Find Academic Supervisors

Yehuda Ben-ZionView profile

Professor

• Geophysics
• Seismology
• Earthquake Dynamics
• +3 more

Yehuda Ben-Zion is a Professor of Earth Sciences at the University of Southern California (USC), affiliated with the Dornsife College of Letters, Arts and Sciences. He serves as Director of the Statewide California Earthquake Center (SCEC). His expertise lies in geophysics and seismology, with a focus on earthquake mechanics, fault dynamics, and seismic hazard assessment. He holds a Ph.D. in Geophysics and Seismology from USC (1990) and a B.S. in Geology and Physics from The Hebrew University of Jerusalem (1982). Research interests include physics of earthquakes and faults, high-resolution fault zone imaging, earthquake source properties, and dynamic rupture processes. Recent work emphasizes multi-scale modeling of rupture zones, seismic velocity monitoring using anthropogenic signals (e.g., train tremors), and probabilistic seismic hazard analysis frameworks like CyberShake. He leads projects such as Quakeworx, an open-source earthquake simulation platform, and investigates fault zone architecture in regions like the San Andreas, San Jacinto, and Marmara faults. His studies address critical questions about large earthquake mechanisms, ground motion prediction, and the interplay between tectonic stress and seismicity patterns. He has pioneered the use of dense seismic arrays and machine learning to analyze seismic data, advancing understanding of fault zone processes and their implications for hazard mitigation.

Md Manjurul AhsanView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +7 more

Dr. Md Manjurul Ahsan serves as a Research Assistant Professor in the Department of Industrial & Systems Engineering at the University of Oklahoma, where he develops AI-driven solutions for healthcare diagnostics and advanced manufacturing optimization. His work bridges theoretical AI advancements with practical industrial and medical applications. Education: Ph.D. in Industrial and Systems Engineering, University of Oklahoma M.S. in Industrial Engineering, Lamar University B.S. in Industrial and Production Engineering, Shahjalal University of Science and Technology Research Focus: Dr. Ahsan specializes in Artificial Intelligence with technical depth in Machine Learning , Deep Learning , and Computer Vision to solve critical challenges in healthcare diagnostics and additive manufacturing . His research emphasizes Explainable AI to enhance model trustworthiness and deployment efficiency across Cyber-Physical-Social Systems, with significant contributions to Aerospace and Defense applications. Publication Trends: Recent work (2023-2025) reveals a strategic expansion from core manufacturing applications into medical AI (diffusion models for diagnostics), cultural preservation (NLP for Dravidian languages), and geopolitical AI analysis. His publications consistently address data imbalance challenges while advancing digital twin integration in quality control systems. Scientific Recognition: GCOE Dissertation Excellence Award (2023) International Student Scholarship (2022) Outstanding Academic Achievement in Engineering (2022) IEEE IEMCON Best Paper Award (2020) Netti Vincent Boggs Engineering Excellence Award (2020) Research Leadership: As director of the Sooner Additive Manufacturing Laboratory , Dr. Ahsan leads cross-disciplinary teams developing real-time monitoring systems using FARO arms and CMM metrology. His postdoctoral work at Northwestern University (2023-2024) advanced AI deployment frameworks, resulting in 60+ peer-reviewed publications with multiple papers ranking in engineering's top 1% for citations.

Olga FinkView profile

Assistant Professor

• Machine Learning
• Predictive Maintenance
• Industrial IoT
• +3 more

Olga Fink is a Tenure Track Assistant Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Department of Intelligent Maintenance and Operations Systems (IMOS) within the School of Architecture, Civil and Environmental Engineering (ENAC). She also holds roles in PhD program committees for Civil and Environmental Engineering (EDCE) and Robotics, Control, and Intelligent Systems (EDRS). Her research focuses on machine learning for infrastructure monitoring, predictive maintenance, and physics-informed AI models. She teaches courses on machine learning, data science for infrastructure, and advanced deep learning topics. Fink advises multiple PhD students and is involved in interdisciplinary projects such as ThermoNeRF (multimodal 3D thermal modeling) and physics-informed neural networks for fault diagnostics. Her work bridges AI and engineering with applications in smart infrastructure, energy systems, and industrial IoT. Education: PhD in Engineering (inferred from role) Affiliations: IMOS Lab, ENAC-SGC, EPFL PhD Committees (EDCE, EDRS) Key Research Themes: Explainable AI, Digital Twins, Structural Health Monitoring, Domain Adaptation Her publications (2023–2025) emphasize robust AI for industrial systems, including fault detection in high-voltage equipment, multimodal data fusion, and physics-consistent models. She collaborates on EU and industry-funded projects, focusing on real-world applications like predictive maintenance and energy efficiency.

