جست‌وجوی استاد و پژوهشگر

Jerome F. Hajjarمشاهده پروفایل

استاد

• Sustainable and Resilient Steel Structures
• Composite Steel/Concrete Structures
• Earthquake Engineering
• +۷ مورد دیگر

Jerome F. Hajjar is a University Distinguished Professor and CDM Smith Professor in the Department of Civil and Environmental Engineering at Northeastern University, with an affiliation in Marine and Environmental Sciences. He holds a PhD in Structural Engineering from Cornell University (1988) and is a licensed Professional Engineer in Illinois and Minnesota. PhD, Structural Engineering, Cornell University, 1988 MS, Structural Engineering, Cornell University, 1985 BS, Engineering Mechanics, Yale University, 1982 Hajjar’s research focuses on sustainable and resilient steel/concrete composite structures , earthquake engineering , structural stability , and large-scale experimental testing . He pioneered design for deconstruction and physics-guided machine learning for structural analysis. His work addresses climate change risks through offshore wind resilience and hurricane risk assessment. His recent publications emphasize carbon reduction strategies via steel-CLT hybrids, machine learning techniques for seismic modeling, and experimental programs on composite diaphragms. Hajjar’s projects include the STReSS Laboratory , equipped with a reinforced concrete strong floor for full-scale structural testing. 2025 William H. Wisely American Civil Engineer Award 2025 SSRC Distinguished Member Award 2021 AISC Lifetime Achievement Award 2018 Robert D. Klein Lectureship 2007 ASCE Fellow Hajjar mentors PhD students, including R. Bailey Bond (2024), and leads major initiatives like the Academic Center for Reliability and Resilience of Offshore Wind (ARROW) and the Steel Diaphragm Innovation Initiative . His advocacy extends to integrating sustainability, resilience, and equity into national building codes through roles in the Structural Engineering Institute and American Society of Civil Engineers.

• Artificial Intelligence
• Explainable AI (XAI)
• Green AI
• +۱۲ مورد دیگر

Dr Andrew Starkey is a Reader in the School of Engineering at the University of Aberdeen, where he also completed his PhD in 2001. He holds an Honours degree in Applied Mathematics from the University of St Andrews. He is actively involved in research and currently accepting PhD students in Engineering. His work bridges academia and industry, with a focus on AI applications in engineering, bioinformatics, and geosciences. University: University of Aberdeen School: School of Engineering Academic Rank: Reader Email: a.starkey@abdn.ac.uk Phone: +44 (0)1224 272801 Dr Starkey's research centers on Explainable AI (XAI) , Green AI , and Autonomous AI , with applications in robotics, econometrics, bioinformatics, seismic data analysis, and virtual reality. He has developed novel methods for feature selection, autonomous learning, and knowledge abstraction from agent-environment interactions. His work emphasizes low computational cost and transparency in AI systems. The most recent publications reflect a strong trend in applying AI to complex real-world problems, including digital rock technology, robotic grasping, real-time event detection, and medical data analysis. His interdisciplinary research combines machine learning with domain-specific knowledge in engineering and life sciences, often resulting in practical, industry-ready solutions. Millennium Product Award John Logie Baird Award for Innovation Enterprise Fellowship from Royal Society of Edinburgh and Scottish Enterprise Dr Starkey has supervised multiple research projects and secured funding from major bodies including EPSRC, BBSRC, and industry partners. His past work on the GRANIT project led to the development of AI-based condition monitoring for ground anchorages, resulting in commercialization through BlueFlow Ltd. He has collaborated with researchers across disciplines, including Dr Alasdair MacKenzie (bioinformatics), Dr Anne Schwab (seismic analysis), and Dr David Hazlerigg (genomics). He leads research in AI-driven engineering solutions and is the CEO of BlueFlow Ltd, a spinout company commercializing AI technologies developed at the University of Aberdeen. His lab focuses on developing autonomous, explainable, and environmentally sustainable AI systems for real-world deployment.

