at Georgia Tech, which specializes in atomistic modeling , nanofabrication , and compact model development . The lab collaborates with industry giants like Intel , Micron , and IBM through the ASCENT center.
Dr. Kim Yong-Joe is an Associate Professor in the J. Mike Walker ’66 Department of Mechanical Engineering at Texas A&M University. He serves as the Director of the Acoustics and Signal Processing Laboratory (ASPL), founded in 2009. His research focuses on acoustics, applied signal processing, nonlinear acoustics, biomedical acoustics, noise and vibration control, and structural dynamics. He has received notable awards including the 2014 Department of Mechanical Engineering Graduate Teaching Award and the 2014 Pioneer Natural Resources Faculty Fellow II. His lab specializes in wave propagation analysis, ultrasonic structural health monitoring, and acoustophoresis in microfluidic systems. He has collaborated with sponsors like the National Science Foundation, Qatar National Research Fund, and Samsung Techwin. His research has led to advancements in noise reduction technologies, biomedical diagnostics, and nondestructive evaluation methods.
Daniel Kifer is a Professor in the Computer Science and Engineering department at Pennsylvania State University, with affiliations to the Huck Institutes of the Life Sciences. His work bridges computer science, privacy-preserving machine learning, and geoscience applications. With over 10,000 citations and a high h-index, he focuses on methods to unify theoretical and applied research. Research Interests: Differential Privacy, Privacy-Preserving Machine Learning, Physics-Informed Neural Networks, Landslide Prediction, and Formal Verification of Privacy Systems. Recent projects include grants from the National Science Foundation: SaTC: CORE: Small (2024): privacy-preserving user data embedding in machine learning pipelines. SaTC: CORE: Medium (2017-2023): formal methods for differential privacy and accuracy optimization. His research outputs span domains like geoscience, database systems, and policy analysis, emphasizing precision and scalability of privacy-preserving algorithms.
University of Illinois Urbana-ChampaignUnited States
Imad L. Al-Qadi is the Grainger Distinguished Chair in Engineering and Director of the Illinois Center for Transportation (ICT) at the University of Illinois at Urbana-Champaign (UIUC). He holds a Ph.D. in Civil Engineering from Penn State and has held faculty positions at Virginia Tech and Penn State. His research focuses on sustainable transportation infrastructure, pavement mechanics, and advanced materials. Al-Qadi leads initiatives like the Illinois Autonomous and Connected Track (I-ACT), a high-speed test facility for autonomous vehicles and energy harvesting systems. Key roles include: Director of ICT, advancing multimodal transportation infrastructure Pioneer of the Smart Road and full-scale pavement testing Founder of the Academy of Pavement Science and Engineering Research interests span: Highway/airfield sustainability Tire-pavement interaction Energy harvesting Electric vehicles' infrastructure impact Leadership roles include past presidency of ASCE's Transportation and Development Institute and editorship of the International Journal of Pavement Engineering. He has authored over 1,000 publications, including 390 refereed papers, and secured over 180 research grants from federal agencies and industry. Awards include NSF Young Investigator Award (1994), TRB Crum Award (2023), and 2024 Executive Leadership Fellow. His work is internationally recognized, with honorary professorships at institutions in China, Sweden, and the UK.
Professor Ali Yapar is a faculty member at Istanbul Technical University in the Electronics and Communication Engineering department. His research focuses on Electromagnetics , Microwave Engineering , and Antenna Technologies , with a particular emphasis on inverse scattering problems and microwave imaging for biomedical applications. He has supervised numerous graduate students and led projects related to breast cancer treatment and rough surface imaging. PhD in Electronics and Communication Engineering from Istanbul Technical University (1997) MSc in Electronics and Communication Engineering (1995) His recent publications analyze advanced techniques for microwave hyperthermia systems, reverse time migration methods, and Newton-based solutions for electromagnetic inverse scattering. Key projects include TUBITAK-funded initiatives on microwave tomography and brain stroke imaging. He serves as a project investigator and executive for electromagnetic research programs. Research areas span Electromagnetic Wave Propagation , Green's Function Applications , and Dielectric Material Analysis . Collaborations include IEEE members and international researchers in computational electromagnetics.