John H. ShawView profile

Professor

• Structural Geology
• Seismology
• Tectonics
• +3 more

John H. Shaw is the Harry C. Dudley Professor of Structural and Economic Geology and Professor of Environmental Science & Engineering at Harvard University's School of Engineering and Applied Sciences (SEAS). He specializes in structural geology, earthquake hazards, and geomechanics, with a focus on thrust fault systems, fault-related folding, and seismic risk assessment in regions like California and China. His research integrates field observations, 3D modeling, and geomechanical simulations to understand fault dynamics and their implications for societal safety. Shaw's work emphasizes quantitative analysis of fault geometry, slip rates, and rupture processes. Key projects include modeling ground deformation during earthquakes, assessing seismic hazards in fold-thrust belts, and investigating reservoir-induced seismicity. He leads the Structural Geology & Earth Resources Group and contributes to collaborative initiatives like the Southern California Earthquake Center (SCEC). His articles highlight advancements in fault system modeling, including 3D structural reconstructions, distinct element method applications, and coupling geomechanical models with fluid flow simulations. Recent studies focus on the Wilmington blind-thrust fault beneath Los Angeles, the Ventura fault system, and tectonic evolution of the Canadian Rockies and Qaidam Basin. Shaw's research also addresses interdisciplinary challenges such as stochastic velocity modeling for earthquake ground motion prediction and developing open-source tools like the SCEC Unified Community Velocity Model (UCVM). His work bridges fundamental structural geology with applied seismic hazard mitigation strategies.

Raj RajkumarView profile

Professor

• Connected and autonomous driving
• Cyber-physical systems
• Embedded and real-time systems
• +3 more

Raj Rajkumar is the George Westinghouse Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in the Robotics Institute. He holds leadership roles as Director of the USDOT Mobility21 and Safety21 National University Transportation Centers, and Director of the Metro21: Smart Cities Institute. His work focuses on cyber-physical systems, autonomous driving, and vehicular networking. Education: Ph.D. in Electrical and Computer Engineering from CMU (1989). Research interests include connected/autonomous vehicles, cyber-physical systems, embedded systems, and vehicular networking. Key projects include the General Motors-CMU Collaborative Research Lab and the development of autonomous vehicle protocols like Ballroom Intersection Protocol. Notable awards include the 2016 National Academy of Inventors Fellowship and the 2017 Pittsburgh Business Times Innovation Award. His publications span real-time systems, sensor networks, and automotive cyber-physical frameworks. Rajkumar advises on autonomous vehicle safety, energy efficiency, and societal impacts, with frequent media engagements on self-driving technologies.

