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Mohammad DadashzadehView profile

Professor

• Management Information Systems
• Database Management
• IT Strategy
• +5 more

Mohammad Dadashzadeh is a Professor of Management Information Systems at Oakland University’s School of Business Administration, within the Decision and Information Sciences Department. He has held roles including Director of Applied Technology in Business (ATiB) from 2003 to 2009. His education includes a B.Sc. in Electrical Engineering (MIT), M.Sc. in Computer Science (MIT), MBA, and Ph.D. in Computer & Information Science (University of Massachusetts). Previously, he served at Wichita State University as W. Frank Barton Endowed Chair in MIS, and the University of Detroit. Research Interests : Enterprise Data Integration, MIS Audit, Strategic IT Planning, Database Management, IT Governance, and Data-Driven Decision Making. His work often focuses on practical case studies to bridge theory and application in business systems. Awards & Recognition : Recipient of multiple teaching awards, including the Board of Trustees’ Excellence in Teaching (2000), Co-op Education Adviser of the Year (2003), and MIT Teaching Excellence (1977). Recognized for editorial contributions to journals like Journal of Database Management and leadership roles in academic and professional organizations. Publications & Contributions : Authored 4 books and over 50 articles, with recent works addressing online education challenges, database design, and IT strategy. His 2023 article explores data-driven decision-making in ecotourism, while earlier works covered cybersecurity, lean manufacturing, and green IT. He has also contributed to standards like the Iranian Standard Code for Information Interchange (ISCII). Professional Engagement : Served on editorial boards, conference committees, and advisory panels globally. Co-founder of Sinasoft and active in academic consulting, having trained over 6,000 professionals worldwide through seminars.

• Spatial Observation Data Analysis
• Sensor Integration
• Energy Consumption Analysis
• +3 more

Sebastián Villarroya Fernández is an Assistant Professor at the University of Santiago de Compostela , affiliated with the Department of Electronics and Computing within the Higher Technical School of Engineering . He completed his PhD in 2018 with a thesis titled "Acquisition and declarative analytical processing of spatio-temporal observation data" , supervised by Dr. José Ramón Ríos Viqueira and Dr. José Manuel Cotos Yáñez. His research focuses on spatial observation data analysis, sensor data integration, and energy efficiency in maritime systems. Key projects include the development of the SODA framework for geospatial analytics and the design of a portable data acquisition system for optimizing energy consumption in fishing vessels. He collaborates with researchers in environmental, medical, and building monitoring domains, integrating protocols like HL7 and BACnet for heterogeneous sensor networks. His work addresses challenges in managing large-scale observation data, bridging gaps between entity-based and sampling-based data models. No formal awards are listed, but his contributions reflect innovative solutions in data management and energy efficiency.

• Temporal Information Extraction
• Computational Linguistics
• Natural Language Processing (NLP)
• +3 more

Marc Verhagen is a computational linguist and programmer affiliated with Brandeis University's Computer Science Department. He holds a PhD in Computer Science (2004) and MA degrees in Computational Linguistics (University of Utrecht, 1991) and Social Geography (1985). His roles include Senior Research Scientist (2007-2008) and Postdoctoral Fellow (2004-2006). He co-founded LingoMotors Inc. (1997-2002), leading software development for natural language processing (NLP) tools. Research Focus: Temporal information extraction, TimeML standards, and computational linguistics infrastructure. Key Projects: TARSQI toolkit for temporal processing, LAPPS Grid, ISO-Space spatial annotation, and Medstract biomedical NLP. He has expertise in programming languages (Python, Perl), database systems (Oracle), and tools like Dreamweaver. His work bridges academia and industry, emphasizing NLP tool development and semantic interoperability. Beyond technical roles, he coordinated large-scale events (300–800 attendees) and served as a free-lance DJ and theater participant. Research interests span temporal semantics, event modeling, and spatial NLP, with contributions to TimeML, annotation frameworks, and semantic visualization. Over 30 publications since 1990, including his 2004 PhD thesis Times Between the Lines .