California State University, East BayUnited States
Roya Nasimi, Ph.D., is an Assistant Professor in the Department of Engineering at California State University, East Bay, where she joined in Fall 2023. Her expertise spans structural engineering, computer vision, and artificial intelligence, with a focus on developing innovative solutions for infrastructure monitoring and safety. Dr. Nasimi's educational background includes: Ph.D. with distinction in Structural Engineering from the University of New Mexico Master’s degree in Structural Engineering from the University of Tabriz Bachelor’s degree in Civil Engineering from the University of Tabriz Her research focuses on structural health monitoring using advanced technologies. She integrates computer vision , artificial intelligence , and machine learning to develop systems for monitoring aging infrastructure, particularly bridges. Her work includes designing low-cost and high-end sensor systems, conducting full-scale bridge experiments, and collaborating on interdisciplinary projects to enhance infrastructure safety and resilience. Her recent publications (2021-2025) demonstrate a strong emphasis on non-contact monitoring techniques using drones, lasers, and computer vision. Key trends include the application of deep learning for displacement measurement, digital twinning for infrastructure, and rockfall prevention through machine learning. Her work bridges civil engineering with cutting-edge technology to address critical infrastructure challenges. Dr. Nasimi's research is supported by multiple grants: U.S. Army Corps of Engineers Transportation Research Board (TRB) Transportation Consortium of South-Central States (Tran-SET) New Mexico Consortium She serves on two TRB standing committees and mentors students in structural health monitoring and infrastructure technology. Dr. Nasimi leads interdisciplinary research teams focused on infrastructure monitoring, utilizing drones, lasers, and computer vision systems. Her work involves field experiments on bridges and rail systems, often in collaboration with government agencies and research consortia.
Dr. Maria Anna Polak is a Professor in the Department of Civil and Environmental Engineering at the University of Waterloo, cross-appointed in the Faculty of Engineering. Her research focuses on advanced structural analysis, composite materials, and innovative construction technologies. She specializes in concrete structures, fiber-reinforced polymers (FRP/GFRP), and nondestructive evaluation methods. Her work addresses challenges in structural safety, durability, and sustainable design through computational modeling and experimental validation. Research Interests: Finite Element Analysis of Reinforced Concrete Structures FRP/GFRP Reinforcement for Concrete Applications Punching Shear Behavior and Design 3D-Printed Construction Materials Nondestructive Testing (NDT) with LiDAR and Ultrasonics Time-Dependent Behavior of Polymers and Composites Her recent publications emphasize advancements in computational modeling (FEA) for complex structural systems, material characterization of novel composites, and optimization of concrete components under seismic and environmental loads. Notable trends include integration of emerging technologies like smartphone LiDAR for on-site assessment and development of predictive models for FRP-degraded systems. Grants & Collaborations: Her work has been supported by industry partnerships (e.g., Horizontal Directional Drilling research) and academic initiatives. She contributes to international standards through experimental validation of design methods for modern construction materials. Labs/Teams: Active in the University of Waterloo's Structural Engineering and Applied Mechanics research group, focusing on smart infrastructure and material innovation.
Dr. Hongli (Julie) Zhu is an Associate Professor in the Department of Mechanical and Industrial Engineering at Northeastern University's College of Engineering. Her research focuses on sustainable energy storage, multifunctional materials, and advanced manufacturing, with emphasis on developing environmentally friendly biomass-derived materials, all solid-state batteries, and flow batteries. She leads the ZHU Lab at Northeastern University, which is dedicated to creating safer, cheaper, and higher performance energy storage solutions while exploring multifunctional materials derived from nature. Dr. Zhu received her PhD from South China University of Technology and Western Michigan University (2004-2009). She conducted postdoctoral research at KTH Royal Institute of Technology in Sweden (2009-2011), focusing on biodegradable and renewable biomaterials from natural wood, followed by additional postdoctoral work at the University of Maryland (2012-2015), where she researched nanocellulose and energy storage. Dr. Zhu's research spans multiple disciplines at the intersection of materials science, energy storage, and sustainable manufacturing. Her work addresses critical challenges in energy storage technology, including developing all solid-state batteries, flow batteries, and high energy density battery systems. She has pioneered research in sustainable biomass-derived materials, particularly investigating cellulose, hemicellulose, and lignin for applications in bendable, implantable, and biocompatible electronics. Her lab also focuses on advanced manufacturing techniques, including high-speed roll-to-roll processing for