جست‌وجوی استاد و پژوهشگر

Frederico Fonsecaمشاهده پروفایل

دانشیار

• Ontology
• Geographic Information Systems
• Information Systems
• +۱۲ مورد دیگر

Frederico Fonseca is an Associate Professor in the College of Information Sciences and Technology at Pennsylvania State University. His research focuses on the conceptualization and implementation of information in computer systems, with a particular emphasis on ontologies related to the environment and geographic information systems (GIS). He is affiliated with interdisciplinary research themes in Health and the Environment and contributes to foundational work in information science. His research interests span ontology, geographic information systems, knowledge sharing, big data, information integration, hermeneutics, and the philosophical foundations of information. He explores how meaning is constructed, shared, and represented in digital environments, especially through computational ontologies and cyber-human systems. His work bridges technical, social, and philosophical dimensions of information science. The recent publications highlight a strong trend in the intersection of information theory, environmental modeling, and human cognition. His articles explore semantic structures in data, the epistemology of big data, and the socio-technical aspects of digital systems. Key domains include GIS, ontology engineering, digital divides, and ethical design, reflecting a deeply interdisciplinary approach grounded in both technical rigor and philosophical inquiry. Scientific Awards: No scientific awards mentioned in the provided text. Frederico Fonseca has been involved in significant research projects related to spatial data infrastructures, knowledge sharing, and semantic systems. While specific grants are not listed, his collaborative publications suggest involvement in federally or institutionally funded initiatives, particularly in geoinformatics and data science. He has advised or collaborated with multiple researchers and students, though no formal advisees are named in the text. He is associated with research groups focusing on cyber-human systems, geographic information science, and semantic technologies. His work contributes to broader teams exploring open data, information ethics, and environmental informatics, particularly in the context of global challenges like forest monitoring and digital equity.

Shashi Shekharمشاهده پروفایل

استاد

• Spatial Computing
• Spatial Data Science
• Geographic Information Systems (GIS)
• +۵ مورد دیگر

Shashi Shekhar is a Distinguished McKnight University Professor and Distinguished University Teaching Professor at the University of Minnesota. He holds joint appointments in the Department of Computer Science and Engineering (College of Science and Engineering) and the Center for Transportation Studies. His pioneering research in spatial computing and GIS has revolutionized navigation technologies and evacuation planning. Research Focus: His work spans spatial data science, spatial databases, and spatial data mining. Current projects include scalable algorithms for spatial big data, eco-routing to reduce emissions, and AI for climate-smart agriculture. His innovations in pattern families (colocation, hotspots) have defined the spatial data mining field. Honors & Recognition: IEEE Fellow and AAAS Fellow IEEE-CS Technical Achievement Award UCGIS Education Award Distinguished Teaching Professorship Named 'key difference-maker in GIS' by leading textbooks Academic Leadership: Advised 100+ students, including 32 PhD graduates. Many advisees received Presidential Early Career Awards and NSF CAREER grants. Directs the Spatial Computing Research Group and the $20M AI-LEAF Institute for climate-smart agriculture. Major Grants: Secured $20M for AI-LEAF Institute, $2.5M for urban quality-of-life projects, and NSF funding for polar-region data science. Recent work analyzes COVID-19 impacts on transportation.

Kenny Josephمشاهده پروفایل

دانشیار

• Computational Social Science
• Social Inequality
• Machine Learning
• +۹ مورد دیگر

Kenny Joseph is an Associate Professor in the CSE Department at the University at Buffalo, leading the Computation and Equity Lab (cubelab) . His work bridges computational methods with social inequality research, focusing on predictive modeling for social good and analyzing systemic disparities through digital traces. Current affiliation: University at Buffalo Previous positions: Postdoc at LazerLab (Northeastern), Fellow at Harvard's Institute for Quantitative Social Science Research Interests: Combining machine learning with social theory to address structural inequalities in areas like foster care systems, neighborhood change, and gender disparities in academia. Key methodologies include agent-based modeling, network analysis, and large-scale data mining. Publication Trends: Recent work focuses on Social media dynamics and misinformation Equity-focused predictive modeling Political communication analysis Identity expression in digital spaces Urban planning applications Additional Contributions: Developer of computational tools for location extraction (GALLOC) and self-presentation analysis, with applications in disaster response and social inequality research.

