Ian Bradley is an Assistant Professor in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo, State University of New York. His research focuses on creating sustainable biological processes to address needs in engineered and natural systems for water and wastewater treatment and resource recovery. Education: PhD in Environmental Engineering, University of Illinois at Urbana-Champaign (2017) MS in Environmental Engineering, University of Illinois at Urbana-Champaign (2011) MS in Civil Engineering (Structures), University of Illinois at Urbana-Champaign (2010) Research Interests: Dr. Bradley specializes in microalgal-based nutrient recovery, wastewater surveillance for public health monitoring, PFAS degradation using nanomaterials, and sustainable resource recovery systems. His work integrates biological processes with environmental engineering to optimize wastewater treatment efficiency and develop predictive models for water quality and health outcomes. Publications: His recent research includes advancements in microalgal cultivation (EcoRecover process), wastewater-based epidemiology for SARS-CoV-2 tracking, and computational enzyme design for PFAS remediation. These studies demonstrate interdisciplinary expertise spanning environmental engineering, biotechnology, and public health analytics.
Stefano Galelli is a tenured Associate Professor in the School of Civil and Environmental Engineering at Cornell University, where he leads the Critical Infrastructure Systems Lab. He also holds an adjunct position as a Research Scientist at the Lamont-Doherty Earth Observatory, Columbia University. His career spans roles in Singapore, including a Postdoctoral Research Fellow at NUS (2011–2013) and faculty at the Singapore University of Technology and Design (2013–2023). Dr. Galelli earned his B.Sc. (2004), M.Sc. (2007), and Ph.D. (2011) in Environmental and Land Planning Engineering and Information Technology from Politecnico di Milano, Italy. His research focuses on the interactions between critical infrastructure systems and natural environments, emphasizing adaptive management solutions for water-energy systems. Techniques include process-based modeling, climatology, statistical learning, control theory, and optimization. He explores topics like hydro-climatic variability impacts, dam re-operation for environmental flows, and cyber-physical security in infrastructure. His contributions to journals such as Nature Sustainability, Earth’s Future, and Environmental Modelling & Software have earned him multiple awards, including the Early Career Research Excellence Award (2014) and SUTD Excellence in Research Award (2017). He has served as an editor for several journals and is recognized for advancing interdisciplinary approaches to water-energy nexus challenges. Teaching highlights include foundational mathematics courses and advanced topics in data analytics, optimization, and water-energy management. He is developing new courses on data-driven control of coupled human-natural systems and risk management for interconnected systems.
Dr. Chenming Zhang is an Advanced Queensland Industry Research Fellow at the School of Civil Engineering, The University of Queensland. His research focuses on hydrological processes in coastal and terrestrial groundwater systems, with particular emphasis on evaporation-driven mass and heat transport in soils and tailings, and hydrogeochemical dynamics in aquifers and mine waste systems. Specializes in IoT-based environmental monitoring Develops numerical models for coastal aquifer dynamics Conducts field and laboratory experiments on tailings behavior Research interests span coastal hydrology, groundwater modeling, mine waste management, and environmental monitoring. He works on contamination transport, aquifer protection, and climate impacts on water systems. Recent publications analyze: Iron curtain formation in subterranean estuaries Sea water intrusion mechanisms Salinity dynamics in tidal wetlands Smart sewer monitoring systems Scientific awards include the prestigious Advanced Queensland Industry Research Fellowship. He supervises multiple PhD projects on mine waste hydrology and coastal aquifer management, with notable collaboration on: Evolution Mining's gold tailings projects ARC Discovery Projects on coastal processes Grange Resources' PAF cell instrumentation His work combines field measurements, laboratory testing, and computational modeling to address critical environmental challenges in mining and coastal zones.
