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Dr. I-Ling Yen is a Professor of Computer Science at The University of Texas at Dallas (UTD), affiliated with the Erik Jonsson School of Engineering and Computer Science. She holds a Ph.D. in Computer Science from the University of Houston (1992), an M.S. in Computer Science from the same institution (1985), and a B.S. in Physics from National Tsing-Hua University (1979). Her research focuses on high assurance systems, parallel and distributed computing, secure systems, grid computing, and component-based design. Research Interests High assurance systems Secure and dependable systems Parallel/distributed computing Grid and peer-to-peer computing Systems engineering Component-based adaptive systems Key Contributions Her work emphasizes QoS-driven service composition, reconfigurable systems, and dependability in cloud and distributed environments. Notable outputs include frameworks for cloud computing dependability metrics, role-based security models, and optimization for intelligent transportation systems. Grants & Funding NSF MRI Consortium (2011–2014): $977K for cloud computing instrumentation NSF QoS-Assured Service Composition (2011–2013): $198K Multiple industry grants from Lockheed Martin, Cisco, Texas Instruments, and Alcatel Professional Service Extensive leadership roles in conferences like IEEE HASE, SOSE, and SRDS, including program chair positions and steering committee memberships. Active as a reviewer for top journals and conferences in systems engineering and software reliability. Academic Leadership UTD service roles include Department By-Law Committee Chair (2007–2010), Search Committee member, and graduate student admissions involvement.

• High assurance systems
• Parallel and distributed computing
• Secure and dependable systems
• +3 more

Jose M. Vidal is a Professor and Director of Undergraduate Studies in the Computer Science and Engineering department at the Molinaroli College of Engineering and Computing, University of South Carolina . He holds a Ph.D. in Computer Science and Engineering from the University of Michigan (1998), an M.S. in Computer Science from Rensselaer Polytechnic Institute (1991), and a B.S. in Computer Science and Engineering from MIT (1990). His research focuses on multiagent systems , spanning theoretical aspects like coordination mechanisms, algorithmic game theory, and distributed algorithms, as well as implementation in agent-based simulations, web services, and mobile applications. He has authored numerous publications in fields including healthcare process optimization, traffic engineering, and sociological theory construction. 2019: Ad Hoc Vehicle Platoon Formation (Traffic Engineering) 2019: Wikitheoria for Sociological Theory Construction 2018: Email Intent Classification using Deep Learning 2017: Intelligent Transportation Systems using Mobile Data 2016: Healthcare Workflow Simulation Models 2014: Behavioral Modeling from Observational Data He has received significant funding from the NSF, Darpa, and industry partners for projects like Wikitheoria (a collaborative theory-building platform), TargetShare (resource allocation), and mobile healthcare applications. His work bridges theoretical research with practical implementations in domains ranging from traffic systems to hospital operations.

• Multiagent Systems
• Agent-based Modeling
• Algorithmic Game Theory
• +7 more

Michael N. Huhns is the NCR Distinguished Professor Emeritus of Computer Science and Engineering at the University of South Carolina, affiliated with the Molinaroli College of Engineering and Computing. He previously served as Department Chair and Director of the USC Center for Information Technology. He holds a BSE from the University of Michigan (1969), M.S. and Ph.D. in Electrical Engineering from the University of Southern California (1971, 1975). His research spans multiagent systems, service-oriented computing, ontology-based systems, and computational sociotechnical systems. He has authored over 250 papers and 11 books, including seminal works like Service-Oriented Computing: Semantics, Processes, Agents . He holds a patent for distributed computer system architecture and has received accolades such as IEEE Fellowship and AAAI Fellowship. Research interests emphasize distributed intelligence, system robustness, and socio-technical interactions. His articles explore agent negotiation, cloud-based systems, and ethical AI. Notable grants include projects on information dominance, healthcare systems, and environmental sensor networks. Awards: IEEE Fellow, AAAI Fellow, APAIA Fellow Advising: Supervised 12 PhD students and over 40 M.S. theses Labs/Teams: Founder of the International Foundation for Autonomous Agents and Multiagent Systems

• Multiagent Systems
• Service-Oriented Computing
• Enterprise Integration
• +5 more