• Maritime Engineering
• Machine Learning
• Risk Analysis
• +۴ مورد دیگر

Mingyang Zhang is a Postdoctoral Researcher at the Department of Energy and Mechanical Engineering , Aalto University, Finland. His research focuses on the intersection of Maritime Engineering and Artificial Intelligence , particularly in Digital Twin Technology , Ship Motion Prediction , and Risk Analysis for Arctic and inland waterway operations. Awarded Best Paper at G-NAOE 2024 Honored with 5 Highly Cited Paper Awards (2021-2024) Active in Marine and Arctic Technology research group His machine learning work addresses ship fuel consumption prediction , collision avoidance , and grounding risk assessment , with applications in autonomous shipping and offshore wind farm monitoring . Key publications span Reliability Engineering , Ocean Engineering , and Marine Hydrodynamics journals. Recent article trends include: Digital Twin applications for shipping decarbonization (2024) Deep learning models for 6-DoF ship motions and focused wave prediction (2023) Big Data Analytics for Arctic navigation risks and inland waterways (2022-2021) Integration of HFACS and fault tree analysis in risk modeling (2019) Scientific achievements include: 2024: Best Paper, G-NAOE Conference 2023: 2 Highly Cited Paper Awards 2022: 2 Highly Cited Paper Awards 2021: Highly Cited Paper Award 2019: Best Paper, 5th International Conference on Transportation Information and Safety Current research at the Marine and Arctic Technology group emphasizes AI-driven maritime safety , real-time risk monitoring , and data-intensive shipping decarbonization projects. Collaborations include Spyros Hirdaris , Pentti Kujala , and Jakub Montewka .

Ashly Cabasمشاهده پروفایل

استادیار

• Seismic Hazards
• Geotechnical Engineering
• Earthquake Ground Motions
• +۵ مورد دیگر

Ashly Cabas is an Assistant Professor in the Department of Civil, Construction and Environmental Engineering at North Carolina State University (NC State). She leads the GEOHAZARDS AND EARTHQUAKE ENGINEERING (GEOQUAKE) RESEARCH LAB , focusing on geotechnical aspects of earthquake engineering, including seismic hazard assessment, ground motion modeling, and liquefaction-induced ground deformations. Her work integrates geospatial analytics, numerical modeling, and probabilistic frameworks to enhance infrastructure resilience against seismic risks. Research interests include: Predictive modeling of liquefaction-induced lateral spreading Regional seismic velocity modeling for coastal plains Geostatistical analysis of ground motion data Impact of fluvial geomorphology on seismic hazards Advances in site response analysis methodologies Her research team examines large-scale ground motion databases (e.g., KiK-Net, DesignSafe) and collaborates on projects like the 2023 Gulf/Atlantic Coastal Plains Seismic Model . Key recent contributions involve improving input ground-motion selection protocols and developing databases for hazard mitigation. Grants & Awards: She leads a NSF CAREER Award (2022) focused on probabilistic seismic site response modeling under uncertainty. Her work emphasizes reproducible research practices, as highlighted in publications advocating for open data/code sharing. Labs/Teams: Directs the GEOQUAKE Lab, which bridges geotechnical engineering and computational methods to address societal risks from earthquakes. Collaborations include global case studies (e.g., 2011 Christchurch earthquake, 2018 Anchorage earthquake).

Monica Kohlerمشاهده پروفایل

استاد پژوهشی

• Earthquake Engineering
• Seismic Tomography
• Structural Health Monitoring
• +۵ مورد دیگر

Monica Kohler is a Research Professor in the Department of Mechanical and Civil Engineering at the California Institute of Technology (Caltech). She holds a B.A. from Harvard University (1988) and a Ph.D. from Caltech (1995). Prior to her current role, she served as an Assistant Research Engineer at UCLA (1998–2011), Visiting Associate at Caltech (2007–2011), and Research Assistant Professor (2011–2017). Her work focuses on earthquake engineering, seismic tomography, and structural health monitoring using advanced sensor technologies. Her research integrates observational seismology and engineering principles to detect damage in buildings and infrastructure through dense sensor networks like the Community Seismic Network (CSN). Projects include developing methods for damage identification using seismic data, tsunami early warning systems, and real-time monitoring of urban vibrations from human activity (e.g., concerts). Key areas of exploration include earthquake-induced building response, wave propagation analysis, and the application of Bayesian learning and Gaussian process regression for ground-motion modeling. She advises graduate students at UCLA in civil engineering and collaborates on interdisciplinary projects involving oceanography, structural dynamics, and computational modeling. Her contributions span over 150 publications, including studies on the 2019 Ridgecrest earthquakes, tsunami wavefront mapping, and high-rise structural identification. She also leads efforts to deploy seafloor sensors and improve early warning systems for natural disasters. Labs/Teams: Active in the Caltech CSN project, structural health monitoring initiatives, and tsunami hazard research groups. Her team includes researchers like Viviana Vela, Gloria Hyun, and Richard Guy.