Patrick Kastner is an Assistant Professor at the School of Architecture and holds an adjunct appointment at the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He directs the Sustainable Urban Systems Lab, focusing on environmental performance simulation and urban decarbonization. His work emphasizes software tools for sustainable urban decision-making, such as Eddy3D, a microclimate modeling toolkit widely adopted in academia and practice. Education: Ph.D. and M.S. in Systems Science and Engineering, Cornell University (2022, 2021) M.S. in Sustainable Building Science, Technical University of Munich (2017) B.S. in Energy Engineering, University of Erlangen–Nuremberg (2012) Research Interests: Environmental performance simulation, urban decarbonization, machine learning applications in urban systems, spatial analysis, and software development for sustainability. His work integrates computational fluid dynamics (CFD), surrogate modeling, and data-driven approaches to address urban climate challenges. Key Projects: Leads the Vertically Integrated Project SMUR (Surrogate Modeling for Urban Regeneration), fostering interdisciplinary collaboration across Georgia Tech. Developed Eddy3D, which streamlines microclimate simulations for architects and urban planners. Grants & Advising: Engages students from sophomore to graduate levels in sustainability research. Teaches at Cornell and UPenn previously. Advises on projects blending engineering, urban design, and climate science. Labs & Teams: Director of the Sustainable Urban Systems Lab, focusing on software tools for sustainable urban transformation. Collaborates with industry partners and global institutions on decarbonization strategies.
Dr. Amir Ghanbaripour is a Discipline Lead in Planning, Property, and Project Management at Bond University's Faculty of Society & Design, with a PhD in Construction Project Management (2020). He teaches postgraduate courses and leads the Project Management program. His expertise spans project management methodologies, systems thinking, organizational maturity, and gender equality in projects. He is an active member of the Project Management Institute (PMI) as Associate Director for Academic Outreach. Education: PhD in Construction Project Management (Bond University, 2020), MSc in Civil Engineering (Iran University of Science and Technology, 2012), BSc in Civil Engineering (Amirkabir University of Technology, 2009). Research focuses on project success models, agile methodologies, and technology integration in construction education. He leads research projects on megaprojects, sustainable practices, and gender diversity in the industry. Grants include the 2023 FSD Research Project Grant (focusing on construction project strategies) and the 2023 FSD Deans Award (exploring robotics in manufacturing). He supervises PhD candidates and collaborates with national/international organizations on project management innovation.
Scott Moura is a Professor in Civil and Environmental Engineering at the University of California, Berkeley, holding the Clare and Hsieh Wen Shen Distinguished Professorship. He serves as the Acting Director of the Institute of Transportation Studies (ITS) and directs the Energy, Controls, and Applications Lab (eCAL). Previously, he was Faculty Director of the California Program for Advanced Transportation Technology (PATH) starting January 2022, with recent news (June 2025) confirming new leadership roles at both ITS and PATH. Education: B.S. in Mechanical Engineering, University of California, Berkeley, 2006 M.S.E. in Mechanical Engineering, University of Michigan, Ann Arbor, 2008 Ph.D. in Mechanical Engineering, University of Michigan, Ann Arbor, 2011 Postdoctoral Fellow, University of California, San Diego, Cymer Center for Control Systems and Dynamics, 2013 Visiting Researcher, MINES ParisTech, Centre Automatique et Systèmes, Paris, 2013 Moura's research spans multi-scale energy systems: battery modeling and control at component level, electrified/connected vehicles at system level, and distributed energy resources/smart grid integration at grid scale. His work pioneers real-time battery health estimation, fast-charging algorithms, and vehicle-grid integration to enhance capacity, safety, and efficiency while minimizing degradation. Key methodological contributions include PDE control theory, adaptive control frameworks, and machine learning applications for energy storage systems. Scientific Awards: ASME Division of Control Systems Outstanding Young Investigator Award National Science Foundation CAREER Award NSF Graduate Research Fellowship UC Presidential Postdoctoral Fellowship University of Michigan Distinguished ProQuest Dissertation Honorable Mention University of Michigan Rackham Merit Fellowship College of Engineering Distinguished Leadership Award ITS Faculty of the Year Award (2020) As eCAL Lab Director, Moura mentors undergraduate/graduate students, postdocs, and visiting scholars in developing battery monitoring software and control systems. His research attracts significant funding including a $10M USDOT grant for rural autonomous vehicle freight (2025) and the I-40 Corridor SMART Grant (2024), with industry partnerships focused on practical deployment of energy management solutions. Current projects address EV longevity, HOV lane optimization via AI traffic signals, and climate impact assessments for California infrastructure. eCAL Lab operates at the forefront of energy systems research, combining theoretical control frameworks with experimental validation. The lab's work on battery degradation models directly informs industry practices, while its vehicle-grid integration research supports California's clean energy transition. Recent initiatives include KTH Royal Institute of Technology student exchanges and Bay Area climate impact assessments.
