Aman Arora is an Assistant Professor at Arizona State University's Ira A. Fulton Schools of Engineering, specializing in the School of Computing and Augmented Intelligence. His research focuses on reconfigurable computing, hardware acceleration of machine learning, and non-traditional computing paradigms like Processing-In-Memory. With over a decade of semiconductor industry experience, he bridges academic research and industrial applications. PhD in Computer Science from The University of Texas at Austin Research interests emphasize domain-specific acceleration through FPGA optimization , compute-in-memory architectures , and machine learning for CAD/EDA . His work addresses critical challenges in energy efficiency and throughput for AI workloads. Recent publications demonstrate trends toward compute-in-memory systems , FPGA-based deep learning acceleration , and sustainable hardware design . Key contributions include frameworks like SAF, CSR, and GAMA for dynamic hardware optimization. Laboratory Website: ADVENT Lab Teaching includes courses on digital hardware design (CSE 320) and advanced topics in machine learning acceleration (CEN 524/CSE 524). Industry experience informs his practical approach to research and education.
M. Tamer Özsu is a University Professor of Computer Science at the David R. Cheriton School of Computer Science, University of Waterloo, where he holds a Cheriton Faculty Fellowship. He also serves as a Distinguished Visiting Professor at Tsinghua University and is the Founding Director of Waterloo-Huawei Joint Innovation Laboratory since 2018. His extensive contributions to computing have earned him numerous prestigious awards including the 2024 ACM Presidential Award for long-standing and significant contributions to the computing field. Professor Özsu's research focuses on data engineering aspects of data science, particularly addressing data management issues with two main foci: management of non-traditional data and large-scale distributed data management. He is renowned for his seminal book "Principles of Distributed Database Systems" (co-authored with Patrick Valduriez), now in its fourth edition, and the "Encyclopedia of Database Systems" (co-edited with Ling Liu), in its second edition. His work bridges theoretical foundations with practical system implementations, targeting grand societal challenges through computational approaches. His recent publications reveal a strong trend toward graph analytics, streaming data processing, and the integration of large language models with vector data management. The research shows increasing focus on GPU-accelerated graph processing, RDF query optimization, and multimodal data analysis, reflecting the evolution of data management challenges in the era of big data and AI. His work continues to address fundamental challenges in distributed data systems while adapting to emerging technologies and application domains. Scientific Awards and Fellowships ACM Presidential Award (2024) IEEE TCDE Education Award (2024) IEEE Innovation in Societal Infrastructure Award (2022) CS Can | Info Can Lifetime Achievement Award (2018/2019) ACM SIGMOD Test-of-Time Award (2015) ACM SIGMOD Contributions Award (2006) The Ohio State University College of Engineering Distinguished Alumnus Award (2008) Fellow of the Royal Society of Canada Fellow of the American Association for the Advancement of Science (AAAS) Life Fellow of the Association for Computing Machinery (ACM) Life Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA) Elected member of the Science Academy, Türkiye Professor Özsu has been deeply involved in academic leadership and community building. As Founding Editor-in-Chief of ACM Books (2013-2019), he launched a series that by 2019 had published 28 major books with another 30 under contract. His service to ACM, particularly through SIGMOD, has been exemplary and widely recognized. He directs the Waterloo-Huawei Joint Innovation Laboratory, which focuses on cutting-edge research in data management and distributed systems, fostering strong industry-academia collaboration.
Liu Lili is a Lecturer (Educator Track) in the Department of Computer Science at the School of Computing, National University of Singapore. She holds a Ph.D. from Nanyang Technological University and a Master's in Computer Science from Shanghai University. Prior to NUS, she served as a Senior Research Scientist at Singapore Polytechnic and a Scientist at A*STAR's Institute of High-Performance Computing. Her research focuses on Machine Learning, Computer Vision, and Multi-modal Learning, with applications in FinTech, Social Media Analysis, and Algorithms & Theory. Notable projects include AI-driven coating inspection systems for marine assets and behavioral competency assessment tools for navigational safety. She has contributed to robotics for construction quality assessment and interactive virtual environments for rehabilitation. Liu's publications span AI applications in finance, robotics, and material science, reflecting her expertise in bridging theoretical computer science with practical industrial solutions. Her work emphasizes automation, anomaly detection, and multi-modal data integration.