Agathoklis Giaralisمشاهده پروفایل

مدرس ارشد

• Structural Dynamics
• Earthquake Engineering
• Structural Health Monitoring
• +۱۱ مورد دیگر

Dr. Agathoklis Giaralis is a Senior Lecturer in Structural Engineering within the Department of Civil Engineering at the School of Engineering and Mathematical Sciences, City, University of London. He earned his PhD in Civil & Environmental Engineering from Rice University, USA, in 2008, following an MSc and a 5-year Diploma (Ptychion) in Structural Engineering from Aristotle University of Thessaloniki, Greece. He is a Fellow of the Higher Education Academy, UK. PhD, Civil & Environmental Engineering, Rice University, USA (2008) MSc, Seismic Design of Structures, Aristotle University of Thessaloniki, Greece (2004) Ptychion (5 yr Diploma), Civil/Structural Engineering, Aristotle University of Thessaloniki, Greece (2003) Dr. Giaralis's research is centered on nonlinear stochastic dynamics and time-frequency signal analysis , applied to critical areas such as earthquake engineering , seismic structural design and assessment , structural health monitoring (SHM) , and passive vibration control . His work is pioneering in the development and application of inerter-based vibration control systems, such as the Tuned Mass-Damper-Inerter (TMDI), for enhancing the resilience of structures. He also explores compressive sensing and low-power wireless sensors for sustainable SHM, as well as digital twinning and machine learning in wind engineering. His recent research has significant implications for offshore wind turbines and urban wind comfort. An analysis of his 15 most recent publications reveals a consistent and cutting-edge research trajectory focused on the optimization and application of inerter-based devices for structural control. The work spans from developing analytical tuning formulas for TMDIs to conducting experimental validation on shaking tables and exploring novel applications in offshore wind turbines and composite floors. A strong emphasis is placed on performance-based design , uncertainty quantification , and practical implementation for real-world infrastructure. His scientific contributions have been recognized by prestigious awards, including the Fulbright Exchange Student Program scholarship for his PhD studies and a Fellowship from the Higher Education Academy . He is also a member of several leading professional organizations such as the American Society of Civil Engineers (ASCE) and the Society for Earthquake and Civil Engineering Dynamics (SECED). Dr. Giaralis is actively involved in research funding and academic mentorship. He has secured significant grants from Innovate UK and the EPSRC to support his work on machine learning-based design and optimal inerter configurations. He supervises a cohort of PhD students whose theses focus on advanced topics like adaptive control of bridge joints, inerter-based energy harvesting, and seismic assessment using digital twins. He also leads the Smart Structures and Structural Health Monitoring Research Unit , driving collaborative research in smart infrastructure technologies.

• Artificial Intelligence
• Simulated and Digital Reality
• Computer Graphics
• +۵ مورد دیگر

Prof. Dr. Philipp Slusallek serves as Scientific Director and executive board member at the German Research Center for Artificial Intelligence (DFKI), where he leads the Agents and Simulated Reality research area. He holds a Full Professorship in Computer Graphics at Saarland University since 1999, co-founded the European AI initiative CAIRNE as Director of Strategy, and directs research at the Intel Visual Computing Institute. His career spans leadership roles in the Excellence Cluster on Multimodal Computing and Interaction and prior visiting positions at Stanford University and Nvidia Research. His academic foundation includes: 1983-1990: M.Sc. in Physics, University of Tübingen 1992-1995: Ph.D. in Computer Science, University of Erlangen Slusallek's research bridges Artificial Intelligence, Simulated Reality, and Computer Graphics with applications in high-performance computing, motion synthesis, and AI for science. His interdisciplinary work integrates real-time rendering, heterogeneous system programming (CPU/GPU/FPGA), and biomechanical modeling, driving innovations in digital reality frameworks and AI-driven simulation systems across medical, engineering, and autonomous vehicle domains. His 2025 publications reveal a strong focus on graphics compilation (Vulkan SPIR-V), rehabilitation biomechanics, and multi-agent motion simulation, demonstrating consistent integration of computer graphics foundations with emerging AI methodologies for practical real-world applications. Award highlights include the Eurographics Gold Medal (2023), acatech membership (2018), Land of Ideas Awards (2015, 2010), and Eurographics Fellowship (2013), recognizing his transformative contributions to computer graphics and AI. Eurographics Gold Medal (2023) acatech Membership (2018) Land of Ideas Award: Display as a Service (2015) Fellow of Eurographics Association (2013) CeBIT Innovation Award (2013) Land of Ideas Award: DFKI Visualization Center (2010) Slusallek leads major research initiatives including B5GCyberTestV2X (cybersecurity for autonomous driving), ENGAGE (AI computing environments), Carousel+ (digital character interaction), PRIME (predictive rendering), and TAILOR (trustworthy AI). His DFKI research group pioneers virtual environment frameworks while his academic mentorship has shaped generations of computer graphics researchers through Saarland University's programs. He co-founded the Intel Visual Computing Institute and established foundational visualization infrastructure at DFKI, maintaining active leadership in European AI strategy through CAIRNE and prior service on the European Commission's High-Level Expert Group on AI.