Dr. Ralph Evins is an Associate Professor and Director of the Graduate Program in the Department of Civil Engineering at the University of Victoria. He holds affiliations with the Urban Energy Systems laboratory at Empa and ETH Zurich in Switzerland. His expertise spans building energy simulation, energy system optimization, and machine intelligence applications in sustainable design. Evins holds an MEng from Imperial College London and an EngD from the University of Bristol. His research focuses on computational problem-solving in energy systems, including surrogate modeling, optimization algorithms, and machine learning. He develops tools like the Holistic Urban Energy Simulation (HUES) platform and BESOS software framework to bridge building, district, and city-scale energy analysis. His work emphasizes holistic systems thinking, integrating energy hubs, thermal modeling, and digital twin technologies. Recent articles explore surrogate model refinement, inverse modeling for building characterization, and decarbonization strategies. He collaborates with industry to translate academic innovations into practical solutions. Evins advises students in energy systems and leads projects on net-zero building design, retrofit prioritization, and smart grid integration. His research addresses challenges in climate adaptation, energy efficiency, and sustainable urban development through interdisciplinary approaches.
Norman Sadeh is a Professor in the School of Computer Science at Carnegie Mellon University (CMU), where he has made significant contributions to cybersecurity, privacy, and AI research. He has co-founded and co-directed several groundbreaking graduate programs at CMU, including the Privacy Engineering Program (2012-present), the Ph.D. Program in Societal Computing (2003-2013), and the MBA track in Technology Strategy and Product Management (2005-2017). Carnegie Mellon University, School of Computer Science Software and Societal Systems Department CyLab Security and Privacy Institute Manufacturing Futures Institute Dr. Sadeh received his Ph.D. in Computer Science at CMU with a major in Artificial Intelligence and a minor in Operations Research. He holds an M.Sc. in computer science from the University of Southern California and a BS/MS degree in electrical engineering and applied physics from the Free University of Brussels (Belgium) as 'Ingénieur Civil Physicien.' Professor Sadeh's research spans cybersecurity, online privacy, Human-AI Interaction, AI governance, mobile computing, the Internet of Things, user-oriented machine learning, and language technologies. He is particularly known for his pioneering work on AI-based privacy enhancing technologies, including privacy assistants, automated privacy compliance tools, and NLP-based privacy solutions. His work has influenced the design of privacy features at major technology companies including Apple, Google, and Facebook/Meta, as well as privacy policies at regulatory agencies like the Federal Trade Commission and the California Office of the Attorney General. Analysis of his recent publications shows a strong focus on practical privacy solutions, particularly in mobile and IoT contexts, with an emphasis on making privacy more usable and understandable for end users. His work bridges technical innovation with policy implications, addressing both the technological and human aspects of privacy protection. 2018 Outstanding Entrepreneur of the Year award from the Pittsburgh Venture Capital Association Test of time award by the AAAI Conference on Web and Social Media (ICWSM) Gartner Group's Magic Quadrant leader in Security Awareness Computer-Based Training for 4 consecutive years Deloitte's Technology Fast 500 recognition for 3 consecutive years Professor Sadeh has advised numerous students, including PhD candidates like Aerin (Shikhun) Zhang, whose dissertation focused on understanding diverse privacy attitudes. His research has been funded through various grants, including NSF SaTC projects, and has resulted in technologies that protect tens of millions of users worldwide. He also founded Wombat Security Technologies, which was acquired by Proofpoint in 2018 and whose technologies are used by over 75% of Fortune 100 companies. Professor Sadeh leads several research initiatives including the Privacy Engineering Program, the Usable Privacy Policy Project, the Personalized Privacy Assistant Project, and CMU's Privacy Infrastructure for the Internet of Things. His Mobile Commerce Lab and E-Supply Chain Management Lab have produced influential research that has been commercialized by major organizations including IBM, Raytheon, Boeing, and the U.S. Army.
