جست‌وجوی استاد و پژوهشگر

Mahdi Safaمشاهده پروفایل

استادیار

• Construction Management
• Sustainability in Construction
• Supply Chain Optimization
• +۷ مورد دیگر

Mahdi Safa is an Instructional Assistant Professor at the University of Houston's Cullen College of Engineering, Department of Civil and Environmental Engineering. His research focuses on digital transformation in construction, supply chain optimization, workplace safety, and disaster management. He has published extensively on topics such as AI applications in engineering, pandemic response logistics, and ethical challenges in smart city development. Research interests include leveraging emerging technologies (IoT, blockchain, AI) to enhance construction processes and safety. His work also addresses global challenges like energy efficiency in buildings, offshore infrastructure resilience, and mental health in the construction industry. Notable contributions include frameworks for vaccine supply chain management during pandemics, analysis of workplace conflicts affecting safety, and strategic project readiness assessments. Though no awards or grants are listed in the provided text, his publications indicate active involvement in interdisciplinary research collaborations. Contact: msafa@central.uh.edu

Patricia Claytonمشاهده پروفایل

دانشیار

• Structural Engineering
• Natural Hazards Engineering
• Earthquake Engineering
• +۴ مورد دیگر

Patricia Clayton, Ph.D., PE, is an Associate Professor specializing in structural and natural hazards engineering. Her office is located at 455 Vine Street, Bldg 60 South, Rm 4512, and she can be reached via phone at 336.702.1924. She holds a B.S. in Civil Engineering from North Carolina State University (2007), an M.S. (2010) and Ph.D. (2013) in Civil Engineering from the University of Washington. Her research focuses on: Hazard-resistant structural technologies Multi-scale modeling of natural hazard impacts Applications of 3D printing in construction Computational modeling and data analysis Small-scale structural testing methodologies She maintains active investigations in earthquake engineering and structural resilience. Recent publications (2022-2025) demonstrate three primary research streams: Structural Seismic Performance : Innovations in steel connections, composite systems, and deployable structures Engineering Education : Remote teaching pedagogy and inclusive curriculum development Disaster Technology : AI-enhanced damage assessment and field instrumentation Her work consistently integrates experimental validation with practical applications.

George T. Heinemanمشاهده پروفایل

دانشیار

• Software Engineering
• Component-Based Software Engineering
• Software Architecture
• +۳ مورد دیگر

George T. Heineman is an Associate Professor of Computer Science at Worcester Polytechnic Institute (WPI). He holds a BS from Dartmouth College (1989), an MS (1990), and a PhD (1996) from Columbia University. His research focuses on software engineering, component-based systems, and modularity, with notable contributions to type-safe modular software evolution through the CoCo design pattern. Heineman emphasizes professional software engineering practices in teaching, challenging students with industry-relevant projects to foster best practices. His work has been published in leading venues like ECOOP, with a 2021 paper on CoCo gaining attention for its impact on Java language design. He received the WPI Trustees' Award for Outstanding Teaching in 2022, reflecting his dedication to education. His research spans algorithm design, system architecture, and cybersecurity, with publications ranging from foundational theory to practical applications in automated assessment and network security. Education: BS in Computer Science, Dartmouth College, 1989 MS in Computer Science, Columbia University, 1990 PhD in Computer Science, Columbia University, 1996 Research interests include software evolution, design patterns, and modular software systems. His recent work addresses challenges in maintaining stable APIs and enabling cohesive extensions in object-oriented systems. Collaborations with institutions like the University of Copenhagen and TU Dortmund highlight his international academic engagement. Beyond research, Heineman contributes to curriculum development, including WPI's new graduate programs in computing and workforce development initiatives.