Allen HuskerView profile

Research Professor

• Geophysics
• Seismology
• Planetary Seismology
• +3 more

Allen Husker is a Research Professor of Geophysics at the California Institute of Technology (Caltech), affiliated with the Seismological Laboratory. He manages the Southern California Seismic Network (SCSN) and the Southern California Earthquake Data Center. Previously, he was a professor at the National Autonomous University of Mexico (UNAM), chairing the Seismology Department, and served as Station Manager for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) seismic stations in Mexico. His academic journey includes a B.S. from the University of Washington (1998), an M.S. from UCLA (2003), and a Ph.D. from Caltech (2008). Research Interests : Husker focuses on geophysical observations of crustal structure, slow-slip events, and seismic network analysis. His work bridges subduction zones (e.g., Mexico) and transform boundaries (e.g., Southern California). He explores planetary seismology, comparing Earth with the Moon and Mars. Recent studies include DAS technology for moonquake detection and seismic monitoring in the Guerrero seismic gap. Publications Trends : His 2024 work emphasizes DAS applications, Mexico’s San Andreas Fault dynamics, and socio-technical aspects of earthquake early warning (EEW) in Mexico. Earlier research (2020s) delves into slow-slip mechanisms, crustal anisotropy, and fault system dynamics in Mexico. He also investigates moonquake behavior and lunar regolith effects. Awards : No explicit scientific awards listed. Advising & Grants : Advises graduate students like Guillermo González (UNAM) and Yuri Tamama (Caltech). Former students include Francesco Civilini (Research Space Scientist) and Jiuxun Yin (Research Geophysicist). Collaborates widely, including with Jennifer Jackson on lunar seismology. Labs/Teams : Leads the SCSN and collaborates with UNAM’s Seismology Department. Engaged with the CTBTO and international seismological networks.

Neal DriscollView profile

Professor

• Tectonic Deformation
• Marine Geology
• Geohazards
• +3 more

Neal Driscoll is a Professor of Geology and Geophysics at the Geosciences Research Division, Scripps Institution of Oceanography, UC San Diego. He specializes in tectonic deformation, landscape evolution, and seafloor imaging, with a focus on understanding Earth's processes through sediment records. Driscoll co-directs UC San Diego’s Center for Public Preparedness (CP2) and leads ALERTCalifornia, a critical infrastructure network monitoring wildfires, floods, and earthquakes via over 1,000 cameras. His work bridges geohazard mitigation, climate impacts, and disaster response. Education: B.S., Geology, University of New Hampshire M.S., Oceanography, University of Rhode Island Ph.D., Columbia University (Lamont-Doherty Earth Observatory) Research Interests: Driscoll investigates tectonic deformation’s role in shaping landscapes and seascapes, particularly in response to climate and sea-level changes. His fieldwork includes high-resolution seafloor imaging and seismic data analysis in regions like Iceland and California. He also studies neotectonics, geohazards, and coastal processes, with recent focus on the San Andreas Fault system and Salton Trough rift dynamics. ALERTCalifornia: This program uses advanced camera networks to monitor natural disasters, providing real-time data for first responders and researchers. Its infrastructure, originally for earthquake monitoring, now supports multi-hazard tracking, including wildfires and landslides, enhancing public safety and environmental understanding. Awards: Office of Naval Research Young Investigator Award Heezen Award and Storke Award (Lamont-Doherty Earth Observatory) Scripps Undergraduate Teaching Award MIT Distinguished Crosby Lecturer Advising & Grants: Driscoll has mentored students in geology and geophysics, with grants supporting his research on fault systems, climate impacts, and disaster preparedness. His collaborative projects include the Salton Seismic Imaging Project and Arctic Ocean sediment studies. Labs & Teams: Leads ALERTCalifornia and CP2 teams, collaborates with Scripps’ Geosciences Research Division on marine geophysics and tectonic studies, and partners with global institutions like WHOI and Icelandic research groups.