• Big Data Analytics
• Sentiment Analysis
• Data Management
• +۳ مورد دیگر

Bela Stantic is a Professor at Griffith University's School of Information and Communication Technology, where he founded and directs the Big Data and Smart Analytics Lab . With a PhD from Griffith University, his academic appointments include Head of School (2015-2019) and Deputy Head of School (2013-2015). He remains an active member of the Institute for Integrated and Intelligent Systems since 2005. Research Focus: Professor Stantic specializes in Big Data Analytics, particularly in social media sentiment analysis and complex data management. His interdisciplinary work spans tourism analytics, environmental monitoring, cryptocurrency forecasting, and AI ethics. Key applications include disaster response systems, aquaculture optimization, and sustainable infrastructure. Publication Trends: Recent articles (2023-2025) demonstrate strong emphasis on AI-driven solutions: 40% focus on time-series forecasting and cryptocurrency prediction, 30% on computer vision/LiDAR applications, and 30% on social media analytics for tourism and public policy. Machine learning integration across environmental and financial domains is a consistent theme. Grants & Projects: Secured 24 funded projects totaling ~$1.8M AUD, including: Automated seagrass monitoring ($403K, 2023-2025) NSW flood impact analysis via social media (2022) Offshore aquaculture welfare systems ($466K, 2022-2026) COVID-19 pandemic behavior tracking (2020) Student Advising: Supervised 15+ doctoral students to completion in areas like 3D data extraction, social media mobility tracking, and stream-processing engines. Currently mentoring PhD candidates on multimodal sentiment analysis and real-time recommendation systems.

Dan Schonfeldمشاهده پروفایل

استاد

• Signal Processing
• Image Processing
• Video Processing
• +۷ مورد دیگر

Dan Schonfeld is a Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Chicago . His research spans signal, image, and video processing, with interdisciplinary applications in genomic signal processing and multimedia systems. Education: Ph.D. and M.Sc. in Electrical and Computer Engineering from The Johns Hopkins University (1990, 1988), B.Sc. in Electrical Engineering and Computer Science from UC Berkeley (1986). Research Interests: Schonfeld's work focuses on video communications, retrieval, and networks, integrating computer vision, pattern recognition, and stochastic optimization. His contributions include mathematical morphology for image processing and statistical methods for real-time scene change detection. Article Trends: His recent publications emphasize particle filtering for video tracking, hidden Markov models for activity recognition, and multi-camera systems for pose estimation. Applications in genomic signal processing and crowded scene tracking highlight his interdisciplinary impact. Scientific Leadership: He has been a Senior Member of IEEE since 2005 and received multiple Best Student Paper Awards at IEEE ICIP (2006, 2007) and SPIE VCIP (2006). Editorial Contributions: Schonfeld has served as Guest Editor for IEEE journals on video and genomic signal processing and as Associate Editor for key IEEE Transactions since the 1990s.

Jonathan Yearsleyمشاهده پروفایل

دانشیار

• Ecological Modelling
• Marine Ecology
• Conservation Biology
• +۳ مورد دیگر

Assoc Professor Jonathan Yearsley is an Associate Professor at the School of Biology and Environmental Science, University College Dublin , leading the Ecological Modelling group. His work combines theoretical ecology with empirical data to study deep-sea ecosystems, focusing on larval dispersal mechanisms , hydrographic barriers , and conservation strategies for deep-sea mining. Education : BSc (University of Birmingham), MSc (University of Cambridge), PhD (University of Sussex) in Cosmology. His research applies biophysical models and oceanographic data (e.g., Argo probes) to map connectivity in fragmented hydrothermal vent habitats. Key projects include the International Climate Initiative (IKI) and collaborations with Duke University Marine Lab and the Global Ocean Biodiversity Initiative (GOBI). Publications highlight median larval dispersal distances (75–300 km) and persistent barriers at 6°N, 15°N, 36°N, and 37°N on the northern Mid-Atlantic Ridge. Students and researchers under his supervision include PhD candidates analyzing spatial biases in species distribution datasets and MSc students in Evolutionary Biology and Environmental Resource Management. Current projects focus on deep-sea ecosystem resilience and conservation policy for polymetallic sulfide extraction.