Muhammad M. Sherifمشاهده پروفایل

استادیار

• Smart Materials
• Structural Systems
• Machine Learning Applications
• +۴ مورد دیگر

Dr. Muhammad M. Sherif is an Assistant Professor in the Department of Civil, Construction, and Environmental Engineering at the University of Alabama at Birmingham (UAB), part of the School of Engineering. He joined UAB in Fall 2019 after completing his Ph.D. at the University of Virginia and M.S. at Carnegie Mellon University, both in structural engineering. His research focuses on smart materials, structural systems, and machine learning applications in civil infrastructure. He is particularly interested in additive manufacturing for construction and the development of innovative materials like engineered cementitious composites. Education: B.S., United Arab Emirates University M.S., Carnegie Mellon University Ph.D., University of Virginia Research Interests: Dr. Sherif’s work spans material characterization, machine learning models for structural analysis, and the integration of advanced materials into infrastructure systems. He explores topics like crack detection using UAVs, superelastic shape memory alloys, and multi-objective optimization in welding processes. His Advanced Materials and Smart Infrastructure Systems (AMSIS) lab emphasizes interdisciplinary approaches to solving civil engineering challenges. Publications: His recent work includes studies on UAV-based pavement crack detection, machine learning for concrete strength prediction, and optimization of tube-to-tubesheet joints. These reflect trends toward AI-driven solutions and sustainable material innovations. Advising: He actively mentors students in multidisciplinary research projects, emphasizing self-motivation and innovation. His lab collaborates on topics like composite materials, structural health monitoring, and infrastructure resilience. Labs/Teams: His AMSIS lab at UAB focuses on advancing smart materials and infrastructure systems through cutting-edge research and collaboration.

• Artificial Intelligence
• Geospatial Data Science
• Knowledge Graphs
• +۵ مورد دیگر

Professor Manolis Koubarakis is a faculty member at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on geospatial data science, knowledge graphs, entity resolution, and AI applications in Earth observation. He leads projects like ExtremeEarth and Plato, advancing semantic data cube systems and geospatial question answering engines. His work bridges AI and geospatial technologies, with contributions to frameworks like pyJedAI and Strabo 2 for managing big geospatial data. Research Interests include: Geospatial Question Answering Systems Entity Resolution and Entity Linking Ontology-Based Data Access (OBDA) Knowledge Graph Construction and Applications Earth Observation Data Analytics AI for Geoinformatics Notable Projects: ExtremeEarth: Combines Copernicus satellite data with machine learning for environmental analytics. Plato: Semantic data cube system enabling advanced querying of multidimensional datasets. GeoQA2: A geospatial question answering engine evaluated on large benchmarks. JedAI Family: Tools for scalable entity resolution in structured/semi-structured data. His publications span 20+ years, with recent emphasis on: AI-driven Earth observation systems Geospatial RDF benchmarking 3D geospatial interlinking Large language models for legal and health content delivery

James Wollackمشاهده پروفایل

استاد

• Test Security
• Item Response Theory
• Test Construction
• +۳ مورد دیگر

James Wollack is a Professor in the Department of Educational Psychology at the University of Wisconsin-Madison, specializing in Quantitative Methods. He serves as Director of Testing & Evaluation Services and the UW System Center for Placement Testing. His research focuses on test security, including detection of cheating, item compromise, and secure test administration. He leads the Council on Test Security (COTS) and co-edited major handbooks on test security and quantitative cheating detection methods. Education: PhD in Educational Psychology (UW-Madison, 1996); MS in Educational Psychology (UW-Madison, 1993); BS in Psychology (UC Davis, 1991). Research emphasizes statistical methods for detecting group/individual cheating, test fraud prevention, and policy development. Key areas include preknowledge detection, collusion analysis, and compromised-item identification. His work bridges academia and industry, influencing testing program policies globally. Notable awards include the Vilas Associates Award (2019–2021) and recognition from the National College Testing Association. His publications span methodological advancements in cheating detection and foundational test security principles.