Adnan Ashraf serves as a Senior University Lecturer at the Department of Information Technology within the Faculty of Science and Engineering at Åbo Akademi University, Finland. His academic profile spans software engineering, cybersecurity, and applied artificial intelligence with emphasis on maritime systems and drone technologies, supported by extensive EU and national research funding. His research portfolio demonstrates deep expertise in: Security frameworks for DevOps and IoT networks Machine learning applications in performance testing Edge computing optimization for resource-constrained environments Swarm robotics navigation and collision avoidance Systematic literature reviews in emerging software domains Analysis of his 46+ publications (2010-2024) reveals consistent focus on bridging theoretical models with practical implementations. Key trends include security enhancement through SDN controllers, reinforcement learning for UAV path planning, and systematic reviews of API documentation practices. His work consistently addresses real-world challenges in critical infrastructure domains with strong empirical validation. Dr. Ashraf has secured significant research funding including EU Horizon 2020 VeriDevOps (as Principal Investigator) and MegaM@Rt2 projects (as Co-Investigator), demonstrating leadership in collaborative research addressing DevOps security and runtime modeling challenges. While specific student supervision details aren't publicly enumerated, his project leadership indicates active mentorship in software engineering research.

• Software Engineering
• Cybersecurity
• Machine Learning
• +7 more

Roberto Corizzo is a Research Fellow at the Department of Computer Science, University of Bari, Italy. He holds a Ph.D. and is affiliated with the LACAM Laboratory. His research focuses on big data analytics, data mining, predictive modeling for sensor networks, energy prediction in smart grids, and anomaly detection. He has conducted research internships at INESC TEC (Portugal) under Prof. João Gama and at the American University (Washington D.C.) under Prof. Nathalie Japkowicz. Key research interests include: Big Data Analytics Predictive Modeling for Sensor Networks Energy Prediction in Smart Grids Anomaly Detection in Dynamic Systems His work spans over 15 publications from 2014–2019, addressing challenges in data stream analysis, renewable energy forecasting, and distributed computing. Notable contributions include Spark-GHSOM for large-scale data clustering and DENCAST for multi-target regression. He has organized conference challenges (e.g., ECML/PKDD Discovery Challenges) and contributed to projects like VIPOC for renewable energy prediction. No scientific awards are explicitly listed. He collaborates with academic institutions globally and participates in interdisciplinary projects involving energy systems and semantic services in big data platforms.

• Big Data Analytics
• Data Mining
• Predictive Modeling
• +3 more

Aritra Dasgupta is an Assistant Professor in Data Science at the New Jersey Institute of Technology (NJIT). His work focuses on visual analytics, machine learning interpretability, and privacy-preserving visualization techniques. He holds a Ph.D. in Computer Science from the University of North Carolina at Charlotte (2012), an M.S. from the same institution (2008), and a B.Tech. in Information Technology from the West Bengal University of Technology (2005). Research interests include: Trustworthy AI and model explainability Climate and energy systems modeling Human-in-the-loop analytics Privacy-preserving data visualization Recent work emphasizes: Developing interactive tools for decision support Addressing adversarial attacks on machine learning systems Designing transparent algorithmic ranking systems His research bridges technical innovations with human factors, aiming to create usable and ethical data-driven systems. Collaborations span climate science, energy systems, and social computing domains.

• Data Science
• Visual Analytics
• Machine Learning
• +4 more

Leah Bidlake is an Associate Teaching Professor and Assistant Dean for Teaching and Undergraduate Affairs in the Department of Computer Science at the University of New Brunswick (UNB). She is based in Fredericton and can be reached at ITD 422 or via email. Her research focuses on the Psychology of Programming and Computer Science Education, particularly exploring mental models formed during parallel programming learning and comprehension. Leah holds a Bachelor of Computer Science (Cooperative Education Program), a Bachelor of Education, a Master of Computer Science, and a PhD, all from UNB. She also earned a NB Department of Education Teacher's Certificate in Computer Science and Mathematics, alongside a Diploma in University Teaching from UNB. Before joining UNB, she taught in New Brunswick's public school system, bridging K-12 and higher education. Her research emphasizes empirical studies on mental representations in programming education, with publications analyzing cognitive processes in parallel programming comprehension and educational methodologies. She has contributed to tools like Grailog KS Viz 2.0 and explored semantic web techniques in earlier work. Leah’s academic leadership includes her role as Assistant Dean, where she oversees undergraduate affairs and teaching initiatives. While no specific grants or awards are listed, her work reflects a commitment to enhancing computer science education through cognitive-focused research and pedagogical innovation.