Prof. Dr. Ercan Yüksel is a full Professor in the Department of Civil Engineering at Istanbul Technical University (ITU), College of Engineering. He has been a faculty member at ITU since 1990, progressing from Assistant Professor to Professor in 2017. His research focuses on earthquake engineering, structural dynamics, and numerical modeling, with applications in seismic design, energy dissipation, and structural health monitoring. PhD, Civil Engineering, Istanbul Technical University MS, Structural Engineering (with thesis), Istanbul Technical University BS, Civil Engineering, Istanbul Technical University His research interests are centered on earthquake engineering , particularly seismic input energy analysis , energy dissipation systems , reinforced and precast concrete structures , and seismic isolation . He actively investigates the dynamic behavior of structures under earthquake loads and develops innovative solutions for improving structural resilience. His work integrates advanced numerical modeling with experimental validation. Recent publications (2023–2025) highlight a strong focus on energy-based seismic design, performance of mechanical couplers, damping systems for high-voltage insulators, and fatigue behavior of railway tracks. These works are closely tied to real-world seismic events like the 2023 Kahramanmaraş earthquake, demonstrating applied and impactful research. His scientific recognition includes: Notable Work Award, Turkish Academy of Sciences (TÜBA), 2012 Golden Beam Award, Turkish Prefabricated Association, 2011 Prof. Yüksel is an active Principal Investigator on multiple research projects funded by ITU’s BAP program, covering topics such as smart sleepers for railway monitoring, novel seismic input energy spectra, and earthquake isolation for racking systems. He has supervised numerous theses and is involved in professional organizations including UNESCO-IPRED and the Turkish Earthquake Foundation. He leads research on structural health monitoring of ballasted railway lines using smart sleeper technology and is developing earthquake isolation systems for industrial storage racks. His lab integrates experimental testing with numerical simulation to validate new structural components under cyclic and biaxial loading.
Suyi Li is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering, where he leads the Dynamic and Architected Robot and structurE (DARE) Lab. Previously, he served as an Assistant Professor at Clemson University from 2016-2022 after completing postdoctoral research at the University of Michigan. Ph.D. in Mechanical Engineering, University of Michigan, Ann Arbor (2014) M.Sc. in Mechanical Engineering, Pennsylvania State University (2008) B.S. Summa Cum Laude in Mechanical Engineering, University of Michigan, Ann Arbor (2006) Dr. Li's research focuses on pioneering new paradigms of intelligent robots and functional structures by exploiting the interplay between geometry, mechanics, actuation, and computation. His work spans origami-inspired morphing structures, physically computing materials that perform machine learning tasks without traditional electronics, and soft/reconfigurable robots that can move like animals or grow like plants. His innovative approach combines mechanical engineering principles with computational thinking to create systems with 'mechano-intelligence'. Analysis of Dr. Li's recent publications reveals a strong trajectory toward embodied intelligence and mechanical computing, where physical structures themselves perform computational tasks. His work increasingly integrates origami/kirigami principles with advanced materials to create systems that can sense, process information, and actuate without conventional electronics. The research shows progression from fundamental mechanics of adaptive structures to sophisticated applications in robotics and computing. Dean's Awards of Excellence – Faculty Fellow, Virginia Tech (2024) C.D. Mote Jr Early Career Award, ASME Design Engineering Division (2022) Gary Anderson Early Achievement Award, ASME Aerospace Division (2021) Junior Researcher of the Year Award, College of Engineering, Clemson University (2020) CECAS Dean's Faculty Fellow, Clemson University (2018) CAREER Award, National Science Foundation (2018) ASME Freudenstein Young Investigator Award Dr. Li has secured nearly two million dollars in research funding, including the prestigious NSF CAREER award and an NSF EFRI project to build mechano-bio hybrid reservoir computers. He advises multiple Ph.D. and Master's students in the DARE Lab, with recent successes including Vishrut Deshpande's Ph.D. defense. His research has generated close to 80 journal and conference papers, demonstrating significant impact in the fields of adaptive structures and materials systems. Dr. Li also serves on editorial boards for several prominent journals including Journal of Intelligent Material Systems and Structures and Philosophical Transactions of the Royal Society A. The DARE Lab at Virginia Tech comprises a multidisciplinary team of researchers working on origami-inspired meta-structures, physically computing materials, and soft robotics. Current projects include developing electronics-free crawling robots with mechanical central pattern generators, creating kirigami-based wearable medical devices, and engineering metamaterials with programmable mechanical properties. The lab actively collaborates with institutions across the country and has received recognition for its innovative approaches to combining mechanical design with computational capabilities.