Suzanne CarbotteView profile

Research Professor

• Marine Geophysics
• Mid-Ocean Ridges
• Multi-channel Seismics
• +6 more

Suzanne M. Carbotte is a Bruce Heezen Lamont Research Professor at the Lamont-Doherty Earth Observatory (LDEO) and affiliated with the Columbia Climate School . She holds a PhD in Marine Geophysics from the University of California, Santa Barbara (1992), an M.Sc. in Geophysics from Queen's University (1986), and an H.B.Sc. in Geology and Physics from the University of Toronto (1982). Marine and Polar Geophysics Department, LDEO Key focus areas: Mid-ocean ridges, subduction zones, seismic imaging, geoinformatics Research Interests : Carbotte specializes in marine geophysical studies of oceanic crust formation, subduction zone dynamics, and cyberinfrastructure development for geoscience data. Her work integrates seismic reflection, sonar mapping, and geoinformatics tools to analyze crustal evolution, magma chamber processes, and sediment dynamics in regions like the East Pacific Rise, Juan de Fuca Ridge, and Hudson Estuary. Scientific Trends : Recent publications highlight 3D/4D seismic imaging of magmatic-hydrothermal systems, sediment consolidation in subduction zones, and data infrastructure innovations. Key subfields include melt sill dynamics, fault distribution in oceanic plates, and mantle temperature gradients. Scientific Awards 2015 AGU Fellow 2010 Ridge2000 Distinguished Lecturer 2008 Birch Lectureship & UCSB Distinguished Alumni Award 2007 Bruce C. Heezen Research Chair 1982 Governor General's Silver Medal Grants & Projects : Her career spans funding for initiatives like the Rolling Deck to Repository (R2R) program, EarthCube Building Blocks , and Integrated Earth Data Applications (IEDA) . She has led 16 marine expeditions, emphasizing seismic studies from ridge to trench.

Ghassan AlRegibView profile

Professor

• Machine Learning
• Image and Video Processing
• Computer Vision
• +7 more

Ghassan AlRegib is the John and Marilu McCarty Chair Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology. He directs the Omni Lab for Intelligent Visual Engineering and Science (OLIVES), the Center for Energy and Geo Processing (CeGP), and previously led Georgia Tech's MENA initiatives (2015-2018). His research spans machine learning, image processing, and seismic interpretation with real-world applications in autonomous vehicles, medical imaging, and subsurface analysis. His research focuses on trustworthy AI systems through three pillars: enhancing interpretability, improving robustness/generalizability, and tackling domain-specific challenges. Key interests include human-in-the-loop frameworks, uncertainty quantification, explainable AI, and physics-driven learning. The OLIVES lab pioneered modern machine learning applications in seismic interpretation and developed open-source datasets for geological fault analysis. Dr. AlRegib's scientific contributions include over 270 publications, multiple U.S. patents, and leadership roles as Technical Program co-Chair for ICIP 2020/2024. His work demonstrates significant impact through awards like the IEEE Fellow designation (2022) and multiple best paper awards at premier conferences. IEEE Fellow (2022) 2023 EURASIP Best Paper Award 2019 ICIP Best Paper Award 2017 Denning Faculty Award for Global Engagement CSIP Research & Service Awards (2003) He has advised numerous PhD students including Dr. Ashraf Alattar (now Auburn professor) and Dr. Zhiling Long (Kennesaw State faculty). His lab structure emphasizes collaborative teams comprising postdocs, senior/junior PhD students, and undergraduates working on high-impact problems from autonomous systems to medical diagnostics. Current research thrusts include trustworthy neural networks, human-in-the-loop frameworks, and deployment of machine learning in seismic interpretation and ophthalmology.

Cynthia EbingerView profile

Professor

• Geophysics
• Rifts
• Seismic Monitoring
• +3 more

Cynthia Ebinger is a Professor in the Department of Earth and Environmental Sciences at Tulane University, affiliated with the School of Science & Engineering. She holds the Marshall-Heape Chair and previously served at the University of Rochester and as an Adjunct Professor at Royal Holloway, University of London. Her research focuses on geophysics, rift systems, seismic monitoring, volcanoes, and plate tectonics in West Africa and East Africa, particularly the Turkana Depression and East African Rift. She has conducted fieldwork in Ecuador, Peru, Kenya, Uganda, Ethiopia, and Australia. Education : Ph.D., MIT/WHOI, Joint Program in Oceanography, Marine Geology & Geophysics (1988) M.A., MIT, Geophysics (1986) B.S., Duke University, Geology (1982) Research Interests : Dr. Ebinger investigates continental rifting mechanisms, magmatic processes, seismic anisotropy, and volcanic systems. Her work integrates geophysical methods (e.g., InSAR, receiver functions) to study deformation in regions like the East African Rift and Gulf of Mexico passive margin. She emphasizes understanding crustal dynamics, lithosphere modification, and the interplay between tectonics and surface processes. Publications : Her recent work addresses rift linkage mechanics, crustal anisotropy variations, and volcanic deformation (e.g., Nyiragongo eruption). Key themes include seismic imaging of rift zones, subsidence patterns in coastal Louisiana, and mantle lithosphere interactions. Awards : American Geophysical Union Distinguished Lecturer (2023-2024) NASEM Jefferson Science Fellow (2022-2023) Woollard Award (2021) Tulane Honors Professor of the Year (2021) Grants & Collaborations : Leads projects funded by NSF and international collaborations, focusing on Turkana Depression geodynamics, Gulf of Mexico subsidence, and volcanic monitoring in East Africa. Active in education initiatives to strengthen quantitative geophysics training. Labs/Teams : Core member of the Tulane Earth Sciences group and collaborates with global networks (e.g., Project TRAILS in East Africa). Engages in field-based research and satellite geodesy applications.