Allegra T. AronView profile

Assistant Professor

• Metabolomics
• Mass Spectrometry
• Microbiology
• +5 more

Dr. Allegra T. Aron is an Assistant Professor in the Department of Chemistry & Biochemistry at the University of Denver's College of Natural Sciences and Mathematics. Her research focuses on metabolomics, mass spectrometry, and environmental chemistry, with an emphasis on discovering novel biomolecules and understanding their roles in biological systems. She leads the Aron Lab, dedicated to advancing analytical techniques for studying complex biological and environmental systems. Dr. Aron holds a Ph.D. in Chemistry from the University of California, Berkeley (2011), and a BS in Chemistry from Brown University (2011). Her work integrates cutting-edge analytical tools with computational methods to explore microbial interactions, metallophore biology, and metabolic pathways in diverse environments, including marine ecosystems, space environments, and human health contexts. Her research interests span molecular networking, environmental metabolomics, and the development of tools for untargeted metabolomics analysis. Recent work includes studies on siderophore discovery, bile acid diversity, and the impact of dietary interventions on gut microbiome composition. She has contributed to advancements in mass spectrometry-based techniques, such as native metabolomics and molecular networking, to identify bioactive compounds and their ecological roles. Dr. Aron’s lab collaborates on projects involving space microbiology, marine biotechnology, and translational metabolomics, with a focus on applying these insights to address challenges in environmental sustainability and human health. Her research has been published in high-impact journals, and she maintains an active laboratory website (https://www.aronlab-denver.com/) for further details.

• Scientific Visualization
• Immersive Visualization
• High-Performance Scientific Computing
• +7 more

Kenny Gruchalla is an Adjunct Assistant Professor at the University of Colorado, affiliated with the National Renewable Energy Laboratory (NREL). His research focuses on scientific visualization techniques for large-scale energy systems, including immersive visualization, high-performance computing, and GPU-based solutions. He specializes in analyzing power grid dynamics, renewable energy integration, and human-computer interaction in energy scenarios. Affiliations: University of Colorado (Computer Science), NREL (Energy Systems Group) Research Themes: Energy Visualization, Grid Resilience, Renewable Technologies His work emphasizes visual analytics for decision-making in energy systems, such as anomaly detection in grids, AR-based training for solar technicians, and AI-driven grid management (eGridGPT). He collaborates with industry partners like Duke Energy and utilities to address challenges in distributed energy resources and decarbonization. Key contributions include the SAGA platform for grid anomaly detection, blade-resolved wind turbine simulations, and frameworks for contextual compression of large-scale datasets. His team also developed tools like the Surface Phase Explorer for catalyst modeling and the OpenStudio City Database for city-scale energy analysis. Gruchalla has been recognized with the APS Gallery of Fluid Motion Award (2021) for his work on jet impingement visualization. His research bridges computational science, visualization, and energy engineering, with a focus on translating complex data into actionable insights for stakeholders.

• Geographic Information Systems
• 3D Visualization
• Spatial Data Indexing
• +1 more

Dr. Vladan T. Mihajlovic is an Assistant Professor at the Department of Computing and Informatics, Faculty of Electronic Engineering, University of Nis. His research focuses on geospatial technologies including 3D visualization, GIS systems, and spatial data indexing methods for mobile applications. Research includes 3D cloud modeling for hail suppression systems, vector spatial data indexing, and visualization techniques. He has contributed to projects involving forensic statement analysis and automated traffic monitoring systems. Collaborative projects include HASIS-3D system architecture for meteorological applications and spatial database optimization techniques. Technical expertise spans geovisualization, spatial algorithms, and distributed systems.

• Semantic Modeling
• Geographic Information Systems
• Spatio-temporal Databases
• +3 more

Stefano Spaccapietra is a professor at the Swiss Federal Institute of Technology in Lausanne (EPFL) specializing in semantic modeling, geographic information systems, and spatio-temporal databases. A recipient of the 2012 Peter P. Chen Award, his research focuses on foundational aspects of data representation and knowledge engineering. His research explores: Semantic modeling for geospatial systems Multi-representation databases Trajectory data analysis and mobility patterns Ontology design for spatial information Temporal evolution in object-oriented systems Publication analysis reveals strong emphasis on: Fundamental theories of spatial and temporal representation Integration frameworks for heterogeneous systems Evolution of conceptual modeling approaches Spatio-temporal query processing techniques Awards & Honors: Peter P. Chen Award (2012) His work has significantly contributed to database integration methodologies and established foundations for modern geospatial data management systems through both theoretical frameworks and practical implementations.

