جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Graph Neural Networks
• Time Series Analysis
• +۷ مورد دیگر

Filippo Maria Bianchi is an Associate Professor in the Department of Mathematics and Statistics at UiT The Arctic University of Norway, where he conducts research at the intersection of machine learning, dynamical systems, and complex networks. He is also a Senior Researcher at NORCE Norwegian Research Centre and actively contributes to the IEEE Task Force on Learning for Structured Data and the ELLIS Society. Department: Department of Mathematics and Statistics School: Faculty of Science and Technology University: UiT The Arctic University of Norway Adjunct Position: Senior Researcher, NORCE Education: Bachelor’s in Computer Engineering, Sapienza University of Rome Master’s in Artificial Intelligence & Robotics, Sapienza University of Rome (cum laude, 2012) PhD in Machine Learning, Sapienza University of Rome His research focuses on graph machine learning, time series analysis, reservoir computing, and probabilistic forecasting , with applications in energy analytics and remote sensing. He has led and contributed to numerous projects involving Arctic power grids, satellite-based environmental monitoring, and deep learning for sustainability. The recent publications reflect a strong trend in graph neural networks —particularly pooling mechanisms, spatiotemporal modeling, and explainability—alongside applications in energy forecasting, avalanche detection, and remote sensing . His work combines theoretical innovation with real-world impact, especially in Arctic and remote environments. Scientific Affiliations and Leadership: Vice-Chair, IEEE Task Force on Learning for Structured Data Member, ELLIS Society Co-founder, Northernmost Graph Machine Learning group Member, IEEE Task Force on Reservoir Computing Visiting Professor, Politecnico di Milano (2024–2025) He actively mentors students and collaborates on interdisciplinary research. He has led projects in power grid reliability, solar fault detection, and unsupervised change detection in satellite imagery . His work is supported by open-source implementations and reproducible research practices. Laboratories and Research Groups: Northernmost Graph Machine Learning group (co-founder) ARC Research Group, UiT Graph Machine Learning Group, Lugano

Stephen Croftمشاهده پروفایل

استاد

• Nuclear Materials Measurement Science
• Radiation Detection
• Nuclear Spectroscopy
• +۳ مورد دیگر

Professor Stephen Croft is a faculty member at Lancaster University , affiliated with the School of Engineering . His research focuses on Nuclear Materials Measurement Science , with expertise in radiation detection, neutron interrogation, and X-ray/gamma-ray spectroscopy. Current projects include cosmic ray neutron monitoring , active neutron interrogation of nuclear materials , and radiation damage assessment . His recent publications emphasize semi-empirical modeling of atomic interactions and advanced detection techniques for nuclear applications. He has contributed to understanding vacancy transfer probabilities , X-ray fluorescence cross-sections , and water detection in nuclear environments . His work supports nuclear security, power plant safety, and space weather monitoring. Scientific awards : None explicitly mentioned in the text. Research groups : Involved in Nuclear Space Weather initiatives.

Esmaeel Esmaeeliمشاهده پروفایل

مدرس ارشد

• Structural Engineering
• Sustainable Construction
• Composite Materials
• +۳ مورد دیگر

Dr. Esmaeel Esmaeeli is a Senior Lecturer in Civil and Environmental Engineering at Brunel University London, serving as Course Director for the MSc in Structural Engineering. His work focuses on sustainable structural retrofitting solutions, safety, and resilience of concrete and masonry structures. Brunel University London (Current: Senior Lecturer) Queen’s University Belfast (Postdoctoral Fellow, Horizon 2020 MSC Fellowship) University of Minho (PhD research on Hybrid Composite Plate) K. N. Toosi University (MSc research on seismic strengthening) His research spans advanced materials like Strain-Hardening Cementitious Composite (SHCC) and Carbon Fibre Reinforced Polymer (CFRP) for seismic retrofitting, computational modeling of FRP-concrete interfaces, and dynamic response under extreme loads. Recent work includes the SMArtPlate and Hybrid Composite Plate (HCP) systems. Scientific recognition includes the Horizon 2020 Marie Skłodowska-Curie Individual Fellowship and a Portuguese Foundation for Science and Technology (FCT) scholarship. He has advised on structural vulnerability assessments and leads teams in consultancy projects.