Hua Chen is an Associate Researcher and PhD Supervisor at the School of Quantum Science and Engineering at Southern University of Science and Technology (SUSTech), with extensive experience in quantum computing circuit design and MEMS sensor interfaces. Previously, he served as an Associate Researcher at the Institute of Microelectronics, Chinese Academy of Sciences (2021-2022) and as an Assistant Researcher there from 2017-2021, building on his industry experience as an RF/Analog IC Design Engineer at Southwest Integrated Circuit Design Co., Ltd (2007-2010). Education: Ph.D. in Microelectronics and Solid-State Electronics, University of Chinese Academy of Sciences (2014-2017) M.Eng. in Electronic and Communication Engineering, University of Chinese Academy of Sciences (2011-2014) B.Eng. in Microelectronics, Chongqing University of Posts and Telecommunications (2003-2007) Dr. Chen's research focuses on interface circuit design for quantum computing and MEMS sensors, with particular expertise in high performance analog/RF/mixed-signal IC design. His recent work has shifted toward cryogenic circuit design for quantum bit control and readout systems, representing a strategic pivot toward China's national priority in quantum information technology. His publications reveal a consistent trajectory from MEMS gyroscopes and oscillators toward quantum computing hardware support circuits, demonstrating his ability to adapt expertise to emerging technological frontiers. Dr. Chen's research output shows a clear evolution from traditional MEMS sensor interfaces toward quantum cryogenic electronics, with his 15 most recent publications heavily concentrated in cryogenic circuit design for quantum applications. This represents a strategic shift aligning with China's substantial investment in quantum computing research, particularly in the development of control and readout electronics for scalable quantum systems. His significant honors include: Special talent of Shenzhen's Pengcheng Peacock Plan (January 2024) IEEE Senior Member (February 2022) Intellectual Property Specialist of Chinese Academy of Sciences (January 2020) Outstanding Employee (Top 10%) at Institute of Microelectronics CAS (2020) Multiple Graduate Student Scholarships from Institute of Microelectronics CAS (2015-2017) As a PhD Supervisor at SUSTech, Dr. Chen mentors graduate students in quantum circuit design while leading research funded through multiple sources including a Beijing Natural Science Foundation General Project (RMB 200,000) for RF MEMS disk oscillator drive circuits and a Youth Project (RMB 100,000) for MEMS gyroscope phase alignment. He has also participated in major national projects totaling over RMB 27 million, demonstrating his integration into China's strategic research initiatives. Dr. Chen leads a research group at the International Quantum Academy in Shenzhen focused on cryogenic CMOS integrated circuit design for quantum computing applications. His team develops specialized low-temperature measurement and control chips that address critical challenges in scaling quantum computing systems, with particular emphasis on MEMS-based quantum frequency references and cryogenic amplifiers that operate at temperatures near absolute zero.
Haipeng Shen is a Professor of Innovation and Information Management at HKU Business School, The University of Hong Kong, serving as Associate Dean (EMBA and IMBA) and holding the Patrick S C Poon Professorship in Analytics and Innovation. He chairs the Business Analytics and Innovation program and joined HKU in 2015 after previously holding a professorship at the University of North Carolina at Chapel Hill. His academic credentials include: PhD in Statistics, The Wharton School of Business, University of Pennsylvania, 2003 MA in Statistics, The Wharton School of Business, University of Pennsylvania, 2000 BS in Mathematics, School of Mathematical Sciences, Peking University, 1998 Professor Shen's research focuses on data-driven decision making under uncertainty, with expertise spanning big data analytics, business analytics, healthcare analytics, and service engineering. He develops advanced statistical and machine learning methodologies to solve complex operational problems in call centers, optimize stroke care protocols, and enhance financial risk modeling, emphasizing real-time applications in high-stakes environments. Analysis of his recent publications reveals a consistent interdisciplinary approach bridging operations research, statistics, and domain-specific knowledge. His work demonstrates strong methodological innovation in time-series forecasting for service systems, risk assessment frameworks for medical complications, and covariance structure analysis for financial markets, with direct translational impact on business operations and clinical outcomes. His scientific contributions have been recognized with prestigious awards including: Most Influential Publication Award from China Stroke Association (2018) Fellow of the American Statistical Association (2015) Best Advisor of the Year Award from Academy of Asian Business (2018) Elected Member of International Statistical Institute (2015) Cluster Chair for Big Data Analytics at INFORMS International (2015) As an academic leader, Professor Shen has secured significant research funding from organizations including The Xerox Foundation and National Institute on Drug Abuse. He serves as Associate Editor for Management Science, Journal of the American Statistical Association, and Technometrics, while mentoring graduate students in statistical methodology and applied analytics. His current initiatives position HKU Business School at the forefront of healthcare innovation through big data analytics, driving collaborations with medical institutions to transform stroke care and hospital operations in Asia.