Ding Zhouمشاهده پروفایل

استادیار

• Industrial Design
• STEM Education
• Human-Computer Interaction
• +۳ مورد دیگر

Dr. Ding Zhou is an Assistant Professor at the School of System Design and Intelligent Manufacturing (SDIM) at Southern University of Science and Technology (SUSTech). He holds a PhD in Industrial Design from Queensland University of Technology (QUT), Australia (commenced 2018), and prior academic roles include Associate Professor at Nanjing University of the Arts (2009–2018). His research focuses on cross-disciplinary innovation at the intersection of Industrial Design and STEM Education, emphasizing human-centric technology integration. He has conducted visiting research at the University of Virginia (2012) and Victoria University of Wellington (2014–2015). Education: PhD in Industrial Design, Queensland University of Technology (QUT), Australia (ongoing since 2018) M.A. and B.A. in Industrial Design (exact institutions unspecified) Research Interests: Dr. Zhou’s work bridges design science and education, prioritizing how technology enhances human experiences. Key areas include 3D printing applications in STEM education, exoskeleton robotics, computational design aesthetics, and user-centric design processes. He advocates for pedagogical frameworks that cultivate students’ transdisciplinary problem-solving skills through integrated STEM tasks. Articles Trends (2022–2025): Recent publications highlight advancements in 3D printing for education and manufacturing, human-robot interaction, and smart classroom technologies. Notable themes include scalable computer vision systems for posture detection, topology optimization in additive manufacturing, and BIM-enabled construction processes. Labs & Teams: He leads the Design Science and Educational Innovation Lab (DSEIL), focusing on translating theoretical research into practical educational tools and technologies.

Mehdi Tarkianمشاهده پروفایل

دانشیار

• Design Automation
• Machine Learning
• Optimization
• +۵ مورد دیگر

Mehdi Tarkian is a Senior Associate Professor at Linköping University within the Department of Management and Engineering (IEI) , focusing on the Product Realisation division. His research and teaching emphasize Design Automation, leveraging methods like Knowledge-Based Engineering (KBE), Machine Learning, and Optimization. He co-founded the spin-off company XperDi in 2012, based on his research, and returned to LiU full-time in 2017. Current research projects include AutoPack (ML-driven CAD automation), ADAPT (design automation for production preparation), and DeProtion (construction sector design automation). He teaches courses such as Collaborative Multidisciplinary Design Optimization (TMKT79) and Product Modeling (TMKT57) , both highly rated by students. Publications highlight advancements in optical character recognition (OCR) for engineering drawings, reinforcement learning in unstructured production environments, and automated fixture design. His work bridges academic research with industrial applications, aiming to reduce repetitive tasks and enhance engineering intuition. He is part of the Automation Lab and the Unit of Machine Design and Industrial Production (PRODKOP) , collaborating with industry partners to translate research into practical solutions.

• Financial Economics
• Momentum Investing
• Corporate Bonds
• +۵ مورد دیگر

Valentina Galvani is a Professor and Chair of the Economics Department at the University of Alberta's Faculty of Arts. She holds a Ph.D. in Economics from Purdue University (2005), an MSc in Economics (2003), a Doctoral Degree in Mathematical Finance (2002) from the University of Brescia (Italy), and a Laurea (BS+MS) in Mathematics. Her research focuses on financial markets microstructure, energy economics, and corporate bond markets, with a strong emphasis on momentum investing and data-driven industry collaborations. Dr. Galvani has led MITACS-accelerated research projects with Alberta's banking sector since 2013, applying machine learning and model development to commercial finance challenges. Her early work included foundational contributions to general equilibrium theory in infinite-dimensional asset markets (Lp spaces). She joined the University of Alberta in 2005 and assumed the Chair position in 2022. Her research interests span financial economics, including market-state effects, corporate bond predictability, and energy market dynamics. Recent work addresses geopolitical conflicts' impact on oil markets, U.S. strategic petroleum reserves, and Saudi Arabia's competitive positioning under sanctions. She teaches graduate-level directed research and undergraduate courses in labor economics and personnel economics. Dr. Galvani's MITACS collaborations span 12 consecutive years (2013–2024), reflecting her industry engagement. While no specific awards are listed, her extensive publication record and leadership roles highlight her academic impact. She advises on energy diversification, market liquidity, and policy interventions in financial systems.