• Hydrogeology
• Groundwater hydraulics
• Seepage flow
• +۳ مورد دیگر

Dr. FARKAS Dávid is an Assistant Professor in the Department of Hydraulic and Water Resources Engineering, Faculty of Civil Engineering, Budapest University of Technology and Economics (BME). His office is located in Building K, basement level, room 12/7, and he holds weekly consultation hours on Mondays from 1–3 pm. Educational contributions include teaching core courses in hydrogeology and groundwater engineering: Groundwater (BMEEOVVMV63) Hydrogeology (BMEEOGMMG62) Infrastructural Design Project (BMEEODHAI41) Research activities concentrate on quantitative hydrogeology, with a special emphasis on karstic groundwater systems, seepage hydraulics, and the safety of flood-protection levees. He couples field investigations in iconic Hungarian cave systems (Buda Castle Cave, Molnár János Cave) with laboratory sandbox experiments and numerical modelling to advance understanding of flow and transport processes in fractured carbonates. Over the past decade his work has evolved from fundamental hydrogeological mapping toward the design and deployment of automated monitoring networks that integrate classical hydrological instruments with modern sensor technologies. This progression is evident in his most recent publications (2024-2025) that document the establishment of high-resolution cave monitoring systems capable of capturing rapid responses to precipitation events. Scientific awards currently listed: none. Advising and grants: no specific student names, grant numbers, or funded project titles are provided in the supplied text. Laboratories and teams: while no dedicated laboratory name is stated, his affiliation with the Department of Hydraulic and Water Resources Engineering implies access to the faculty’s hydraulics and hydro-environmental laboratories, including sandbox and seepage modelling facilities.

• Pharmacy Practice
• Medication Management
• Osteoporosis Care
• +۷ مورد دیگر

Associate Professor Stephen Carter is an Associate Professor in Pharmacy Practice at the University of Sydney's Sydney Pharmacy School within the Faculty of Medicine and Health. He serves as the Program Director for Undergraduate Pharmacy programs and is a registered pharmacist with clinical specialisation in medication management review. Stephen holds qualifications including BPharm, MSc, PhD, and Grad Cert Edu (Higher Ed). He is a Fellow of the Pharmaceutical Society of Australia (FPS), Fellow of the Higher Education Academy (FHEA), and holds other professional accreditations. His research focuses on optimizing the role of pharmacists in healthcare, particularly examining how consumers and caregivers obtain and use medicines, designing effective pharmacist services, and supporting pharmacists throughout their professional journey. His work spans areas including osteoporosis care, medication adherence, service quality in community pharmacies, and the application of advanced statistical methods like Structural Equation Modelling. Stephen's publications demonstrate a strong focus on practical pharmacy interventions, with significant work on osteoporosis management services, perinatal depression screening in pharmacies, and digital health approaches to improve medication adherence. His research employs diverse methodologies including randomized controlled trials, qualitative studies, and advanced psychometric analyses. Early Career Investigator Award Australasian Pharmaceutical Science Association (APSA) for 2017 Lesmuller Award for Best Oral Communication - Pharmaceutical Care Network Europe Working Conference, Berlin, 2013 Recipient of the 2013 Annual Best Paper Award by Elsevier publication, Research in Social and Administrative Pharmacy Best Poster Presentation Award: International Social Pharmacy Workshop, Boston, USA, 2014 Top reviewer, Research in Social and Administrative Pharmacy (2015, 2016, 2017, 2019) Stephen actively supervises several graduate students including PhD candidates Fatima Rezea, Steven Tran, Veronika Seda, Kingston Leung, and Joel Hillman, as well as MPhil student Linda Krogh. He has secured significant research funding, including co-leading a $2.36 million Randomized Controlled Trial and managing four current competitive grant-funded projects totaling over $6.3 million. His work has particular emphasis on translating research into practical pharmacy services that improve patient outcomes. Stephen is actively involved in major research initiatives including the #STOP trial (Safer medicines To reduce falls and refractures for OsteoPorosis) and the TICTOC trial (Timely post-discharge medication reviews to Improve Continuity – the Transitions Of Care stewardship), both focusing on innovative pharmacist-led interventions to improve medication safety and effectiveness.

