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Steven J. KassView profile

Professor

• Human Factors Psychology
• Situation Awareness
• Distracted Driving
• +5 more

Steven J. Kass serves as a Distinguished University Professor in the Department of Psychology within the Usha Kundu, MD College of Health at the University of West Florida. His research focuses on human factors psychology, particularly examining attentional processes through studies on situation awareness, distracted driving, boredom proneness, and cognitive failures. Kass directs the Human Factors Laboratory where he investigates performance optimization in dynamic environments including transportation, healthcare, and military contexts. His primary research interests include: Situation awareness degradation during distracted driving (notably cell phone use) Vibrotactile displays for spatial awareness in aviation and healthcare Virtual reality applications for training and performance enhancement Boredom proneness and vigilance in operational settings Cognitive failure mechanisms in high-stakes environments Recent work emphasizes healthcare applications, developing the MEDUSA training system for nurses and studying VR's impact on mood and cognition. Notable contributions: 2013 testimony before Florida House Transportation Subcommittee influencing texting-while-driving legislation 2015 keynote address at Southeastern Psychological Association annual meeting Continuous research program since 1998 with consistent funding and publications His laboratory actively trains undergraduate researchers, with recent projects involving parachute descent simulators, aggressive driving studies, and mobile SA training applications. Kass advises student researchers across multiple projects and collaborates with US Navy training programs on aviation survival systems. His work bridges theoretical cognitive psychology with practical applications in transportation safety, healthcare performance, and military training systems.

Hyoju AhnView profile

Assistant Professor

• Digital Literacy
• Online Multimodal Reading Strategies
• Qualitative Reading Research
• +7 more

Hyoju Ahn, Ph.D., is an Assistant Professor in the Department of Curriculum and Instruction at Northern Illinois University’s College of Education. Her work bridges digital literacy, reading research, and K–12 instructional practices, with a strong emphasis on multimodal texts and comprehension strategies. Research Interests: Her primary research centers on online multimodal reading strategies, digital literacy, and children's literacy development. She employs qualitative methods, particularly verbal protocol analysis, to understand how readers process complex digital texts. Her work has direct implications for curriculum design, literacy instruction, and assessment in language arts classrooms. The recent publications and presentations reflect a consistent focus on understanding and improving reading comprehension in digital environments. Her work explores how visual and linguistic modes integrate during reading, how prior knowledge affects comprehension, and how assessment practices can be refined to reflect modern literacy demands. These efforts align with broader trends in educational research toward technology-enhanced learning and equitable literacy instruction. Scientific Awards: No awards listed in the provided text. Advising and Grants: While no specific students or grant funding are mentioned, Dr. Ahn is actively contributing to national discourse through publications in major educational handbooks and presentations at premier conferences such as the American Educational Research Association (AERA) and Literacy Research Association (LRA). Her collaborative work with established scholars like Peter Afflerbach indicates strong engagement in the academic community. Labs and Teams: There is no mention of a dedicated research lab, team, or center in the provided information. However, her ongoing research projects suggest active scholarly activity, likely involving collaboration within and beyond NIU.

Anthony CleveView profile

Professor

• information system maintenance and evolution
• software and data reverse engineering
• program analysis and transformation
• +5 more