Josh Reissمشاهده پروفایل

استاد

• Audio Engineering
• Signal Processing
• Music Production
• +۴ مورد دیگر

Josh Reiss is a Professor of Audio Engineering at Queen Mary University of London (QMUL), part of the School of Electronic Engineering and Computer Science . He holds additional roles including President-Elect and Fellow of the Audio Engineering Society (AES), and Visiting Professor at Birmingham City University. His research focuses on audio signal processing, procedural audio, and intelligent music production. He earned degrees including BSc in Physics, BSc in Mathematics, and a PhD. Research & Awards : Reiss has published over 200 papers, authored books like Intelligent Music Production , and received awards such as the AES Board of Governors Award (2009, 2010) and Best JAES Paper 2016. His work spans sound synthesis, dynamic range compression, and live audio systems. Teaching & Industry : Teaches modules like Artificial Intelligence and Sound Design. Co-founded startups LandR (AI mixing), Tonz, and Nemisindo. Leads the Centre for Digital Music at QMUL, advancing research in audio technology. Labs & Teams : Active in the Centre for Digital Music, collaborating on projects like the Open Multitrack Testbed and semantic audio evaluation tools.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Ahmed AbuRa'ed is a Researcher at the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF), Barcelona. He is affiliated with the TALN research group and the Large-Scale Text Understanding Systems Lab. His work focuses on advancing knowledge in scientific text summarization, information extraction, and machine learning. Education: PhD in Computer Science (2020), UPF, Barcelona, Spain M.Sc. in Computer Science (2015), University of Trento, Italy B.Sc. in Computer Information Systems (2007), An-Najah University, Nablus, Palestine Research Interests: Natural Language Processing (NLP), Machine Learning/Deep Learning, Semantic Web, Information Extraction, Data Mining, and Scientific Document Summarization. His projects include developing systems for automatic generation of state-of-the-art reports, scientific text summarization, and cross-document relation discovery. Publications Focus: His 15 most recent articles (2016–2021) emphasize advancements in scientific literature analysis, including citation detection, text simplification, and cross-document summarization. Notable works involve systems like LaSTUS/TALN for scientific text processing and OlloBot for Arabic health dialogue agents. Labs & Teams: Active member of the TALN research group and the Large-Scale Text Understanding Systems Lab at UPF's DTIC department. Open to collaborations in NLP, Machine Learning, and related fields via email or Skype.

• Data fusion
• Machine learning
• Statistical signal processing
• +۶ مورد دیگر

Pierluigi Salvo Rossi is a Full Professor and Deputy Director at the Department of Electronic Systems, Norwegian University of Science and Technology (NTNU), Norway. He leads the Ph.D. Program in Electronics and Telecommunication and serves as Deputy Manager of the Centre for Green Shift in the Built Environment. His roles include leadership in SPIN (Signal Processing for Industry N.0), a research group focusing on industrial digitalization through statistical signal processing and machine learning. Education: Ph.D. in Computer Engineering, University of Naples “Federico II”, Italy (2005) Dr.Eng. (cum laude) in Telecommunications Engineering, University of Naples “Federico II”, Italy (2002) Research Interests: His work centers on data fusion, machine learning, sensor networks, and wireless communication systems. He applies these to industrial challenges such as digital twins, IoT, and sensor validation for safety-critical systems. Recent projects include leadership in initiatives like SIGNIFY (sensor validation) and ML4ITS (machine learning for irregular time series). Awards & Roles: Recipient of the Exemplary Senior Editor Award (IEEE Communications Letters, 2018) Editorial roles include Topical Editor for IEEE Sensors Journal and Area Editor for IEEE Open Journal of the Communications Society Coordinator of major projects funded by RCN, ESA, and ERC Grants & Teams: Leads or co-leads projects such as PREFERENCE (CCS primary reference), DARIO (ESA/PRODEX), and PERSEUS (ERC MSCA-COFUND). The SPIN group collaborates across construction, energy, and ocean industries, anchored at NTNU’s Gløshaugen campus.