• Wireless Charging Networks
• Mobile Computing
• Edge Computing
• +6 more

Haipeng Dai is a Professor at Nanjing University, affiliated with the State Key Laboratory for Novel Software Technology and also associated with Tianjin University's School of Computer Science and Technology. His research spans multiple areas of computer science with a strong focus on wireless systems and mobile computing. Dr. Dai's research interests primarily center on wireless charging networks, mobile computing, edge computing, UAV systems, sensor networks, and data management. His work demonstrates a strong theoretical foundation combined with practical applications, particularly in the areas of wireless power transfer and mobile sensing technologies. He has made significant contributions to understanding wireless charger networks, developing novel techniques for acoustic sensing, and optimizing resource allocation in edge computing environments. His research often bridges the gap between theoretical models and real-world implementations, with many papers published in top-tier conferences and journals. Analysis of Dr. Dai's recent publications reveals a strong trend toward interdisciplinary research combining wireless power transfer with mobile computing and sensing applications. His work shows increasing focus on practical implementations of theoretical concepts, particularly in the areas of wireless charging infrastructure, acoustic sensing for health monitoring, and optimization of UAV-based systems. The research demonstrates a clear progression from fundamental wireless charging concepts to more complex integrated systems involving multiple technologies. Dr. Dai has collaborated extensively with researchers including Guihai Chen (129 joint publications), Jiaqi Zheng (47 papers), Chao Dong (36 papers), and Rong Gu (35 papers), indicating strong research group leadership and collaborative networks across institutions. His work has significant implications for the development of next-generation wireless systems, particularly in the areas of energy-efficient mobile computing, contactless health monitoring, and intelligent resource allocation in distributed computing environments. The research portfolio demonstrates both depth in specific technical areas and breadth across multiple related domains within computer science and networking.

Francesco GuerraView profile

Professor

• Scalable Data Management
• Data Mining
• Big Data Analysis
• +5 more

Francesco Guerra is a Full Professor at the Department of Engineering 'Enzo Ferrari' at the University of Modena and Reggio Emilia. He teaches Software Engineering and Big Data Analysis. His research focuses on scalable data management, machine learning explainability, entity resolution, data mining, text analytics, semantic web, and keyword-based search on structured data. Academic Positions: Rector’s delegate for ICT (since Feb 2024) President of Computer Engineering Degree Councils (since Nov 2022) Curriculum Coordinator for Computer Engineering Doctorate (2021-2023) Visiting Professor at University of Rijeka (2019) Education: PhD in Information Engineering (2004) Master Degree in Information Engineering (2000) Classical Diploma (1992) from Liceo Classico 'L.A. Muratori' Research Interests: Develops explainable machine learning techniques for entity resolution and anomaly detection. Specializes in interpretable time series clustering (Time2Feat), BERT-based entity matching analysis, and pushing ML predictions into DBMS frameworks. Active in semantic keyword search and big data integration projects like KEYSTONE (COST Action 2013-2017) and Re-search Alps (2017-2019). Projects: KEYSTONE COST Action: Semantic keyword search on structured data Re-search Alps: Big data integration for Alpine research labs AutoML4Clust: Automated machine learning for clustering FAIRnessEval: Framework for algorithmic fairness evaluation Awards: No awards explicitly listed in the provided texts. However, his work has been funded through EU and national projects.