Anthony Cleve is a Full Professor in information system evolution at the University of Namur, Faculty of Computer Science. He serves as President of the Faculty Council and is a member of the Council of the Academic Body (COACA). Cleve is affiliated with the PReCISE research center and the Namur Digital Institute (NADI), where he leads the Data-Intensive Systems Evolution Lab. He holds a PhD in Computer Science (2009) and an MSc in Computer Science (2004) from the University of Namur, along with a Bachelor in Economics and Management. Prior to his current position, Cleve was an ERCIM post-doctoral research fellow at INRIA Lille (2009-2010) and worked as a visiting researcher at CWI, Amsterdam (2005-2006). Professor Cleve's research focuses on information system maintenance and evolution, with particular expertise in software and data reverse engineering, program analysis and transformation, and self-adaptive systems. His work bridges theoretical computer science with practical applications, especially in database engineering, system migration, and co-evolution of databases and programs. More recently, his research has expanded into applying computer science techniques to French-Sign language alignment and translation. His research output shows a strong trend toward microservices architecture, data access patterns, and visualization techniques for understanding complex software systems. Cleve has been actively developing tools like DENIM for exploring data access in microservices environments, demonstrating his commitment to practical solutions for contemporary software engineering challenges. Scientific Awards Namurois of the year 2022, Sciences category Best Paper Award at the 20th IEEE Working Conference on Source Code Analysis and Manipulation (SCAM 2020), NIER track Best Paper Award at the 2016 International Conference on Software Quality, Reliability and Security (QRS 2016) Nominated for the Cor Baayen Award 2012 IBM Belgium / FRS-FNRS 2010 Award for best PhD thesis in Computer Science ERCIM "Alain Bensoussan" Post-doctoral Fellowship (2009-2010) Professor Cleve actively mentors students and researchers, serving as promoter/supervisor for several PhD candidates. He has secured significant research funding through multiple projects including RAINDROP, INSTINCT, and various projects on database schema evolution in microservices applications. His research group collaborates extensively with institutions across Europe. He leads the Data-Intensive Systems Evolution Lab at the Namur Digital Institute (NADI) and is a key member of the Namur Institute of Language, Text and Transmediality (NaLTT), where he applies his expertise to sign language processing challenges. His lab focuses on developing practical tools and methodologies for system evolution, with recent work emphasizing microservices architectures and data access patterns.

Aleksandr PerevalovView profile

Researcher

• Question Answering over Knowledge Graphs
• Multilingual Accessibility of Web Systems
• Quantitative Text Analysis
• +3 more

Aleksandr Perevalov is a researcher and PhD student at Anhalt University of Applied Sciences, affiliated with the Department of Computer Science and Languages. His work focuses on question answering systems over knowledge graphs, multilingual accessibility, and quantitative text analysis. Education: BS in Informatics (Perm National Research Polytechnic University), MS in Informatics (Perm), and MS in Data Science (Anhalt University of Applied Sciences, double degree) Employment: Research staff at Hochschule Anhalt since 2020 Research interests center on knowledge graph question answering systems, including automated semantics-driven service composition, entity-aware machine translation, and linguistic analysis of human-computer dialogues. He also explores conversational AI implementation strategies and language model evolution. Recent publications demonstrate expertise in semantic computing, multilingual system design, and benchmark creation. His work bridges academic research with practical applications in web engineering and language technology. 2018: 1st prize at Perm University conference 2018: TOP10 in Russian AI forum Machine Learning competition 2019: TOP9 in Data Mining Cup 2020: Bronze medal on Kaggle toxic comment classification Currently contributing to academic discourse through both peer-reviewed conference papers and industry-focused Medium publications.

Marta Isabel Gomes de SousaView profile

Assistant Professor

• Sexual Crimes Against Children
• Intimate Partner Violence
• Violent Offenders
• +6 more

Marta Isabel Gomes de Sousa is an Assistant Professor at Lusófona University's Faculty of Psychology and Education. She is a practicing forensic psychologist actively engaged in research and intervention programs related to sexual crimes against children, intimate partner violence, and the mental health impacts of imprisonment. Her research focuses on systematic reviews and intervention programs for offenders, emphasizing rehabilitation , risk assessment , and the mental health of inmates and prison staff . She also explores how positive and negative childhood experiences influence adult antisocial behavior and sexual crimes. Recent publications include meta-analyses of prison reintegration programs (2025), scoping reviews on investigative interviewing (2025), and studies on gender-specific interventions for female offenders (2025). Her work aligns with UN Sustainable Development Goals related to justice and mental health. She has organized academic events like the II Jornadas de Psicologia: Práticas e Aplicações (2024) and contributes to public discourse through media interviews on forensic psychology topics.

• Computer Science
• Semantic Web
• Ontology Matching
• +3 more

Alsayed Algergawy is a researcher at the Institute of Computer Science , Friedrich Schiller University Jena . His work focuses on ontology alignment , schema matching , and knowledge graph integration . Affiliation: Friedrich Schiller University Jena, Institute of Computer Science Research interests span semantic web technologies , machine learning for data integration , and ontology engineering , with applications in biodiversity and invasion biology . He has developed tools like OAPT for ontology partitioning and DREIFLUSS for table matching. His recent publications emphasize LLM-driven knowledge graph completion , semantic annotation of scientific datasets , and clustering-based ontology matching . Collaborative projects include BiodivNERE for NLP in biodiversity and INBIO (Invasion Biology Ontology).