• Computer Science Education
• Psychology of Programming
• Mental Models in Programming
• +3 more

Dr. Amir Masoumzadeh is an Associate Professor in the Department of Computer Science at the University at Albany, State University of New York, where he co-directs the Albany Lab for Privacy and Security (ALPS). His academic journey includes a PhD in Information Science from the University of Pittsburgh (2014). Dr. Masoumzadeh's research focuses on information security, privacy, and trust in modern computing systems. His work centers on developing theoretical frameworks and practical mechanisms for protecting information in complex environments such as online social networks and enabling secure data sharing while preserving user privacy. His expertise spans formal methods, knowledge representation and reasoning, data mining, and information system design, with specific applications in access control policy specification, verification, analysis, and testing. His research has significant implications for browser security, privacy-preserving data mining of complex graph structures, and privacy-enhancing technologies in web and location-based services. Analysis of Dr. Masoumzadeh's publication record reveals a consistent focus on access control policy modeling, verification, and learning from black-box systems. His work demonstrates a progression from foundational research on privacy in social networks and location-based services toward more sophisticated approaches involving machine learning for policy discovery and verification. The emergence of social engineering attack countermeasures in his recent work represents an important expansion of his research into human-centered security challenges. NSF CAREER Award for "Black-Box Learning of Authorization Policies" DARPA Funding for "PANACEA: Personalized AutoNomous Agents Countering Social Engineering Attacks" NSF Student Travel Grants for IEEE TPS conferences Dr. Masoumzadeh actively mentors a diverse group of students, including PhD candidates, undergraduate researchers, and high school interns. His research is supported by substantial external funding from NSF and DARPA, enabling cutting-edge work at the intersection of security, privacy, and machine learning. The Albany Lab for Privacy and Security (ALPS), which he co-directs, serves as a hub for collaborative research on privacy and security challenges in modern computing environments. His projects often involve interdisciplinary teams addressing real-world security problems with both theoretical rigor and practical applicability.

• Information Security
• Privacy Protection
• Trust Management
• +13 more

Mohamed Amine Chatti is Professor of Computer Science and head of the Social Computing Group at the University of Duisburg-Essen's Department of Human-centered Computing and Cognitive Science. His research develops intelligent systems for learning analytics, knowledge management, and personalized education. Current projects focus on explainable recommender systems, educational knowledge graphs, and human-centered AI for learning. The OpenLAP platform enables customizable learning analytics, while CourseMapper supports collaborative course design with automatic knowledge graph construction. Recent work explores transparent user modeling and justification mechanisms in scientific literature recommendation systems. Research bridges data science, HCI, and learning technology, emphasizing user control and interpretability in AI-driven educational tools. Publications appear in journals including IEEE Transactions on Learning Technologies and Computers in Human Behavior.

• Learning Analytics
• Recommender Systems
• Knowledge Management
• +2 more

Dr. Hai Huang is a Senior Lecturer in Computing at the University of Greenwich, affiliated with the School of Computing and Mathematical Sciences under the Faculty of Engineering and Science. He holds a PhD from Swinburne University of Technology, Australia, and has over 10 years of international research experience across France, Australia, Saudi Arabia, Ireland, and China. Prior to his current role, he served as a Senior Research Fellow at INRIA, the French Institute for Research in Computer Science and Automation. His research focuses on computer science and informatics, with expertise in semantic web technologies, database systems, information retrieval, and query optimization. Key areas include RDF data management, SPARQL query processing, probabilistic databases, and ontology-driven systems. Dr. Huang’s work spans theoretical advancements and practical applications, addressing challenges in web harvesting, data integration, and user profiling through formal concept analysis (FCA). His contributions include innovations in query relaxation, selectivity estimation, and legal rule visualization for compliance systems. No academic awards or grants are explicitly listed, and no student advisees are documented here. His research activities are centered at the University of Greenwich, though specific lab affiliations are not mentioned.

• Computer Science
• Informatics
• Semantic Web
• +7 more

Dr Christian Clausner is a Research Fellow at the University of Salford, affiliated with the School of Science, Engineering & Environment and the Informatics research center. He holds a part-time PhD in Computer Science, completed in parallel with his academic role. His research focuses on image analysis, pattern recognition, and document analysis, with a particular emphasis on OCR technology, historical document digitization, and semantic metadata frameworks. Education: Studied Computer Science and Artificial Intelligence in Germany. Professional Experience: Joined academia in 2009 after private sector work, specializing in technical workflows for large-scale document digitization projects. Research Highlights: Developed NAME XML for entity-relation tagging, contributed to OCR evaluation tools, and led initiatives like the 1961 UK Census digitization and crowdsourcing for tabular data extraction. He co-chaired HIP workshops in 2021 and 2023, advancing historical document processing standards. Key Projects: WaterAGRI (2020–2024), Europeana Newspapers OCR workflow, and the Medical Officer of Health Reports scoping study. His work bridges computer science and cultural heritage, addressing challenges in text recognition, layout analysis, and semantic labeling.