emerging advanced materials and devices. Analysis of Dr. Zhu's publication record reveals a strong focus on next-generation battery technologies, particularly solid-state systems. Her research demonstrates significant contributions to understanding and improving lithium dendrite suppression, electrode architecture optimization, and interface stabilization in solid-state batteries. She has also made substantial advances in sustainable materials derived from natural resources, developing applications for cellulose nanostructured fibers, paper, and aerogel/hydrogel systems. MRS Communications Early Career Distinguished Presenters and JMR Distinguished Invited Speakers (2024) Selected in Stanford University List of Top 2% Scientists Worldwide (2021-2024) College of Engineering Faculty Fellow (2023) Soren Buus Outstanding Research Award (2022) Women in Materials Science, Advanced Materials (2021 and 2022) Women Scientists at the Forefront of Energy Research, ACS Energy Letters (2020) Innovator of the Year 2013, Maryland Jakob Wallenberg Scholarship, Sweden Dr. Zhu has secured significant research funding from various sources, including the National Science Foundation and Department of Energy. Her current projects include "Uncovering the mechano-electro-chemo mechanism of fresh Li in sulfide based all solid-state batteries through operando studies" (NSF), "Enabling Advanced Electrode Architecture through Printing Technique" (DOE), and "Engineering the Metal Sulfide Interface in All Solid State Batteries through Operando Study" (NSF). She collaborates with industry partners including Rogers Corporation and has developed patented technologies related to sustainable materials and energy storage. Dr. Zhu serves as Codirector of Advanced & Intelligent Manufacturing, Editor of Progress in Materials Science, and on the Editorial Advisory Board of Chemical Society Reviews. The ZHU Lab at Northeastern University is a highly interdisciplinary research group that bridges scales from the nanoscopic to macroscopic and system level. The lab's work has led to numerous patents, including "Natural fiber composites as a low-cost plastic alternative" and "Fire-retardant Nanocellulose Aerogel, and Methods of Preparation and Uses Thereof." The group focuses on making energy storage safer, cheaper, and higher performing while exploring multifunctional materials derived from nature, with particular emphasis on applying high-speed roll-to-roll manufacturing to emerging advanced materials and devices.
Erin Bell is a Professor in the Department of Civil and Environmental Engineering at the University of New Hampshire . She holds a Ph.D. in Structural Engineering from Tufts University and has extensive experience in structural health monitoring, finite element modeling, and infrastructure sustainability. B.C.E., Georgia Institute of Technology M.S., Civil Engineering, Tufts University Ph.D., Structural Engineering, Tufts University Her research focuses on structural health monitoring, bridge condition assessment, and integrating AI techniques like artificial neural networks and deep reinforcement learning for infrastructure asset management. Recent work includes equitable maintenance strategies for aging bridges in flood-prone zones and tidal energy conversion for sustainable bridge monitoring systems. Key trends in her publications include the application of machine learning to structural analysis, finite element model calibration, and climate change adaptation in transportation infrastructure. She has led projects on deep reinforcement learning for bridge scour maintenance, modal-based uncertainty quantification, and multi-scale modeling of steel bridges. Grants and Collaborations : Erin Bell has secured funding from the National Science Foundation (NSF) , US Department of Energy (DOE) , and New Hampshire Department of Transportation . Notable projects include the Living Bridge initiative for tidal energy-powered smart infrastructure and statewide data exchange systems for bridge condition assessment.
Dr. Andy Nguyen is a Senior Lecturer in the School of Engineering at the University of Southern Queensland. He holds a PhD from Queensland University of Technology (QUT), an MEng from the National University of Civil Engineering (NUCE), and a BEng from NUCE. His research focuses on structural health monitoring, integrating machine learning and deep learning techniques to assess infrastructure integrity. Key areas include damage detection in bridges, pavements, and buildings, as well as sustainable construction materials like bamboo. Nguyen leads projects such as the 'Next Generation Living Laboratory for Engineering Education and Engagement,' emphasizing real-world applications of technology in civil infrastructure. His work spans crack detection algorithms, finite element model updating, and vibration-based structural analysis. He collaborates on AI-driven solutions for autonomous vehicle object detection and smart maintenance planning. Nguyen’s contributions include over 50 peer-reviewed publications and active supervision of postgraduate research in composite materials and transport infrastructure. His research outputs highlight advancements in computational mechanics, sensor technologies, and data-driven methods for infrastructure resilience. Nguyen’s expertise bridges civil engineering challenges with cutting-edge machine learning, advancing both theoretical and applied solutions for sustainable and safe structures.