• Occupational Health
• Environmental Health
• Cancer Epidemiology
• +3 more

France Labrèche is a Clinical Professor at the Department of Environmental and Occupational Health, School of Public Health, University of Montreal. She is also a researcher at the Institut de recherche Robert-Sauvé en santé et en sécurité du travail (IRSST). Her primary research focuses on occupational and environmental exposures linked to cancer, particularly breast cancer in postmenopausal women and carcinogenic risks in workers such as aluminum industry employees and asbestos-exposed workers. She utilizes exposure databases and job-exposure matrices to identify high-risk populations. She explores emerging areas like climate change impacts on worker health and occupational hazards in green technologies. Key projects include assessing carcinogen exposure among young workers, comparative analysis of exposure databases (IMIS vs. LIMS), and prevention initiatives targeting apprentices in semi-specialized trades. She has secured grants from the Canadian Institutes of Health Research (CIHR) and the IRSST. Her supervision includes three graduate students: Sabrina Gravel (Ph.D., 2020), Kahlila Paul-Cole (M.Sc., 2024), and Maymouna Myriam Ka (M.Sc., 2023). Her work emphasizes practical applications, such as improving job-exposure matrices for sex-specific assessments and evaluating workplace mental health supports during the pandemic. She collaborates with interdisciplinary teams on topics like e-waste recycling risks, antineoplastic drug exposure in healthcare workers, and the epidemiology of shift work’s impact on cancer risks. Her research bridges occupational health, environmental science, and public policy, aiming to reduce preventable occupational diseases.

Elina TakolaView profile

Researcher

• Ecology
• Conservation Biology
• Meta-Analysis
• +4 more

Dr. Elina Takola is a Greek ecologist and meta-analyst leading the BIOECOS group at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany. Her research focuses on cross-scale data syntheses to explore organism-environment relationships, with a strong commitment to open science principles. She holds a PhD from Friedrich-Schiller University of Jena (2022) and has conducted research at institutions including the University of Glasgow and Aristotle University of Thessaloniki. Her work bridges theoretical ecology and applied conservation, emphasizing evidence-based approaches to biodiversity and sustainable land use. Affiliations: Helmholtz-Zentrum für Umweltforschung (UFZ), Department of Computational Landscape Ecology Education: PhD in Ecology (FSU Jena, 2022), MSc/BS in Forestry & Natural Environment (Aristotle U, 2016/2010) Her research interests include meta-analyses, ecological niche theory, landscape heterogeneity, and conservation strategies. She co-leads the Open CLE Forum, fostering interdisciplinary dialogue at UFZ. Notable awards include a 2021 GfÖ poster prize and commendations for academic excellence in Greece. Recent projects include global meta-analyses of sustainable agriculture impacts and software development (e.g., decimatoR). Teaching roles span universities in Germany and Greece, with courses on ecological concepts and evidence synthesis methods.

Pia EbelingView profile

Researcher

• Hydrology
• Environmental Science
• Catchment Hydrology
• +6 more

Dr. Pia Ebeling is a Researcher at the Department of Hydrogeology, Helmholtz Centre for Environmental Research - UFZ in Leipzig, Germany. She holds a Master of Science in Hydrology (2018) and a Bachelor of Science in Hydrology (2014), both from Technical University Dresden. Her research focuses on water quality dynamics, catchment-scale nutrient interactions, data-driven hydrological analysis, and groundwater dynamics under climate variability. She has been involved in international research stays, including at INRAE in France (2018-2022), and has contributed to projects such as CAMELS-DE and QUADICA, which compile extensive hydro-meteorological datasets for German catchments. Dr. Ebeling has received the Karl-Franz-Busch Medal (2018) for her Master’s thesis on seawater intrusion remediation. She collaborates with interdisciplinary teams in the Helmholtz program 'Changing Earth - Sustaining our Future', particularly in topics like coastal zones, landscapes of the future, and sustainable bioeconomy. Her work emphasizes developing Python-based modeling tools, integrating machine learning for environmental prediction, and addressing global challenges in water security and ecosystem health. Education: Bachelor of Science in Hydrology, Technical University Dresden (2014) Master of Science in Hydrology, Technical University Dresden (2018) Research Interests: Quantifying groundwater dynamics and drought patterns Examining nutrient depletion and stoichiometric imbalances in streams Advancing large-sample hydrological analysis through data synthesis Modeling subsurface processes under climate change scenarios Developing open-source tools for hydro-ecological research Advising & Grants: Completed PhD under the supervision of Prof. Jan Fleckenstein at UFZ (2022) Contributed to interdisciplinary research initiatives like Helmholtz TRACER PhD school Involved in international collaborations, including with the University of Texas at Austin’s hydrology team Labs/Teams: Member of the Hydrogeology Department team at UFZ Contributor to the 'Healthy Planet' and 'Landscapes of the Future' research topics Developed the HydroEcoLSTM package for hydro-ecological modeling