Wojciech Solowskiمشاهده پروفایل

دانشیار

• Geotechnical Engineering
• Computational Geomechanics
• Numerical Modeling of Soils
• +۷ مورد دیگر

Dr. Wojciech Solowski is an Associate Professor at Aalto University , specializing in computational simulations of soils and granular materials with a focus on numerical methods and constitutive modeling. His research spans geotechnical engineering, environmental geomechanics, and computational mechanics. Research Interests : Numerical modeling (FEM/MPM), THMC behavior of soils, unsaturated soil mechanics, soil improvement, frost susceptibility, ground vibrations, and laboratory testing. Scientific Contributions : Dr. Solowski has extensively advanced the Material Point Method (MPM) for large deformation problems in geotechnics and developed the in-house finite element code Thebes for THMC coupling simulations. His work addresses critical challenges in nuclear waste repositories, soft soil stabilization, and offshore sediment characterization. Publication Trends : Recent articles focus on MPM for marine clay analysis, THMC coupling in bentonite barriers, 3D shrinkage deformation measurements, and geophysical-geotechnical integration for offshore wind farms. His research emphasizes practical applications in energy transition and infrastructure resilience. Affiliations : Mineral Based Materials and Mechanics research group at Aalto University. Committee Roles : International Secretary of the Finnish Geotechnical Society; member of ISSMGE TC106 (unsaturated soils) and ERTC7 (numerical methods).

Shahram Pezeshkمشاهده پروفایل

استاد

• Engineering Seismology
• Earthquake Engineering
• Ground Motion Prediction
• +۵ مورد دیگر

Shahram Pezeshk is the Chair and Emison Professor of Civil Engineering at The University of Memphis, affiliated with the Herff College of Engineering. His research focuses on engineering seismology, earthquake engineering, ground motion prediction, and structural optimization. He holds prestigious awards including the 2014 Herff College Outstanding Research Award and the Emison Professorship. Education: B.S., Civil Engineering, University of Illinois, Urbana-Champaign (1982) M.S., Civil Engineering, University of California, Berkeley (1983) Ph.D., Civil Engineering, University of Illinois, Urbana-Champaign (1989) Research Interests: Dr. Pezeshk's work spans engineering seismology and seismic hazard analysis, including ground motion prediction equations (GMPEs) used in USGS hazard maps. He also explores structural optimization and probabilistic seismic design. His research has been applied to projects like the 2014 NSHMs and LNG tank station hazard analysis. Grants & Awards: Recipient of multiple research awards from the Herff College and University of Memphis Featured Engineer (2002) and Don P. Smith Professorship (1999-2002) Listed in Who's Who in Science and Engineering Advising & Teams: Dr. Pezeshk supervises a diverse research team, including doctoral students (e.g., Nima Nazemi, Niloufar Alidadi) and postdoctoral researchers (e.g., Behrooz Tavakoli). His lab focuses on seismic hazard assessment, ground motion modeling, and structural resilience.