• Database Systems
• Machine Learning
• Graph Theory
• +3 more

Shuai Ma is a researcher at Beihang University , School of Computer Science and Engineering, China. His work spans database systems , machine learning , and natural language processing , focusing on temporal knowledge graphs, graph neural networks, and privacy-preserving federated learning. He received his PhD from the University of Edinburgh , UK, in 2011. Research interests include graph theory , spatiotemporal data analysis , data mining , and anomaly detection . His recent publications address: 2025 : Technology mapping for ASICs, temporal network motifs, and 3D geometry compression. 2024 : Knowledge graph completion, scene mining for e-commerce, and secure aggregation for federated learning. Article trends reveal expertise in graph neural networks , temporal data processing , and privacy-aware systems . Collaborations with institutions like Concordia University and industry leaders underscore his interdisciplinary impact.

Lora AroyoView profile

Professor

• Crowdsourcing and human computation
• Hybrid human-AI systems
• Video understanding and multimedia semantics
• +4 more

Lora Aroyo is Full Professor in the Department of Computer Science at VU University Amsterdam , leading the Web & Media group and actively contributing to the university’s Network Institute . Her research centers on hybrid human-AI systems for video understanding, crowdsourcing, data quality, and semantic search, with strong impact on digital humanities, cultural heritage, and interactive television. Research Interests: Human computation and large-scale crowdsourcing Hybrid human-AI architectures for multimedia analysis Data quality, annotation reliability, and disagreement modeling Semantic search and recommendation in cultural heritage Responsible AI and pluralistic alignment of generative models Across 2023–2025 her publications reveal a sharp focus on AI safety for generative and multimodal systems, including red-teaming of text-to-image models, evaluation of safety perceptions across demographic groups, and the creation of open benchmarks and datasets to support these goals. Earlier work (2018–2022) addresses video discovery, cultural heritage metadata, and human-centered data practices. Scientific Service & Funding: She has led major Dutch and EU projects in semantic search, event-driven multimedia access, and digital infrastructures for humanities research. She currently serves on the editorial board of PeerJ Computer Science . Labs & Teams: Prof. Aroyo heads the Web & Media group at VU, collaborates closely with the Network Institute , and coordinates interdisciplinary teams spanning computer science, digital humanities, and AI ethics.

• Mathematics Education
• Assessment in Education
• Inquiry-Based Learning
• +3 more

Dr. M. (Michiel) Veldhuis is an Assistant Professor in Mathematics Education at the Freudenthal Institute , Utrecht University. His research focuses on higher-order thinking skills in mathematics, inquiry-based learning , and ICT integration in educational settings. He is actively involved in projects like Beyond Flatland , which explores dynamic data processing in primary mathematics, and serves as a board member for the Dutch Association for Mathematics Education (NVORWO) and European Association for Research in Mathematics Education (ERME). PhD in Mathematics Education (2015), Utrecht University MSc (Research) in Cognitive Psychology (2011), University of Toulouse-II BSc in Applied Mathematics (2011), University of Toulouse-II Veldhuis’ research emphasizes embodied learning and representational redescription to enhance mathematical understanding. His work spans primary to secondary education , addressing cultural diversity and sustainability in STEM. He collaborates with institutions like the Leibniz Institute IPN Kiel and contributes to EU-funded initiatives such as Erasmus+ TIME. Recent publications analyze growth mindset cultivation in Dutch classrooms and mathematical origami for secondary education. His Beyond Flatland project (2016–2020) received NWO funding (€700k) and focused on algebraic reasoning and probability theory through ICT interventions .