• Image Analysis
• Pattern Recognition
• Document Analysis
• +3 more

Panagiotis Stamatopoulos is an Assistant Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, where he has been employed since 1993. He holds a PhD in Computer Science (1988) and a Diploma in Physics (1982) from the University of Athens. His research spans artificial intelligence, constraint programming, natural language processing, machine learning, and optimization. Specific interests include: Hybrid approaches combining constraint programming with operations research Natural language understanding for database access Parallel processing and distributed constraint solving Multi-agent systems and web intelligence applications His publications show consistent focus on constraint satisfaction algorithms, text summarization techniques, educational timetabling systems, and AI applications in diverse domains like sports analytics and robotics. Recent works demonstrate increased attention to NLP evaluation metrics and multimodal learning. He has supervised numerous diploma theses and led projects funded by the European Union (EDS, APPLAUSE, PARACHUTE, PARROT), University of Athens, and Olympic Airways. Stamatopoulos teaches undergraduate courses in Introduction to Programming and Logic Programming, plus postgraduate courses in Advanced Artificial Intelligence. He previously taught Artificial Intelligence, System Programming, and Expert Systems.

• Artificial Intelligence
• Constraint Programming
• Logic Programming
• +9 more

Ullrich Martin is a Professor and Head of the Institute of Railway and Transport Engineering at the University of Stuttgart, Germany. His work spans railway systems, infrastructure modeling, and transport policy. Key areas include fault diagnosis, simulation-based optimization, and capacity evaluation. Contact: Pfaffenwaldring 7, 70569 Stuttgart, Germany Office Hours: By agreement Research Trends: Recent publications focus on GAN-based data augmentation for railway fault detection, high-speed maglev systems optimization, and early instability detection in ballast tracks. His team explores discrete element modeling, operational risk analysis, and machine learning applications for track condition monitoring. Infrastructure Innovation: He drives digitalization in railway planning through graph-based knowledge databases and automated compliance tools. Projects address dwell time forecasting, electromagnetic suspension design, and accessibility solutions like the Sinn²-App for visually impaired passengers. Operational Modeling: His work includes tabu search algorithms for dispatching, reinforcement learning for timetable calibration, and multi-scale simulation frameworks. He investigates interactions between track irregularities and vehicle dynamics, with a focus on safety and efficiency.

• Railway Engineering
• Transport Systems
• Fault Diagnosis
• +7 more

Dr. Hyunsoung Park is an Assistant Professor of Civil Engineering and Program Director of Construction Management at the University of Evansville's College of Engineering and Science. His expertise spans Building Information Modeling (BIM), construction safety ontology systems, and natural disaster risk analysis. He holds a PhD in Construction Management from the University of Florida, MS from Texas A&M, and BS from Hongik University, South Korea. Education: PhD in Construction Management, University of Florida MS in Construction Management, Texas A&M University BS in Architectural Engineering, Hongik University Graduate Certificates: Teaching with Technology (University of Florida), Protege (Stanford University) His research focuses on integrating deep learning algorithms for disaster cost prediction, ontology-driven safety knowledge systems, and resilient infrastructure design. Recent work includes frameworks for natural disaster-induced cost mitigation and design-stage safety protocols using ontology models. He is a member of ASCE Construction Institute and SLX honor society. Awards: Grinter Fellowship (University of Florida) Top-Off Scholarship (Texas A&M) Experience: Lab Instructor, University of Florida Research Assistant, Human-Centered Innovative Technology Lab Assistant Construction Project Manager, Hyundai Engineering & Construction Prior to academia, he served as a Sergeant in the Republic of Korea Air Force and held administrative roles in architectural engineering departments.

• Building Information Modeling
• Construction Safety
• Ontology in Construction Domain
• +3 more

Philip Bogden is Associate Teaching Professor of Computer Science at Northeastern University's Roux Institute, specializing in data visualization, data science, web technologies, and AI/ML. With significant industry experience, he has consulted for energy and finance sectors and served as CEO of a nonprofit providing real-time environmental data. His research develops computational solutions for environmental challenges, including flood detection systems, coastal hazard modeling, and oceanographic data infrastructure. Projects emphasize open data standards and AI applications for disaster resilience. Bogden previously contributed to open data policy at the National Science Foundation and held faculty positions at Yale and UConn. Education includes a PhD from University of California and bachelor's degree from Harvard University.

• Data Visualization
• Data Science
• Web Technologies
• +2 more