Jose Ferrerمشاهده پروفایل

پژوهشگر ارشد

• Spatial Ecology
• Biodiversity Informatics
• Conservation Biology
• +۵ مورد دیگر

Dr. Jose Ferrer is a Senior Research Fellow at the School of Biological, Earth and Environmental Sciences at the University of New South Wales (UNSW). With extensive field experience in Germany, Venezuela, and South Africa , his work focuses on spatial ecology, biodiversity informatics, and ecosystem conservation , particularly through developing analytical tools for conservation decision-making. Affiliation: UNSW, IUCN Global Ecosystem Typology project Research Themes: Species distribution modeling, ecosystem risk assessment, environmental data integration His research spans diverse ecosystems, with a strong emphasis on animal/plant distribution patterns and human impact mitigation . Recent publications address: Ecosystem resilience under anthropogenic stressors Red List of Ecosystems applications in Africa Mining expansion impacts in Venezuela Ecological trap detection for Andean bears Invasive species effects in arid environments Conservation strategies for critically endangered species He contributes to open science initiatives through: Code sharing via UNSW codeRs group Data repository contributions Drop-in research assistance sessions His teaching emphasizes reproducible research methods and data management skills , supporting both academic and conservation communities through technical training.

Timothy Cribbinمشاهده پروفایل

مدرس ارشد

• Information visualisation
• Information retrieval
• Text mining
• +۷ مورد دیگر

Dr. Timothy Cribbin is a Senior Lecturer in the Department of Computer Science within the College of Engineering, Design and Physical Sciences at Brunel University London. He has been with the university since 2001, initially joining as a lecturer and advancing to his current position. His academic home is firmly rooted in the intersection of information science, human-computer interaction, and data analytics. His educational background includes: PGCert Learning and Teaching in Higher Education, Brunel University (2007) PhD Information Science, Brunel University (2005) for research exploring spatial-semantic interfaces for exploratory document search MSc Industrial Psychology, University of Hull (1996), where he was awarded the Tom Hoyes Memorial Prize BSc (Hons) Psychology, University of Portsmouth (1994) Dr. Cribbin's research focuses on information visualization, interactive search interfaces, and text analytics, with particular expertise in processing and modeling large text collections to uncover meaningful insights. His work spans the design and evaluation of algorithms, interaction models, and end-user tools that support search, navigation, exploration, and sense-making within connected information spaces like scholarly publications and social media platforms. Early in his career, he pioneered work on interactive visualization using distance-similarity and spatial-semantic metaphors, making key contributions through the application of geodesic distance and second-order similarity transformations. More recently, his research has centered on citation-enhanced information retrieval and social media analytics, including the development of the Chorus Twitter analytics project. His scholarly output reveals a consistent trajectory from foundational work in information visualization to increasingly applied research in social media analytics and text mining. Throughout his career, Dr. Cribbin has maintained a strong focus on human-centered approaches to information processing, with particular attention to how users interact with and make sense of complex information spaces. His recent work demonstrates growing interest in psychological aspects of information processing, author classification, and the analysis of linguistic patterns in online radicalization. Dr. Cribbin has received notable recognition including: Tom Hoyes Memorial Prize for his MSc in Industrial Psychology Fellowship of the Higher Education Academy (FHEA) He has secured research funding for projects including "Predicting online radicalisation" and "Facilitating social media research in social sciences." Dr. Cribbin serves as a Deputy Senior Tutor (Academic Misconduct) and provides supervisory duties for final year undergraduate and Masters dissertation projects. He regularly acts as a reviewer for conferences and journals in information science, social media analytics, and information visualization. Dr. Cribbin is a key contributor to the User Centred Design research group and is the founder and lead programmer of the Chorus Twitter analytics project. His work bridges theoretical research with practical applications, particularly in the areas of social media analytics and text mining.

Stasha Lauriaمشاهده پروفایل

مدرس

• Intelligent Robotics
• Neural Networks
• Pattern Recognition
• +۶ مورد دیگر

Dr. Stasha Lauria is a Lecturer in the Department of Computer Science within the College of Engineering, Design and Physical Sciences at Brunel University London. With over 15 years of experience in intelligent robotics, she specializes in human-machine interactions, neural networks, and pattern recognition, leading the Brunel Robotics Laboratory for cognitive mobile robot experiments. Education: Laurea, University of Studies “Federico II” of Napoli, Italy Ph.D. in Cybernetics, University of Reading, UK Research Focus: Her work centers on modeling mobile robots through natural language interactions, converting human speech into robot actions, and AI-driven signal processing. Current projects investigate social media's impact on human-robot dialogue management and robotics as educational tools, with strong emphasis on neural networks and big data applications in vision systems. Publication Trends: Recent publications (2022-2009) reveal consistent innovation in computer vision (object detection, segmentation) and human-robot interaction, increasingly integrating deep learning for manufacturing and vision tasks. Educational robotics remains a parallel thread, with quantitative evaluations of programming pedagogy. Research Grants: A human-centred internet of things platform for the sustainable mine of the future (European Commission, May 2020 - April 2024) Intelligent data-driven pipeline for certified metal parts manufacturing (European Commission, October 2018 - March 2023) Big Data Learning-based QoS Analysis for Cloud-services (Royal Society, March 2016 - February 2018) Laboratory & Collaboration: Founder of the Brunel Robotics Laboratory, she collaborates extensively with Dr. Theodora Koulouri, Prof. Xiaohui Liu, and Dr. Stephen Swift on human-robot interaction, as evidenced by co-author networks spanning neural networks, dialogue systems, and multi-agent architectures.