Edward Andò is a Principal Scientist and Lecturer at École Polytechnique Fédérale de Lausanne (EPFL) , with affiliations to the IMAGING group and the College of Engineering (ENAC) . His work bridges software development, experimental geomechanics, and educational initiatives in image analysis. Principal Scientist, IMAGING-GE (EPFL) Lecturer, Sciences et Génie Civil (SGC-ENS) Lecturer, Enseignement à la Défense (EDEE-ENS) Research Interests Andò specializes in 3D image analysis , with a focus on X-ray tomography , digital volume correlation (DVC) , and micromechanical modeling of granular materials. His work addresses geomechanical failure mechanisms, soil dynamics, and open-source software tools like SPAM for practical material analysis. Publication Trends His recent articles (2025–2023) emphasize X-ray tomography for studying granular deformation , rock failure , medical imaging , and soft particle compaction . Topics span geomechanics, computational modeling, and software development for experimental validation. Labs and Teams Andò contributes to the IMAGING group at EPFL, where he co-develops the SPAM (Software for Practical Analysis of Materials) . His teaching includes courses like Fundamentals of Image Analysis and Quantitative Imaging for Engineers , which integrate hands-on training with theoretical frameworks.
Renate Sachse is a Researcher and Responsible Investigator at the Chair of Structural Analysis, Technical University of Munich (TUM), under Prof. Kai-Uwe Bletzinger. She holds a Dr.-Ing. from the University of Stuttgart and has held postdoctoral positions at Harvard University (Bertoldi Lab) and TU Munich's Institute for Computational Mechanics. Her research focuses on biomimetic adaptive structures, biomechanics, and smart materials. Education M.Sc. in Civil Engineering (University of Stuttgart, 2014) – Thesis: "Isogeometric Contact Analysis of Thin-Walled Structures" B.Sc. in Civil Engineering (University of Stuttgart, 2011) – Thesis: "Elementary School Pavilion Structural Analysis" Study Abroad: École Spéciale des Travaux Publics (ESTP, France, 2012) Research Interests Her work integrates principles from biology and mechanics to design adaptive structures, including motion design, soft robotics, and active metamaterials. Notable projects include studying snapping mechanisms in plants (e.g., Venus flytrap) and developing bio-inspired systems like Flectofold shading devices. She also explores isogeometric analysis and structural optimization for thin-walled and slender structures. Grants & Awards Bertha Benz Prize 2022 (Daimler and Benz Foundation) Klaus Tschira Boost Fund Fellowship (€80,000 interdisciplinary grant) 3rd Place AVK-Prize for Innovations (2017, Flectofold Shading System) GAMM Juniors Fellowship (2020–2022) Teaching & Grants She teaches advanced finite element methods and nonlinear mechanics at TUM and has supervised projects in computational mechanics. Her grants include CareerDesign@TUM funding and the Klaus Tschira Fellowship for high-risk, interdisciplinary research. Labs & Teams Associated with the Chair of Structural Analysis at TUM, collaborating on projects like livMatS (Living Materials Systems) and the Harvard SEAS Bertoldi Lab. Involved in software development (e.g., Carat++, Kiwi!3d) and third-party initiatives (CoDA, FlexWing).