• Public Finance
• Law and Economics
• Competition Policy
• +۸ مورد دیگر

Angelo Castaldo is an Associate Professor in Public Finance at the Faculty of Law, Sapienza University of Rome, with a Ph.D. in Law and Economics from the University of Siena and an M.Sc. in Economics from the University of York. He serves as Chair of the Graduate Program in European Studies (LM-90) and the Master in Competition and Regulation of Markets (CORE), while also holding roles at international institutions like Zhongnan University of Economics and Law in China. Education: Ph.D. in Law and Economics, University of Siena M.Sc. in Economics, University of York, UK Master in Law and Economics, University of Siena Research Focus: Public Finance Law and Economics Environmental Crime Analysis Occupational Safety and Health Competition Policy Technological Innovation Impact His recent publications analyze workplace accident determinants, environmental crime drivers, and taxation policies for sin goods, employing empirical methods across European and Italian contexts. Current research projects focus on technology's impact on occupational safety and public investment incentives for workplace health improvements. He actively participates in academic conferences and serves as co-managing editor for public finance working papers at Sapienza University of Rome.

Hwan-Sik Yoonمشاهده پروفایل

دانشیار

• Advanced Manufacturing
• Artificial Intelligence
• Computer Vision
• +۸ مورد دیگر

Dr. Hwan-Sik Yoon is an Associate Professor in the Department of Mechanical Engineering at The University of Alabama, where he focuses on applying Artificial Intelligence (AI) and Machine Learning (ML) to automotive, transportation, and manufacturing systems. His research spans modeling, simulation, and control of dynamic systems, with a strong emphasis on connected and automated vehicles (CAVs), energy-efficient routing, and sensor fusion technologies. Ph.D., Mechanical Engineering, Ohio State University, 2002 M.S., Mechanical Engineering, Ohio State University, 1998 B.S., Physics Education, Seoul National University, Korea, 1994 Dr. Yoon’s research integrates AI/ML into applications such as traffic signal control , excavator manipulator pose estimation , hybrid electric vehicle powertrain control , and factory floor safety monitoring . He is also involved in additive manufacturing , vision-based control systems , and reinforcement learning -driven automotive innovations. Recent publications highlight trends in deep reinforcement learning for vehicle energy efficiency, sensor fusion for traffic surveillance, and neural networks for dynamic system control. His work addresses challenges in multi-component failure analysis and real-time edge computing platforms . NSF Outstanding Faculty Advisor Award (2019) College of Engineering Faculty Productivity Award, Tennessee Tech University (2012) Dr. Yoon leads the Intelligent Structures and Systems Laboratory and serves as the lead CAVs faculty advisor for the University of Alabama’s EcoCAR student team, which has achieved national recognition in advanced vehicle technology competitions.

• Theoretical Deep Learning
• Uncertainty Quantification
• Reliable Artificial Intelligence
• +۱۰ مورد دیگر

Gianni Franchi is an assistant professor at ENSTA Paris , affiliated with the Computer Science and Systems Engineering Unit (U2IS) . His work focuses on theoretical deep learning , with a strong emphasis on uncertainty quantification, robustness, and explainability in machine learning models. Current affiliation: ENSTA Paris (U2IS) Academic rank: Assistant Professor Key collaborators: David Filliat, Emanuel Aldea, Andrei Bursuc, Antoine Manzanera His research spans uncertainty quantification , explainable AI , and reliable machine learning . He investigates methods like Bayesian neural networks, ensemble approaches, and deterministic uncertainty models. His work also addresses domain adaptation , self-supervised learning , and autonomous systems , particularly in trajectory forecasting and semantic segmentation for autonomous driving. Recent publications analyze probabilistic modeling for robustness, symmetry-aware Bayesian methods , and multi-modal datasets like InfraParis. He develops frameworks like Torch-Uncertainty and benchmarks such as MUAD for uncertainty types in autonomous driving. Key themes: Uncertainty Quantification Deep Learning Theory Autonomous Systems Explainable AI Dataset Creation Bayesian Methods