Erhard RahmView profile

Professor

• Data Integration
• Knowledge Graphs
• Privacy-Preserving Data Analysis
• +4 more

Prof. Dr. Erhard Rahm is a leading computer science academic at the University of Leipzig , affiliated with the Institute of Computer Science under the Faculty of Mathematics and Computer Science. With over 35 years of research contributions, he specializes in scalable data integration, privacy-preserving record linkage (PPRL), and graph analytics for knowledge graphs and digital twins. Key research areas: Data Integration for Knowledge Graphs, Privacy-Preserving Data Analysis, Dynamic Graph Management Recent work focuses on hybrid digital twins, medical image analysis, and secure health data processing 2016-2021: Speaker of GI's Database Systems and Information Systems division Scientific Contributions: His 15 most recent publications (2023-2025) span: Privacy-preserving machine learning (federated learning, PPRL with LLMs) Graph-based data transformations (Temporal Knowledge Graphs, Property Graph Streams) Automated schema matching and entity resolution systems Biomedical data applications (cell confluence assessment, stress detection) Selected Honors: VLDB Ten-Year Best Paper Award (2011) ICDE Influential Paper Award (2013) MSR Outstanding Collaborator Award (2016) Leadership Roles: Currently Vice President of the Gesellschaft für Informatik (since 2022), former DFG reviewer (2016-2024), and active in NFDI infrastructure (2019-2022). He leads research at ScaDS.AI, focusing on big data integration and scalable graph analytics.

Varish MulwadView profile

Researcher

• Information Extraction
• Knowledge Graph Population
• Semantic Web
• +4 more

Varish Mulwad is a Senior Scientist at GE Research with 14 years of experience in algorithm development and knowledge graph construction from structured/unstructured data. He holds a Ph.D. and M.S. in Computer Science from the University of Maryland, Baltimore County (UMBC), where he worked under Prof. Tim Finin and collaborated with Prof. Anupam Joshi, and a B.E. in Computer Engineering from University of Mumbai. Ph.D. & M.S. in Computer Science (UMBC) B.E. in Computer Engineering (University of Mumbai) His research focuses on semantic interpretation of tabular data through linked data frameworks, information extraction from unstructured text, and knowledge graph population using probabilistic reasoning and graphical models. He has pioneered domain-independent systems for table interpretation and developed novel methods for cloud SLA automation and cybersecurity threat detection via social media analysis. Recent work trends include: Context-aware web table annotation Relational table representation learning Linked data generation from spreadsheets Pre-training/fine-tuning paradigms for web tables Application of semantic web standards to cybersecurity He has led 3-4 member project teams in developing production-ready solutions, contributed to 19 peer-reviewed publications, and secured 7 patents with 900+ citations. During his academic tenure at UMBC's Ebiquity Research Lab, he co-developed the TABEL framework for table semantics inference and produced the first interactive system for meta-analysis report generation from linked data.

Devavrat ShahView profile

Professor

• Machine Learning
• Artificial Intelligence
• Data Science
• +7 more

Devavrat Shah is a Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Laboratory for Information and Decision Systems (LIDS). His research focuses on machine learning, causal inference, and algorithmic fairness, with applications in healthcare outcomes, criminal justice reform, and cryptocurrency analysis. He has contributed to groundbreaking work, such as developing a machine-learning algorithm that nearly doubled Bitcoin investments over 50 days using real-time price data analysis. Shah's academic work integrates statistical methods with real-world challenges, including personalized medicine, policy evaluation, and bias detection in algorithms. His recent projects include global clinical studies on lymphoma treatments and frameworks for auditing racial bias in law enforcement systems. His interdisciplinary approach bridges computer science, statistics, and domain-specific applications. Key areas of his research include causal inference frameworks for data-rich environments, algorithmic fairness in decision-making systems, and predictive modeling for healthcare and public policy. His work often combines theoretical rigor with practical impact, addressing societal challenges through data-driven solutions. Shah's contributions to synthetic interventions and causal simulators have advanced trace-driven simulation methodologies, while his collaboration with global consortia like PETAL highlights his commitment to translational research. His students, including Kang Zhang, have contributed to impactful projects in algorithm design and data science.