Prashanth KrishnamurthyView profile

Researcher

• Robotics
• Control Systems
• Cyber-Physical Systems
• +3 more

Prashanth Krishnamurthy is a Research Scientist in the Department of Electrical and Computer Engineering at New York University Tandon School of Engineering. His research focuses on robotics, control systems, and cybersecurity, particularly in cyber-physical systems such as power grids and embedded devices. He holds a Ph.D. in Electrical Engineering from NYU. Key research areas include hardware security (e.g., detecting Trojans in chips), anomaly detection in critical infrastructure, and resilient control strategies for robotic systems. He has led or contributed to projects funded by the U.S. Department of Energy (DOE), Office of Naval Research (ONR), and others, including the Tracking Real-time Anomalies in Power Systems (TRAPS) initiative and hardware Trojan detection using short-term aging phenomena. Education: Ph.D., Electrical Engineering, NYU His work bridges theoretical advancements and practical implementations, such as developing FPGA-based testbeds for hardware security validation and creating AI-driven cybersecurity tools like the CRAKEN LLM agent. Collaborators include institutions like SRI International, Karlsruhe Institute of Technology, and the NYU Center for Cybersecurity. Grants include a $1.94M DOE grant for TRAPS and a $359K DURIP grant for hardware Trojan detection. His technical contributions span control systems, anomaly detection algorithms, and cybersecurity frameworks for embedded systems. He is actively involved in advancing secure cyber-physical systems through innovations in real-time monitoring, robust control mechanisms, and AI-augmented security solutions.

• Structural Engineering
• Structural Health Monitoring
• Civil Engineering
• +3 more

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.

Sergey FomelView profile

Professor

• Geophysics
• Seismic Data Analysis
• Computational Seismology
• +3 more

Sergey Fomel is a Professor of Geophysics at the University of Texas at Austin, holding the Wallace E. Pratt Professorship and serving as Director of the Texas Consortium for Computational Seismology (TCCS). He is affiliated with the Jackson School of Geosciences, Bureau of Economic Geology, and the Oden Institute for Computational Engineering and Sciences. His research focuses on seismic data analysis, computational seismology, and machine learning applications in geophysics. He leads the Madagascar software project for open-source geophysical data analysis. Dr. Fomel earned his Ph.D. in Geophysics from Stanford University in 2001. He has held leadership roles in the Society of Exploration Geophysicists (SEG), including Vice President, Publications (2017–2019) and Distinguished Lecturer (2020). His awards include honorary memberships in SEG and the Geophysical Society of Houston (GSH). Recent research emphasizes deep learning for seismic inversion, noise reduction, and fault segmentation. His work addresses challenges in geophysical data processing, including adaptive algorithms, wave propagation modeling, and CO2 monitoring. Fomel's contributions span both theoretical and applied domains, bridging computational methods with practical geoscience applications. Education: Ph.D. in Geophysics, Stanford University (2001) Affiliations: Jackson School of Geosciences, Bureau of Economic Geology, Oden Institute Labs/Teams: Texas Consortium for Computational Seismology (TCCS), Madagascar Project

Brandon ShuckView profile

Assistant Professor

• Solid-Earth Geophysics
• Tectonic Processes
• Active-Source Seismic Imaging
• +5 more