Dr. Ali Amin is a Senior Lecturer and ARC Industry Fellow at the School of Civil Engineering, The University of Sydney. He holds academic roles at ETH Zurich and The University of Toronto, and has consulting experience at Pells Sullivan Meynink. He earned a Bachelor of Engineering (Honours Class I) and PhD in Civil Engineering from UNSW Sydney, with awards including the 2017 Concrete Institute of Australia National Bursary Award and the 2016 UNSW Vice-Chancellor’s Teaching Excellence Award. His research focuses on structural analysis and design of high-performance and fiber-reinforced concrete structures, including contributions to Australian standards like AS5100.5-2017 and AS3600-2018. He teaches courses such as CIVL5269 (Advanced Concrete Structures) and CIVL3235 (Structural Analysis). Key research areas include fiber-reinforced concrete (FRC/SFRC) behavior, shear strength analysis, time-dependent deformation, and fluid-structure interaction in tall buildings. Collaborations include Professor Walter Kaufmann (ETH Zurich) and Professor Fausto Minelli (University of Brescia). Grants: ARC Industry Fellowship (2024), UNSW Goldstar Award (2018). Awards: 2017 Concrete Institute of Australia National Bursary Award, 2016 Teaching Excellence Award. His publications span over 50 peer-reviewed articles in journals like Journal of Structural Engineering , ACI Structural Journal , and conferences such as BEFIB and FraMCoS. Current research includes AI-based quality control in steel fabrication and performance evaluation of specialty cement in waste systems.
Charles Baden-Fuller is the Centenary Professor of Strategy and leader of the Strategy Group at Bayes Business School , City St George’s, University of London . He is concurrently a Senior Fellow at the Wharton School, University of Pennsylvania . Recognised among the world’s top strategy scholars, he has directed major multi-institutional research initiatives and served as Editor-in-Chief of Long Range Planning (1999-2010). Education & Qualifications BA (Oxon) – University of Oxford MA Economics – Cornell University PhD – London School of Economics Research Interests Charles’s work lies at the intersection of strategic management , business model innovation and digital transformation . His early research explained how mature firms can be rejuvenated and how alliances create competitive advantage. More recently he has advanced the concept of business models , investigating what they are, how they evolve, and how managerial cognition shapes their deployment in increasingly digitalised environments. Empirical settings span biotechnology, financial services, automotive software ecosystems and creative industries. Publications & Impact With over 80 refereed journal articles and five influential books—including the seminal Rejuvenating the Mature Business (Harvard Business Press)—his scholarship has shaped both academic theory and managerial practice. Recent articles (2021-2025) focus on digital platform alliances, entrepreneurial networking logics, and AI-enabled business model design. Honours & Awards Fellow of the Strategic Management Society (SMS Fellow, 2009) Fellow of the British Academy of Management Fellow of the British Academy Fellow of AACSB Doctoral Supervision & Research Funding He has supervised to completion more than six PhD students, many now faculty at leading universities. His research has attracted over £4 million in grants from the European Union , UK ESRC , EPSRC and the Mack Institute-Wharton , supporting multi-university teams at Bayes, Sussex, LSE, CREATE-Glasgow, Grenoble EM and Wharton. Professional & Outreach Roles Beyond academia, Charles serves as director or strategic advisor to several high-technology start-ups and as trustee of a major charity. He is a frequent keynote speaker for industry and policy audiences, and his research findings have been featured in the Financial Times , Management Today and other leading media.