Simon WattView profile

Senior Lecturer

• Sensorimotor Control
• Multisensory Integration
• 3D Vision
• +3 more

Simon Watt is a Senior Lecturer in the Department of Psychology at Bangor University's School of Psychology and Sport Science. His research focuses on sensorimotor control, multisensory integration, and 3D vision, with applications to prosthetic limb design, virtual reality systems, and surgical robotics. PhD in Psychology from University of Surrey Postdoctoral research at UC Berkeley Joined Bangor University faculty in 2004 Director of the Cognitive Neuroscience Institute His work explores how humans control hands and tools in 3D space, examining whether tools become incorporated into body schema and how sensorimotor mechanisms adapt to different tool geometries. Key research areas include: Tool use and body schema modification Visual-tactile integration Reaching and grasping mechanics Stereoscopic display optimization Recent studies investigate the functional requirements for tool control resembling body parts, revealing both successful integration and surprising failures depending on tool properties. This aligns with his broader approach in 'Pasteur's Quadrant,' combining fundamental science with practical applications. Affiliation: Bangor University, School of Psychology and Sport Science, Department of Psychology

Megan BurtonView profile

Professor

• STEM Education
• Elementary Mathematics Education
• Teacher Identity and Beliefs
• +4 more

Megan Burton is a Professor of Elementary Education in the Department of Curriculum and Teaching at Auburn University. She specializes in STEM education, with a focus on elementary mathematics teachers' identities, beliefs, and inclusive practices. Her work includes developing teacher candidates' abilities to address diverse learner needs through innovative instructional strategies and technology integration. Dr. Burton has led STEM camps and conducted research on AI in education, equity frameworks, and culturally responsive pedagogy. Ph.D. in Elementary Education, Mathematics (2006), The University of Alabama M.Ed. in Early Childhood Education (1998), Kennesaw State University B.S. in Elementary Education (1994), Auburn University Dr. Burton's research spans inclusive STEM education, teacher identity, and the application of artificial intelligence in mathematics instruction. She has published extensively in journals such as Journal of Teacher Education and Young Children , emphasizing accessible pedagogy and equity. Her recent articles explore AI tools, STEM equity in picture books, and design thinking for societal improvement. Key trends in her work include: Integration of STEM with literacy and empathy-driven design Addressing the digital divide through discursive practices and AI tools Advancing inclusive pedagogy for struggling and multilingual learners Analyzing teacher self-efficacy in virtual and pandemic-driven environments Developing pre-service teachers' STEM and mathematics competencies Advocating for equity-focused scholarly communities Past President, Association of Mathematics Teacher Educators Co-author of Making Mathematics Standards Accessible to Students with Diverse Learning Needs Dr. Burton combines classroom experience from her decade as an elementary teacher with academic research to prepare educators for inclusive STEM teaching. She mentors teacher candidates through field experiences and technology-enhanced pedagogy, ensuring practical application of her findings.

• Data Science
• Big Data
• Natural Language Query Processing
• +4 more

Prof. Dr. Kurt Stockinger is a Professor of Computer Science at ZHAW School of Engineering and holds a doctorate at the University of Zurich . He serves as Head of the MAS Data Science program and co-leads the ZHAW Datalab . His research focuses on Intelligent Information Systems , bridging information systems, natural language processing, and machine learning. Affiliated with the University of Zurich, he contributes to Quantum Machine Learning and Open Data Exploration initiatives. Stockinger's educational background includes a PhD in Computer Science (University of Vienna & CERN), a Master in Business Informatics (University of Vienna), and a CAS in Didactics & Methodology (ZHAW). He has taught courses in Quantum Computing , Big Data for Natural Sciences , and Data Science programs at ZHAW and University of Zurich. His research spans Data Science , Big Data , Natural Language Query Processing , Knowledge Graphs , and Quantum Machine Learning . Recent publications focus on quantum autoencoders , hybrid quantum neural networks , and prompt engineering for knowledge graph question answering. He has developed frameworks like ScienceBenchmark for real-world NL-to-SQL evaluation and NQuest for natural language query exploration. Scientific awards include the Best Paper Award at 7th Swiss Conference on Data Science (2020) He leads major projects such as DataGEMS (Data Discovery Platform, Horizon Europe) Digital Health Zurich (Clinical Innovation Lab) INODE4StatBot.swiss (NL-to-SQL Translation) GraphQueryML (Graph Database Optimization) ScienceBenchmark (NL-to-SQL Evaluation) Stockinger's work intersects with computer vision , biomedical data , and industrial applications , demonstrated through collaborations with institutions like Lawrence Berkeley National Laboratory, CERN, and University of Washington. He has contributed to establishing QuantumBasel and ZHAW Datalab as research hubs.