Richard Allenمشاهده پروفایل

استاد

• Seismology
• Earthquake Early Warning Systems
• Structural Health Monitoring
• +۹ مورد دیگر

Richard Allen is a Professor and the Class of 1954 Endowed Chair at the University of California, Berkeley, serving as Director of the Berkeley Seismological Laboratory. His work focuses on seismology, earthquake early warning systems, and seismic hazard mitigation. Research interests include earthquake rupture mechanisms, regional seismic structure and dynamics, mantle upwelling processes, fault interaction analysis, stress modeling in seismology, and machine learning applications in seismic data analysis. He pioneered smartphone-based seismic networks like MyShake and advanced technologies such as distributed acoustic sensing (DAS) for offshore monitoring. His recent publications highlight trends in earthquake early warning algorithms (EPIC, bEPIC), real-time ground-motion modeling, ShakeAlert system performance, and integration of multimodal data (e.g., social media, LLMs, DAS) for hazard mitigation. Collaborative efforts include global smartphone networks and cloud computing for seismic datasets. Allen leads the Berkeley Seismological Laboratory, driving innovations in seismic monitoring, structural health assessment, and public alerting systems to enhance disaster resilience.

John Dalsgaard Sørensenمشاهده پروفایل

استاد

• Wind Turbines
• Structural Safety
• Risk Analysis
• +۵ مورد دیگر

John Dalsgaard Sørensen is a Professor and Head of Research Group at the Department of the Built Environment, Aalborg University, within the Faculty of Engineering and Science. He leads the Risk, Resilience, Safety, and Sustainability of Systems Research Group and is affiliated with the Danish Centre for Risk and Safety Management. His research focuses on structural safety, wind turbine reliability, probabilistic design, and risk assessment of infrastructure systems. He has supervised 13 PhD students and contributed to over 600 publications. Key research areas include wind turbine structural integrity, fatigue analysis of offshore and onshore structures, probabilistic design standards (e.g., Eurocodes), and risk-based decision-making for infrastructure. He leads projects like Windscanner (remote sensing for wind measurements) and MANTIS (cyber-physical maintenance systems). Collaborations span academia and industry, addressing challenges in energy systems, civil infrastructure, and safety engineering. His work emphasizes practical applications of advanced modeling techniques, such as Bayesian networks and stochastic simulations, to enhance reliability and reduce operational costs. He is actively involved in standardization efforts for structural design and serves on boards like Energi- og MiljøData Fonden. Recent activities include presenting at international conferences and advising on media debates related to structural safety.

• Structural Health Monitoring
• Seismic Analysis
• Bayesian Calibration
• +۱۴ مورد دیگر