Patrick Phelan is a Professor and Associate Dean of Graduate Programs at the Ira A. Fulton Schools of Engineering, Arizona State University (ASU). He holds additional roles as a Senior Global Futures Scientist and Editor-in-Chief of Frontiers in Energy Efficiency . His research focuses on sustainable energy systems, thermal management, and energy efficiency, with notable contributions to solar energy, thermal transport processes, and industrial cooling technologies. Phelan has extensive administrative experience, including managing the U.S. Department of Energy’s Emerging Technologies Program and the National Science Foundation’s Thermal Transport Processes Program. Education: Postdoctoral Fellow, Tokyo Institute of Technology (1990–1992) Ph.D., Mechanical Engineering, University of California, Berkeley (1990) M.S., Mechanical Engineering, Massachusetts Institute of Technology (1987) B.S., Mechanical Engineering, Tulane University (1985) Research Interests: Thermal engineering and heat transfer Sustainable energy systems and cooling Energy efficiency in buildings and industry Thermogalvanic systems and advanced materials Decarbonization and community benefit strategies Professional Associations: Fellow, American Society of Mechanical Engineers (ASME) Member, American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Current Activities: Leading the ASU Energy Efficiency Center Contributing to the Energy for Rural Arizona initiative Advancing agricultural cold chain efficiency Teaching courses on heat transfer and energy systems (e.g., MAE 589, MAE 576)
Dr. Nicholas Brake is an Associate Professor at Lamar University's Department of Civil and Environmental Engineering, focusing on reclaimed materials, wireless power transfer applications in concrete, and fatigue fracture modeling for pavements. His research spans recycled concrete aggregate, coal ash utilization, and electromagnetic cementitious composites. Education: Ph.D., M.S., B.S. in Civil Engineering from Michigan State University Awards: Anita Riddle Fellowship (2018), Lamar Merit Award (2018), Presidential Faculty Fellowship (2015), and multiple scholarships during his studies. His research emphasizes three key areas: 1) Material reclamation using recycled concrete aggregate, coal combustion residuals, and EAF slag. 2) Electromagnetic transport properties for wireless vehicle charging applications. 3) Fatigue damage modeling in concrete pavements. Through 3D printing integration and design-build-test pedagogy, he enhances student learning outcomes. Recent publications focus on international engineering education (2020), magnetic concrete composites (2019), and advanced testing methodologies for civil infrastructure (2018). His teaching innovation includes developing nine Lamar University courses with active learning strategies that improved student design confidence (p Scientific Awards: Anita Riddle Excellence in Teaching Fellowship (2018) Presidential Faculty Fellowship for Teaching Innovation (2015) Outstanding Teaching Assistant Award at Michigan State (2011) Dr. Brake mentors undergraduate and graduate researchers, including doctoral candidates Mahdi Feizbahr and Hossein Hariri Asli (2023-2024). His lab (LUMS) houses advanced testing systems like Instron 5965/8803, MTS Insight 100SL, and thermal analyzers for material characterization.
Dr. Gabriel Wainer is a Professor in the Department of Systems and Computer Engineering at Carleton University's Faculty of Engineering and Design. He leads the Advanced Real-Time Simulation Lab and specializes in modeling and simulation methodologies, particularly focusing on discrete event systems, real-time modeling, cellular automata, and DEVS formalism. Research Interests: Discrete event systems, DEVS formalism, cellular automata, real-time simulation, IoT applications, and parallel/distributed simulation Affiliation: Carleton University Recent publications highlight his work in advanced simulation frameworks, energy-efficient 5G systems using deep reinforcement learning, and pandemic modeling with cellular automata. His lab develops tools like PROMETHEUS and Devsmap for standardized DEVS model representation, while also exploring applications in wireless communication, building energy systems, and behavioral epidemiology.