Nadine Meyerمشاهده پروفایل

پژوهشگر

• Nanophotonics
• Cavity Optomechanics
• Levitation Optomechanics
• +۳ مورد دیگر

Dr. Nadine Meyer is a researcher at the Nanophotonics Systems Laboratory (light.ethz.ch/) within ETH Zurich, Switzerland. Her work focuses on levitation optomechanics with nanoparticles, developing hybrid levitation platforms and metasurfaces for fundamental and applied research in cavity optomechanics and inertial sensing applications. Her research centers on quantum optomechanics using optically levitated nanoparticles in vacuum environments. Key investigations include ground-state cooling of mechanical modes, mechanical squeezing phenomena, and the development of ultrathin tunable optomechanical metalenses. She also pioneers applications in chemical nanoreactors and ultra-precise inertial sensing systems, leveraging quantum effects at the nanoscale. Analysis of her 15 most recent publications (2019-2025) reveals a clear trajectory toward integrating metasurfaces with levitated optomechanical systems and advancing quantum control techniques for nanoparticles. Her work consistently bridges fundamental quantum physics with practical sensor development, particularly through collaborations within the Nanophotonics Systems Laboratory. The Nanophotonics Systems Laboratory, led by Professor Romain Quidant, provides the experimental infrastructure for Dr. Meyer's research. Located at CLA E 17.1, Tannenstrasse 3, Zürich, the laboratory specializes in optical trapping technologies, vacuum systems, and quantum measurement techniques for levitated nanoparticles.

Gulen Ozkulaمشاهده پروفایل

استادیار

• Seismic Design
• Steel Structures
• Earthquake Engineering
• +۴ مورد دیگر

Gulen Ozkula is an Assistant Professor of Civil Engineering at the University of the District of Columbia's School of Engineering and Applied Sciences. She specializes in seismic design, evaluation, and rehabilitation of steel structures, with a focus on steel columns and their behavior under extreme loading conditions. Her research integrates experimental methods, numerical modeling, and performance-based design principles to enhance structural resilience against earthquakes and seismic hazards. Education: Executive MBA, Istanbul University Post-Doctorate, Tokyo Institute of Technology Post-Doctorate, University of California, San Diego Ph.D., University of California, San Diego M.S., University of Illinois at Urbana-Champaign B.S., Celal Bayar University Research Interests: Ozkula’s work addresses critical challenges in seismic engineering, including cyclic stability of steel columns, high-performance steel materials, and seismic risk assessment. She explores innovative solutions for retrofitting existing structures and improving design codes through advanced testing methodologies and data analysis. Key Research Trends: Her publications emphasize experimental testing of steel beam-column subassemblages, field reconnaissance of recent earthquakes (e.g., Turkey 2023), and classification of buckling modes in steel columns. Findings often inform practical design guidelines and safety protocols for earthquake-prone regions. Grants & Advising: While specific grants are not listed, her active research program suggests involvement in funded projects related to seismic engineering. No current advisees are noted in the provided information. Labs & Teams: While not explicitly mentioned, her experimental work implies affiliation with structural testing facilities and interdisciplinary teams focused on earthquake engineering and materials science.

Hakan Temeltaşمشاهده پروفایل

استاد

• Robotics
• Autonomous Systems
• Control Engineering
• +۶ مورد دیگر

Professor Hakan Temeltaş is affiliated with Istanbul Technical University , where he serves in the Department of Control and Automation Engineering . His research focuses on robotics, control systems, and autonomous technologies. He has contributed to advancements in motion planning, localization, and deep reinforcement learning for robotic systems. Research Interests: Robotics, Autonomous Systems, Control Engineering, Machine Learning Current Projects: Deep reinforcement learning for quadrupedal robots, localization frameworks, multi-agent systems His recent work includes autonomous exploration strategies using Rapidly-Exploring Random Trees (RRT), multi-stage localization for mobile robots, and quaternion-based orientation estimation in robot manipulators. He supervises projects involving adversarial attack mitigation and self-recovery mechanisms in quadrupedal robots. Publications highlight applications of deep reinforcement learning in robotics, with a focus on dynamic stability, sensor fusion, and simulation environments. His research outputs span conferences like IEEE RAAI and journals such as Robotica and Unmanned Systems . Scientific Awards : None explicitly mentioned in the provided data. As a principal investigator, he leads projects on ground reaction force balancing, autonomous navigation, and swarm robotics. His collaborations extend to simulation frameworks and real-time control systems for mobile robots.