Gaetano Miraglia is a Fixed-term Assistant Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at Politecnico di Torino, where he conducts research in structural health monitoring, seismic analysis, and computational modeling. He is a member of the Interdepartmental Center R3C – Responsible Risk Resilience Centre, contributing to interdisciplinary efforts in risk mitigation and infrastructure resilience. His work spans both theoretical and applied domains, with strong emphasis on heritage preservation and sustainable urban development. His research interests include Bayesian calibration of nonlinear models, hybrid simulation, peridynamics, masonry structures, and the integration of satellite interferometric (InSAR) data with in-situ measurements for structural monitoring. He applies advanced computational and machine learning techniques to improve the accuracy and reliability of structural assessments, particularly in historical and monumental buildings. His work supports UN Sustainable Development Goals 9, 11, and 13. His recent publications demonstrate a consistent focus on data fusion, digital twinning, domain adaptation, and real-time damage detection. He frequently collaborates with researchers such as Rosario Ceravolo and Erica Lenticchia, publishing in high-impact journals like Computer-Aided Civil and Infrastructure Engineering , Structures , and Scientific Reports , as well as at major conferences including EWSHM, SAHC, and EVACES. His research is applied in projects such as the monitoring of the Vicoforte Sanctuary and the development of the CAMELOT and HY-LEARN toolboxes. Research Projects: MONITORAGGIO VICOFORTE (2024–2026) – Member of Research Group CAMELOT – PoC Transition (2023–2024) – Member of Research Group HY-LEARN – Model Calibration via Hybrid Simulation and ML (2022–2024) – Scientific Manager (PNRR Mission 4) He teaches in various programs, including as a course collaborator in PhD, Master’s, and Bachelor’s level courses such as Earthquake Engineering , Structural Consolidation , and Seismic Risk of Cultural Heritage . He is also an inventor on national and international patents and software related to the CAMELOT toolbox, highlighting the translational impact of his research. He has no listed scientific awards or formal advisees in the provided text.

Terje Haukaasمشاهده پروفایل

استاد

• Structural Reliability
• Earthquake Engineering
• Probabilistic Mechanics
• +۳ مورد دیگر

Dr. Terje Haukaas is a Professor of Structural & Earthquake Engineering at the University of British Columbia (UBC), Department of Civil Engineering, Faculty of Applied Science. He holds a PhD and Master's from UC Berkeley (2003, 1999) and a bachelor's from the Norwegian University of Science and Technology (1996). His research focuses on probabilistic modeling, structural reliability, and earthquake engineering, with contributions to software development (e.g., FERUM, OpenSees). He teaches courses like Structural Analysis, Nonlinear Analysis, and Reliability & Safety. Education: PhD in Civil Engineering, UC Berkeley, 2003 Master's in Civil Engineering, UC Berkeley, 1999 Bachelor's in Civil Engineering, NTNU, Trondheim, 1996 Engineering Degree (Stavanger University College, 1994) and Technician Degree (Stavanger Technical College, 1992) Research Interests: Probabilistic mechanics and reliability analysis Seismic vulnerability and risk assessment Software tools for finite element analysis (FERUM, OpenSees) Timber engineering and structural optimization Awards & Recognition: UBC Killam Teaching Prize (2016) President of CERRA (2015–2019) Keynote/Semi-plenary speaker at major conferences (ICASP12, COMPDYN 2017) Student Appreciation Awards (Top Professor rankings) Grants & Labs: Recipient of grants supporting seismic risk research Developed computational frameworks for structural analysis

Mikael Rinneمشاهده پروفایل

دانشیار

• Rock Fracture Mechanics
• Geotechnical Engineering
• Nuclear Waste Repository
• +۳ مورد دیگر

Mikael Rinne is an Associate Professor in the Department of Civil Engineering at Aalto University's School of Engineering. His research focuses on rock fracture mechanics and its applications in various engineering contexts including nuclear waste repositories, geothermal energy systems, and underground construction. His expertise spans time-dependent rock failure mechanisms, fracture propagation models, and rock mechanics applications in energy storage and disposal systems. His work has direct applications in projects with Posiva Oy (nuclear waste repository), St1 Deepheat (geothermal energy), and mining operations with companies like First Quantum Minerals. Rinne's research integrates advanced numerical modeling with field applications, particularly in Finnish crystalline bedrock conditions. He has contributed significantly to understanding fracture initiation and propagation in rock masses under various stress conditions, with particular emphasis on long-term stability considerations for deep underground structures. His scholarly work demonstrates strong connections between theoretical fracture mechanics and practical engineering applications, with a focus on ensuring safety and reliability in rock engineering projects. His research has evolved from fundamental fracture mechanics studies to application-focused investigations addressing contemporary challenges in energy and waste management. Rinne has supervised doctoral research in rock mechanics and collaborates with researchers specializing in photogrammetry, virtual reality applications, and energy storage systems, creating a multidisciplinary approach to complex rock engineering problems.