Robert M. Weikle, II is a Professor in the Charles L. Brown Department of Electrical and Computer Engineering at the University of Virginia, with a courtesy appointment in the Department of Physics. He earned his B.S. from Rice University (1986), M.S. (1987), and Ph.D. (1992) in Electrical Engineering from Caltech, followed by postdoctoral work at Chalmers University of Technology (1992). His research focuses on millimeter-wave and terahertz electronics , applied electromagnetics, integrated antennas, low-noise sensors, and heterogeneous integration of compound semiconductors. His work bridges electronics and photonics for spectrum access, with applications in astronomy, spectroscopy, and metrology. He has published extensively on micromachined silicon substrates, superconducting materials, and emerging technologies. Scientific Awards: IEEE Microwave Prize (1993) David A. Harrison III Award (1999) University of Virginia All-University Outstanding Teaching Award (2000) Edlich-Henderson Innovator of the Year (2016) Fulbright Scholar (2001) As Chief Technology Officer and co-founder of Dominion Microprobes, Inc., he commercializes micromachined wafer probes for high-frequency metrology. His lab, located in E220 Thornton Hall and the Jesse W. Beams Physics Building, has produced 15+ recent publications on submillimeter-wave devices, THz probes, and calibration techniques.
Cecilia R. Aragon is a Professor in the Department of Human Centered Design & Engineering at the University of Washington, where she also serves as an Adjunct Professor in Computer Science & Engineering, Electrical and Computer Engineering, and the Information School. She is additionally a Senior Data Science Fellow at the eScience Institute. Aragon directs the Human-Centered Data Science Lab and has made significant contributions at the intersection of human-computer interaction and data science. Her research interests focus on human-centered data science, human-centered artificial intelligence, human-centered machine learning, human-computer interaction (HCI), computer-supported cooperative work (CSCW), visual analytics, aviation and astronautics sociotechnical systems, and emotion in informal text communication. Aragon's work bridges technical and social aspects of data science, particularly examining how humans interact with and gain insight from large datasets through both quantitative and qualitative methods. Aragon's recent publications demonstrate a strong focus on understanding online communities, sentiment analysis, distributed mentoring systems, and the ethical implications of AI. Her work spans multiple disciplines including social computing, data visualization, and astrophysics data analysis, showing her interdisciplinary approach to human-centered data science. Presidential Early Career Award for Scientists and Engineers (PECASE) 2008 Fulbright Fellowship 2017-18 HCDE Faculty Innovator in Research Award, University of Washington, 2015 Distinguished Alumni Award, Computer Science, University of California, Berkeley, 2013 Top 25 Women of the Year, Hispanic Business Magazine, 2009 Aragon has secured over $28 million in research funding from organizations including the National Science Foundation, National Institute of Standards and Technology, Department of Energy, Gordon and Betty Moore Foundation, Alfred P. Sloan Foundation, Washington Research Foundation, and industry partners like Microsoft and Intel. Her educational background includes a Ph.D. in Computer Science from UC Berkeley (2004), an M.S. in Computer Science from UC Berkeley, and a B.S. with Honors in Mathematics from Caltech. She leads the Human-Centered Data Science Lab and is affiliated with the eScience Institute, the Nearby Supernova Factory, and various research groups focused on data-intensive scientific collaborations. Her work on collaborative visual analytics systems like Sunfall has had significant impact in both academic and applied settings.
Kuanshi Zhong is an Assistant Professor in the Department of Civil and Architectural Engineering and Construction Management at the University of Cincinnati. He holds a PhD from Stanford University (2021) in Civil and Environmental Engineering, with prior degrees from Stanford (Master, 2017) and Tongji University (Bachelor, 2015). His research focuses on earthquake engineering, structural resilience, and advanced computational methods for infrastructure safety. Key research interests include seismic design of tall buildings, probabilistic modeling of structural response (e.g., using Probabilistic Learning on Manifolds), and material failure mechanisms in reinforced concrete. He also explores multi-hazard resilience, regional risk assessment, and software tools for disaster simulation (e.g., R2DTool and EE-UQ). Dr. Zhong has secured grant funding as PI/Co-PI, including a National Science Foundation grant (2023-2026) for equitable building decarbonization strategies and a Concrete Reinforcing Steel Institute grant (2024-2025) for bar performance improvements. He teaches graduate/undergraduate courses on concrete design and structural mechanics. His work spans collaborations with institutions like Stanford University and the SimCenter, contributing to open-source tools for regional loss assessments and hurricane impact modeling. Current projects address cascading hazards, steel reinforcement durability, and high-resolution seismic risk evaluation.