• Digital Humanities
• Spatial Humanities
• Artificial Intelligence
• +۷ مورد دیگر

Professor Patricia Murrieta-Flores is a faculty member at Lancaster University's School of Global Affairs and Co-Director of the Digital Humanities Centre. Her research focuses on the intersection of Digital Humanities, Artificial Intelligence, and Spatial Humanities to study Latin American colonial history, particularly 16th–18th century New Spain. She employs GIS, NLP, Computer Vision, and Machine Learning to analyze epidemics, economic systems, and indigenous spatial epistemologies. Research Grants : TAP/ESRC: Digging into Early Colonial Mexico AHRC/NEH: Unlocking the Colonial Archive ESRC: The Fleets of New Spain (2024–) Scientific Awards : Fellow, Royal Historical Society Fellow, Centre for Apocalyptic and Postapocalyptic Studies (Heidelberg) PhD Supervision : Katherine Bellamy Edward Moore Collaborative Networks : Cross-institutional projects with University of Lisbon, LLILAS Benson, and others Interdisciplinary teams combining Computer Science, History, and Archaeology

• Environmental Economics
• Agri-food and Environmental Economics
• Social Economy
• +۵ مورد دیگر

MARIA LUZ LOUREIRO GARCIA is a Professor in the Department of Fundamentals of Economic Analysis at the Faculty of Economic and Business Sciences, University of Santiago de Compostela. She is affiliated with the Interuniversity Research Center in Economics and Business for Society (ECOBAS) and leads the ECO-IURIS Legal-economic analysis group, while also collaborating with the ECOAGRASOC group focused on Agri-Food and Environmental Economics, Rural Development, and Social Economy. Her research spans Environmental Economics , Climate Change , Energy Economics , and Tourism Economics , with a focus on public sentiment analysis , behavioral economics , and ecosystem services valuation . Recent work applies choice experiments and big data to assess preferences for nature-based solutions , clean energy adoption , and tourism demand dynamics . Her publications (2011–2025) cover broad disciplines including Climate Change Mitigation , Energy Transition , Wildfire Economics , and Behavioral Analysis , with specific subfields such as sentiment analysis in Spain , gender roles in rural energy access , blue carbon valuation , wine consumer emotions , and policy evaluation for invasive species .

Eszter Rita Katonaمشاهده پروفایل

استادیار

• Computational Social Science
• Social Research Methodology
• Natural Language Processing
• +۷ مورد دیگر

Eszter Rita Katona is an Assistant Professor at Eötvös Loránd University's Faculty of Social Sciences, Department of Social Research Methodology. She serves as a lecturer at multiple research centers including the Research Center for Computational Social Science (RC2S2), Survey Methods Room Budapest, and Széchenyi István College for Advanced Studies. Education: PhD in Interdisciplinary Social Research (Doctoral School of Sociology, 2018-2023) Computer Science specialization (Faculty of Informatics, 2016-2017) Survey Statistics MSc (Faculty of Social Sciences, 2015-2018) Social Sciences BA (Faculty of Social Sciences, 2011-2015) German Studies BA (Faculty of Humanities, 2012-2015) Angelusz Róbert College for Advanced Studies (2014-2018) Research Focus: As a computational social scientist, her work spans three major domains: NLP and data visualization applications in social research Discursive framing of depression in online communities Corruption risk assessment in public procurement Teaching Expertise: In her academic role, she teaches: BA courses: Data Collection Methods, Data Visualization, Introduction to Sociological Research, Quantitative Data Analysis MSc courses: Advanced Data Visualization, Python Programming, Communication and Data Visualization, Text Analytics Scientific Contributions: Her recent publications and conference presentations focus on: Machine learning for depression discourse analysis Digital lens approach to Holocaust testimonies Corruption risk modeling in public procurement Interdisciplinary NLP applications Computational social science methodology Contact: katona.eszter@tatk.elte.hu