Brandon Shuck is an Assistant Professor in the Department of Geology & Geophysics at Louisiana State University (LSU), part of the College of Science. His research focuses on solid-earth geophysics, particularly tectonic processes within plate boundaries and mature tectonic settings. He uses active-source seismic reflection and wide-angle ocean-bottom seismometer data to image subsurface lithospheric architecture and integrate interdisciplinary datasets including bathymetry, borehole logs, and geodynamic models. Education: Ph.D. in Geological Sciences (2021) from the University of Texas at Austin; B.S. in Geology (Petroleum Emphasis) and Mathematics (2015) from Western Colorado University. Previously served as a Postdoctoral Fellow at Lamont-Doherty Earth Observatory, Columbia University (2021–2024). Research Interests: Tectonic evolution of the lithosphere at plate boundaries, feedbacks between lithospheric stress and fluid-rock interactions, geologic hazards related to subduction zones, and mantle dynamics during continental breakup. Active projects include studies of subduction initiation in the Tyrrhenian Sea, megathrust fault segmentation in Cascadia, and water content in the Cocos Plate offshore Mexico. Current opportunities include an NSF-funded PhD position (starting Fall 2025) investigating mantle dynamics during early Atlantic seafloor spreading, involving seismic data acquisition on the R/V Langseth. His group emphasizes collaborative, interdisciplinary approaches combining seismic imaging, field geology, and modeling. Awards: None explicitly listed, though his work has been supported through NSF funding and institutional grants. Lab/Team: Directs the LSU Solid-Earth Geophysics Research Group, which integrates geophysical data analysis with field observations to address tectonic questions at multiple scales.

• Structural Health Monitoring
• Civil Infrastructure
• Machine Learning for Engineering
• +7 more

Dr. Andy Nguyen is a Senior Lecturer in Structural Engineering at the University of Southern Queensland, within the School of Engineering. He is an active researcher and educator, specializing in the Structural Health Monitoring (SHM) of critical civil infrastructure such as bridges, buildings, and transport tunnels. Bachelor of Engineering (BEng), NUCE, 1999 Master of Engineering (MEng), NUCE, 2003 Doctor of Philosophy (PhD), Queensland University of Technology (QUT), 2014 Dr. Nguyen's research is at the forefront of integrating advanced technologies into civil engineering. His primary focus is on developing and deploying sophisticated SHM systems that utilize sensors, data analytics, and machine learning to provide real-time insights into the structural integrity of ageing infrastructure. His work aims to enable proactive maintenance, extend the lifespan of structures, and enhance public safety. He has successfully implemented monitoring systems on major bridges and high-rise buildings in Queensland and New South Wales, with systems capable of even detecting distant earthquake events. His research interests span Structural Health Monitoring, Machine Learning for Engineering, Damage Detection, Finite Element Model Updating, Sustainable Building Materials like bamboo, and the application of AI for automated condition assessment of transport infrastructure. The analysis of his recent publications reveals a strong and consistent research trajectory centered on the application of data-driven and AI methods to solve practical problems in civil infrastructure. His work frequently combines signal processing techniques (like Stockwell Transform) with deep learning models for tasks such as crack detection in concrete and pavement. He also conducts significant research on model updating for complex structures like cable-stayed and arch bridges, using vibration data and optimization algorithms. The integration of machine learning for overload classification and the development of cost-effective, automated monitoring systems are key trends in his recent output. Advanced Queensland Fellow (2024-2027) Dr. Nguyen is actively involved in research supervision and collaboration. He is currently supervising several postgraduate students on projects related to AI-powered condition assessment, bamboo as a sustainable building material, and railway track design. He receives research funding from the Queensland Government through his Advanced Queensland Fellowship. His research has direct practical applications, as evidenced by his public engagement, such as writing for The Conversation on safeguarding ageing bridges, and his work with the Australian Network of Structural Health Monitoring. Dr. Nguyen's work embodies the development of a next-generation 'Living' Laboratory for engineering education, where research, teaching, and real-world infrastructure monitoring are integrated. His current projects involve creating smart, automated fault detection systems and advancing 'digital twin'-based monitoring platforms for infrastructure.