Sameer Mulaniمشاهده پروفایل

دانشیار

• Uncertainty Quantification
• Random Vibrations
• Multi-disciplinary Optimization
• +۱۲ مورد دیگر

Dr. Sameer Mulani is an Associate Professor, Associate Department Head, and Director of Graduate Programs in the Department of Aerospace Engineering and Mechanics at the University of Alabama's College of Engineering. He leads the Stochastic Mechanics and Multi-Disciplinary Optimization Laboratory (SMO Lab) and is an integral part of the Remote Sensing Center and Alabama Materials Institute. Dr. Mulani's research spans uncertainty quantification, random vibrations, multi-disciplinary optimization, and composite structures' multi-scale analysis and design. His work combines computational methods with machine learning to develop innovative solutions for aerospace engineering challenges. He has made significant contributions to self-healing composite materials, uncertainty quantification techniques, and optimization of composite structures. His research group has published extensively on topics including polynomial chaos expansion for uncertainty quantification, self-healing composites, stochastic buckling analysis, and machine learning applications in structural mechanics. The publications demonstrate a strong trend toward integrating probabilistic methods with traditional engineering analysis to improve reliability and safety of aerospace structures. AIAA Associate Fellow, Class of 2025 2025 Department of the Air Force Summer Faculty Fellowship Program 2024 Department of the Air Force Summer Faculty Fellowship Program MSC Software Contest Winner (2011) Night on the Town: General Electric Award (2007) DAAD Fellowship (1999-2000) Dr. Mulani has advised numerous graduate students who have gone on to successful careers at institutions including Los Alamos National Laboratory, Cirrus Aircraft, L3Harris, and Lockheed-Martin. His lab collaborates with various research centers including the Remote Sensing Center where they work on antenna design, manufacturing, and integration for aircraft systems. The SMO Lab utilizes advanced software including MSC NASTRAN/PATRAN, ANSYS Mechanical/FLUENT, ABAQUS, SOLIDWORKS, and CATIA for their simulations and analyses.

• Risk Management
• Risk Analysis
• Uncertainty Quantification
• +۱۲ مورد دیگر

Roger Flage is a Professor of Risk Management at the University of Stavanger, affiliated with the Faculty of Science and Technology and the Department of Security, Economics and Planning. His research focuses on foundational and applied aspects of risk analysis, uncertainty quantification, and decision-making under uncertainty, with applications in critical infrastructure, environmental systems, and offshore energy. Roger Flage's research interests lie at the intersection of risk science, safety engineering, and decision theory. He investigates how uncertainty—especially epistemic uncertainty and assumptions—affects risk assessments, and advocates for more transparent and robust frameworks. His work spans theoretical advances, such as the treatment of 'black swan' events and the concept of 'real risk', as well as practical applications in offshore safety, power systems, and geohazards. He emphasizes the integration of data-driven methods, AI, and digital twins while critically assessing their limitations and associated security risks. His recent publications show a strong trend toward integrating dynamic, data-rich, and interdisciplinary approaches to risk analysis. Themes include the role of time in risk, AI applications, infrastructure interdependencies, and environmental risk in the oil and gas sector. He frequently publishes in top-tier journals like Risk Analysis , Reliability Engineering & System Safety , and Safety Science , often in collaboration with leading scholars such as Terje Aven and Seth Guikema. No scientific awards are mentioned in the provided text. Roger Flage has supervised or collaborated with several researchers, though no formal list of advisees is provided. His work is supported through academic collaborations and institutional affiliations rather than explicit grant mentions. He is actively involved in advancing risk science methodology, particularly in the treatment of assumptions and uncertainty, and contributes to both theoretical foundations and real-world applications in safety-critical domains. He is associated with research groups and collaborative networks at the University of Stavanger, particularly within the Department of Security, Economics and Planning. His work often involves interdisciplinary teams focusing on risk in complex engineered systems, including energy, transportation, and environmental systems.