• Applied Economics
• Environmental Economics
• Agricultural Policy
• +۳ مورد دیگر

Ángel Perni Llorente is a Professor at the University of Cádiz, affiliated with the Department of Economics, Quantitative Methods and Economic History. His research focuses on applied economics, particularly in environmental economics, agricultural policy, and socioeconomic analysis of rural and coastal ecosystems. He has collaborated with José Miguel Martínez Paz and others on cost-benefit analyses for environmental restoration projects, including the Mar Menor coastal lagoon and Portmán Bay. PhD in Economics from the University of Murcia (2014) Specializes in EU Common Agricultural Policy (CAP) reforms and their socioeconomic impacts Expertise in contingent valuation and choice experiments for environmental goods Active in modeling agricultural risk and policy scenarios His recent publications analyze climate change impacts on irrigation agriculture, CAP post-2020 reforms, and consumer preferences for circular bioeconomy attributes. He also contributes educational materials like the Guía de Estudio de Macroeconomía (2022). While no specific scientific awards are documented in the provided texts, his work on environmental valuation and policy implementation remains influential. Collaborations span institutions such as European Commission agencies and regional governments, with a focus on transdisciplinary approaches to environmental and agricultural challenges. His research frequently addresses policy effectiveness, resource allocation, and public perception in water management and agricultural sustainability.

Neil McIntyreمشاهده پروفایل

استاد

• Hydrology
• Water Resources
• Environmental Engineering
• +۳ مورد دیگر

Professor Neil McIntyre is a civil engineer with expertise in hydrology and water resources at the University of Queensland (UQ). He divides his time between the Centre for Water in the Minerals Industry and the School of Civil Engineering. His research focuses include water resource systems modeling, mining impacts on water resources, remote sensing in hydrology, and stochastic hydrology. McIntyre earned a BEng in Civil Engineering from Edinburgh University (1990), an MSc in Environmental Engineering (1998), and a PhD in water quality modeling from Imperial College. He served as a Lecturer and Reader at Imperial (2001–2013), teaching water quality, hydrometry, hydraulics, and water resources engineering, and directed the Hydrology MSc program for five years. McIntyre's work spans Australia and the UK, with international projects in Thailand, Uganda, Botswana, Peru, Chile, Colombia, Mongolia, and China. He has contributed to the British Hydrological Society, ICE’s Water Expert Panel, and the NERC Peer Review College. His awards include the Institution of Civil Engineers’ Baker Medal and RA Carr Award for water resources research, alongside an ARC Future Fellowship (2014–2019). His recent publications emphasize desalination sustainability, mine closure risks, remote sensing applications, and erosion modeling. The 15 most recent articles reflect interdisciplinary themes in hydrology, environmental engineering, and climate-water-food nexus challenges. McIntyre actively supervises PhD students, with current projects on desalination impacts, chloride deposition, and climate-resilient land management. He has secured substantial funding from CRC TIME, ARC Linkage Projects, and industry partners like Stanmore Resources and CleanCo. Scientific Awards Baker Medal RA Carr Award ARC Future Fellowship (2014–2019)

Kevin A. Angstadtمشاهده پروفایل

استادیار

• Computer Architecture
• Programming Languages
• Software Engineering
• +۵ مورد دیگر

Kevin A. Angstadt is an Assistant Professor in the Department of Mathematics, Computer Science, and Statistics at St. Lawrence University. His research bridges computer architecture, programming languages, and software engineering, focusing on programming support for emerging hardware technologies like FPGAs and custom accelerators. He teaches systems-oriented courses such as Computer Organization and Programming Languages. Ph.D., Computer Science and Engineering, University of Michigan (2020) MCS, Computer Science, University of Virginia (2016) B.S., Computer Science, Mathematics, and German Studies, St. Lawrence University (2014) His research explores automata processing for hardware acceleration, deterministic/non-deterministic finite automata for accelerators, and resiliency in autonomous vehicles. He develops tools like MNRL Network Representation Language, AutomataSynth, and RAPID Compiler for pattern-matching applications. Recent publications focus on hardware fault tolerance, autonomous system repair, and automata-based programming. Key conferences include ASPLOS, IEEE MICRO, and ICCPS. Awards include a $1.2M NSF grant (2022), TECHCON 2016 Best in Session, and Mac Krell Fellowship (2014–2017). He co-advises research projects and maintains the CS Grad Job and Interview Guide , a collaborative resource for academic career preparation. His lab works on open-source state machine ecosystems and hardware-software co-design frameworks.