Jorge Macedoمشاهده پروفایل

استادیار

• Geotechnical Earthquake Engineering
• Advanced Numerical Modeling (FEM, FDM, MPM, DEM)
• Performance-Based Engineering
• +۸ مورد دیگر

Jorge Macedo is an Assistant Professor and Frederick L. Olmsted Early-Career Professor at the School of Civil and Environmental Engineering , Georgia Institute of Technology. He received his B.S. and M.S. in civil engineering and soil mechanics from the Peruvian National University of Engineering (2007-2011), followed by M.S. (2014) and Ph.D. (2017) in Geoengineering from UC Berkeley. Education: B.S. Civil Engineering (2007), Peruvian National University of Engineering M.S. Soil Mechanics (2011), Peruvian National University of Engineering M.S. Geoengineering (2014), UC Berkeley Ph.D. Geoengineering (2017), UC Berkeley His research focuses on geotechnical earthquake engineering , advanced numerical modeling (FEM, FDM, MPM), performance-based design , and mining geotechnics . He applies machine learning and reliability tools to assess seismic risks, particularly in liquefaction and residual drift modeling. Recent work examines nonergodic ground motion models, slope stability under subduction earthquakes, and mine tailings behavior. The 2025-2024 publications highlight trends in machine learning for hazard assessment , nonergodic ground motion modeling , and mine tailings analysis . Articles address slope systems, liquefaction effects, and physics-informed neural networks in seismic analysis. Scientific Awards: Young Researcher Award (2023), ISSMGE Technical Committee NSF CAREER Award (2022) Dr. Macedo's work bridges academic research with industry applications , including collaborations with Golder Associates and contributions to geotechnical asset management in Georgia. He actively participates in curriculum development, emphasizing data analytics and computational skills.

• Sensor network data analysis
• Crowdsourced data analysis from citizen science initiatives
• Statistical modeling and analysis of spatio-temporal data
• +۳ مورد دیگر

Francesco Finazzi is a full professor of statistics (SECS-S/02) at the Department of Economics of the University of Bergamo and maintains a research affiliation with the School of Mathematics and Statistics at the University of Glasgow. He is internationally recognized as the founder of the Earthquake Network citizen science initiative (www.sismo.app), which pioneered the first globally implemented smartphone-based seismic early warning system. His research expertise spans sensor network data analysis, crowdsourced data from citizen science initiatives, statistical modeling of spatio-temporal data, and parallel scientific software development. He has made significant contributions to developing statistical methodologies for earthquake parameter estimation using smartphone sensor networks and has advanced techniques for analyzing environmental time series data. His recent publications reveal a strong research trajectory focused on earthquake early warning systems, spatio-temporal environmental modeling, and statistical approaches to crowdsourced seismic data. His work uniquely bridges statistics, seismology, and computer science to develop practical, real-world early warning solutions that leverage mobile technology and citizen participation. Finazzi has secured substantial research funding as Principal Investigator for the University of Bergamo in major Horizon 2020 projects, including RISE (Real-time earthquake risk reduction for a ReSilient Europe, 2019-2023, €8,000,000) and TURNkey (Towards more Earthquake-resilient Urban Societies through a Multi-sensor-based Information System, 2019-2022, €7,999,948). He leads the Earthquake Network initiative, a groundbreaking citizen science project that has created the first operational smartphone-based seismic early warning system worldwide. This platform not only provides early warnings but also facilitates rapid impact assessment and supports search and rescue operations following seismic events.

Ben Leshchinskyمشاهده پروفایل

استاد

• Geotechnical Engineering
• Landslide Hazards
• Slope Stability
• +۷ مورد دیگر

Ben Leshchinsky is a Professor and Richardson Chair in the Department of Forest Engineering, Resources & Management at Oregon State University's College of Forestry. He specializes in geotechnical engineering with focuses on landslide hazards, slope stability, and geosynthetic applications. His research integrates numerical modeling, remote sensing, and field monitoring to address natural hazard challenges in forested and coastal environments. Education: Ph.D., Civil Engineering, Columbia University (2012) M.Phil, Civil Engineering, Columbia University (2010) M.S., Civil Engineering, Columbia University (2008) B.S., Civil Engineering, University of Delaware (2007) Research Interests: Landslide dynamics and mitigation Coastal erosion forecasting Wildfire-landslide interactions Geotechnical infrastructure resilience Numerical modeling of slope failure mechanisms His recent publications emphasize landslide susceptibility modeling, coastal highway vulnerability assessment, and post-wildfire geohazard analysis. He leads the Landslide Hazards Research Lab, advancing interdisciplinary approaches to natural hazard mitigation. Advises graduate students and teaches courses on soil mechanics, geosynthetics, and slope stability analysis. Key Contributions: Developed the RegionGrow3D algorithm for 3D landslide source characterization Pioneered real-time landslide displacement monitoring techniques Advocated for climate-resilient transportation infrastructure planning