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.
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.
Mark S. Handcock is a Distinguished Professor in the Department of Statistics and Data Science at the University of California, Los Angeles (UCLA), where he leads research at the intersection of statistical methodology and applied problems in social sciences, epidemiology, and environmental science. His work bridges theoretical statistics with real-world challenges through innovative methodological development. His primary research interests encompass statistical models for social networks, network inference, methodology for hard-to-reach population surveys, spatial processes, demography, and environmetrics. Handcock has pioneered advances in exponential-family random graph models (ERGMs) and developed foundational R packages like ergm and tergm within the statnet suite, enabling sophisticated network analysis across disciplines. Analysis of his recent publications (2023-2025) reveals three dominant research thrusts: (1) Antarctic sea ice modeling using Bayesian reconstruction and temporal variability analysis, (2) epidemiological modeling of infectious disease transmission dynamics (particularly COVID-19), and (3) methodological innovations in network inference and causal analysis over stochastic networks. His work consistently integrates advanced computational statistics with domain-specific applications in climate science, public health, and social systems.
Dr. Michel Chaaya is a Senior Lecturer in Civil Engineering at the University of Sydney, with expertise in project management, construction engineering, and sustainability. He holds a PhD from the University of Sydney and is a Fellow of the Institution of Engineers Australia and the College of Leadership and Management. His research focuses on innovative project management methodologies, sustainable construction practices, and BIM implementation. Education: BE, ME(Res), PhD in Project Management and IT from the University of Sydney. Research Interests: Enhancing project success through risk management, modular construction, and BIM adoption. He emphasizes communication, sustainability, and community wellbeing in construction projects. Recent projects include studies on net-zero steel production, BIM in SMEs, and NCC 2022 energy requirements. Awards: ARCHIBUS Excellence Awards (2017-2013), Best Residential Development Awards (2009-2010), and Australian Postgraduate Award (1997). Teaching: Courses include Project Planning, Professional Practice in Engineering Management, and Global Project Management. He has supervised over 250 theses since 2003. Industry Roles: Director of Business Development for multiple organizations, specializing in construction, IT systems, and real estate. He advises on complex project delivery and stakeholder management.
Professor Chongmin Song is a faculty member at the University of New South Wales (UNSW), affiliated with the School of Civil and Environmental Engineering. His academic rank is Professor, and he specializes in computational mechanics with a focus on innovative numerical methods. He holds a BE and ME from Tsinghua University and a DEng from the University of Tokyo. His research explores computational mechanics, fracture analysis, wave propagation, and soil-structure interactions. Key methodologies include the Scaled Boundary Finite Element Method (SBFEM), image-based modeling, and dynamic simulations of infrastructure systems. He leads significant ARC-funded projects like 'A scaled boundary framework for nonlinear dynamic analysis of structures' (DP250100955) and 'Developing sustainable graded porous cementitious structures' (LP240100123), totaling over $1M in recent grants. Recent publications emphasize adaptive modeling techniques, multiphysics simulations, and high-performance computing applications. Trends include topology optimization for structural dynamics, phase-field fracture modeling for brittle materials, and GPU-accelerated elastodynamics. His work integrates computational efficiency with real-world engineering challenges, particularly in geomechanics and material failure analysis. Professor Song collaborates extensively on projects involving computational fracture mechanics and maintains laboratories focused on numerical simulation advancements. Future work targets scalable algorithms for 3D crack propagation and multiphysics coupling in infrastructure systems.
![](https://bond.edu.au/profile/"https://bond.edu.au/sites/default/files/styles/quote_portrait/public/2023-08/amir-ghanbaripour.jpg?h=10090962&itok=bsqp1mtc")