Brian Fisherمشاهده پروفایل

استاد

• Cognitive Science
• Visual Analytics
• Human-Computer Interaction
• +۲ مورد دیگر

Brian Fisher is a Professor at Simon Fraser University's School of Interactive Arts and Technology, where he leads the Interaction Science Research Group. He holds affiliate positions at the University of British Columbia and serves as Associate Director for the Media And Graphics Interdisciplinary Centre (MAGIC). His research investigates human reasoning in responsive environments through cognitive science approaches, developing visualization systems that support individual and distributed cognition. Fisher's work spans personalized health, aircraft safety analysis, space object classification, and emergency management. His teaching integrates perceptual, cognitive, and social science knowledge into design education. He actively participates in science policy through organizations including NSERC, Defence R&D Canada, EUREKA Eurostars, and IEEE committees. Fisher has been recognized as a Fellow of the Psychonomics Society and chaired major conferences including IEEE VIS 2019. His research is characterized by strong interdisciplinary collaboration and real-world applications in high-stakes decision domains.

Rasmus Waagepetersenمشاهده پروفایل

استاد

• Spatial Statistics
• Quantitative Genetics
• Markov Chain Monte Carlo Methods
• +۳ مورد دیگر

Rasmus Waagepetersen is a Professor in the Department of Mathematical Sciences at Aalborg University, affiliated with The Faculty of Engineering and Science. His research focuses on spatial statistics, quantitative genetics, and statistical methodology for spatial point processes. He leads and participates in interdisciplinary projects such as urbanLab (spatial data analysis for urban planning) and studies on microbiome interactions in agricultural systems. Key research areas include spatial point processes, Markov chain Monte Carlo methods, and statistical inference for complex ecological and biomedical data. His work frequently involves collaborations with environmental and biological scientists, as seen in projects analyzing root microbiota assemblies in legumes and climate data for building simulations. Waagepetersen has contributed to methodological advancements in spatial statistics, including goodness-of-fit tests, likelihood-based inference for log Gaussian Cox processes, and quasi-likelihood approaches for case-control point pattern data. His research has been supported by grants from institutions like the Villum Foundation. Key Projects: urbanLab, Klimadata til fugtsimuleringer, Nod factor signaling in plant microbiota. Grants: Multiple projects funded by the Villum Foundation and Danish research councils. His recent publications address topics such as space-time point processes, microbiome data analysis, and statistical modeling in education. Waagepetersen maintains an active research group and collaborates internationally on both theoretical and applied statistical problems.

H. David Jeongمشاهده پروفایل

استاد

• Construction Management
• Artificial Intelligence in Civil Engineering
• Data Analytics for Infrastructure
• +۵ مورد دیگر

H. David Jeong is the Associate Department Head and Professor in the Department of Construction Science at Texas A&M University's College of Architecture. His work focuses on advancing construction management through data analytics, artificial intelligence, and innovative technologies. Key areas of research include risk analysis, cost estimation, transportation infrastructure optimization, and collaboration strategies in project delivery. He leads initiatives such as the Serious Games and Simulations for the Built Environment (SeGSiBE) and contributes to the Data Analytics and Artificial Intelligence for Construction Management program. Jeong’s research integrates machine learning, NLP, and GIS technologies to address challenges in construction scheduling, asset management, and project performance evaluation. His projects emphasize practical applications, such as developing predictive models for gravel loss, contingency estimation frameworks, and chatbot-driven workflow tools. He has published extensively on topics like highway construction contract times, AI-based project prioritization, and lifecycle data management in transportation assets. Education : While specific academic credentials are not detailed, his roles imply advanced training in construction engineering and management. Labs/Teams : Leads SeGSiBE lab and collaborates on the HCCI (Highway Construction Cost Index) tool development. Grants/Advising : No student advisees listed, but his research projects likely involve graduate students and industry partnerships.