• Semantic Web
• Knowledge Graphs
• Linked Data
• +3 more

Mohamed Ahmed Sherif is an academic affiliated with Paderborn University's Department of Computer Science and the University of Leipzig's Institute of Computer Science. His primary research focuses on semantic web technologies, knowledge graph integration, and machine learning applications in data integration. Key affiliations: Paderborn University, University of Leipzig Specialization: Link discovery, knowledge graph construction, semantic web standards His work emphasizes scalable methods for linking heterogeneous data sources, explainable AI techniques for knowledge integration, and geospatial semantic technologies. Recent contributions include the ANTS system for entity summarization in knowledge graphs and the NELLIE framework for continuous linked data integration. Notable projects include LIMES - a widely-used link discovery framework - and contributions to the HOBBIT benchmarking platform. His research has been applied in disaster management (I-AID system), Quran semantification, and global health data integration.

Almudena García-GarcíaView profile

Researcher

• Remote Sensing
• Climate Science
• Environmental Monitoring
• +6 more

Almudena García-García is a Researcher in the Department of Remote Sensing at the Helmholtz Centre for Environmental Research - UFZ in Leipzig, Germany. Her work focuses on land-atmosphere interactions, climate extremes, satellite remote sensing, and process-based modeling. She holds a Ph.D. in Environmental Sciences from Memorial University of Newfoundland (2020), a Master's in Earth Sciences from St. Francis Xavier University (2016), and a BSc in Physics from the University of Murcia (2014). She has been recognized with the Moire A. Wadleigh Award (2020) and the Governor General Graduate Medal (2016), and was nominated for the Lindau Nobel Laureate Meeting (2014). Her research integrates remote sensing data with climate models to study energy and water fluxes, soil moisture dynamics, and heat extremes. Key projects include the 4DHydro initiative (2023–2025) for hyper-resolution Earth observations and the iDiv Flexpool project on biodiversity mapping. She leads studies on soil heat extremes, continental heat storage, and transpiration modeling using satellite data and neural networks. Publications highlight contributions to global soil moisture products, continental heat dynamics, and climate extremes. She collaborates on the GCOS Earth Heat Inventory and has co-authored over 30 peer-reviewed articles. Her work bridges environmental informatics and Earth system science, addressing climate change impacts and sustainable monitoring solutions.

• Augmented reality
• Computer graphics
• Extended reality
• +4 more

Davide Calandra is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN) within the College of Computer, Film, and Mechatronics Engineering at Politecnico di Torino. He holds expertise in Information Processing Systems (IINF-05/A) and focuses on computer graphics, human-computer interaction, and virtual reality applications. His research spans augmented reality, extended reality, mixed reality, and virtual reality with applications in healthcare, education, emergency response, and cultural heritage preservation. Calandra's work addresses fundamental challenges in human-robot interaction, social VR experiences, and XR-based training systems. His research contributes to multiple UN Sustainable Development Goals including Good Health and Well-being, Quality Education, Industry Innovation and Infrastructure, Sustainable Cities and Communities, and Life on Land. Analysis of his recent publications reveals a consistent focus on practical applications of VR/AR technologies, particularly in social interaction enhancement, emergency response training, cultural heritage preservation, and rehabilitation. His work demonstrates a strong interdisciplinary approach, bridging computer science with practical applications in diverse fields. Calandra actively contributes to the GRAINS - GRAphics and INtelligent Systems research group and the VR@POLITO laboratory, where he develops cutting-edge XR technologies and applications. As an educator, he teaches across multiple programs including PhD courses in Information Visualization and Visual Analytics, Master's courses in Generative Artificial Intelligence for Graphics and Multimedia, and various undergraduate courses in databases and information systems. His teaching spans multiple engineering disciplines including Computer Engineering, Aerospace Engineering, and Engineering and Management. His notable project includes the Augmented Sand Table for Forest Firefighting, which demonstrates his commitment to applying XR technologies to real-world emergency response scenarios.