Professor Elena Simperl is affiliated with the University of Southampton, UK, as a faculty member in the Department of Electronics and Computer Science (ECS), specifically within the Web and Internet Science (WAIS) research group. She holds a doctoral degree (Dr. rer. nat.) in Computer Science from Freie Universität Berlin and a Diploma in Computer Science from Technische Universität München. Research Focus: Intersects knowledge technologies, social computing, and crowdsourcing, with emphasis on incentivizing collaboration via semantically enabled web systems like citizen science platforms, open innovation initiatives, and universal knowledge bases (DBpedia, Wikidata, Linked Open Data Cloud). Academic Leadership: Coordinated over twenty European/national research projects, served as scientific director of the European Data Science Academy (EDSA), and led educational initiatives including EUCLID curriculum development and ESWC summer schools. Conference Roles: Held leadership positions at ISWC, ESWC, EDF, and ESTC conferences as track co-chair, general co-chair, and program chair. Labs: Active member of the Web and Internet Science (WAIS) research group at ECS, University of Southampton.
Dr. Ismail Sengor Altingovde serves as an Associate Professor in the Department of Computer Engineering within the College of Engineering at Middle East Technical University (METU) in Ankara, Turkey. Previously, he completed his B.S. and M.S. degrees at Bilkent University, followed by a Ph.D. in Computer Engineering from Bilkent in 2009. His academic journey includes post-doctoral research at Bilkent University (2009-2011) and L3S Research Center in Hannover, Germany (2011-2012) before joining METU. His educational background includes: B.S. in Computer Engineering, Bilkent University (1999) M.S. in Computer Engineering, Bilkent University (2001) Ph.D. in Computer Engineering, Bilkent University (2009) - Thesis: "Improving The Efficiency of Search Engines: Strategies for Focused Crawling, Searching, and Index Pruning" Dr. Altingovde's research focuses on Information Retrieval , particularly Web Search and Mining, Big Data analysis, and Database Management Systems. His work addresses critical challenges in search result diversification, query performance prediction, and scalable indexing techniques. He has pioneered approaches in handling zero-result queries, integrating social signals into search, and developing neural information retrieval models. His research bridges theoretical algorithm design with practical implementations for real-world search engines. His publication record demonstrates a strong trajectory in search technologies, with recent work emphasizing neural information retrieval, social media integration in search, and cross-lingual search systems. The research shows consistent focus on improving search relevance while addressing scalability challenges in modern web-scale systems. His work spans both theoretical contributions and practical implementations with industry relevance. Among his notable recognitions: Distinguished Young Scientist 2016 award (GEBIP) from Turkish Academy of Sciences (TUBA) 2013 Yahoo! Faculty Research and Engagement Program (FREP) award (selected from 27 researchers across 24 countries) Dr. Altingovde actively contributes to the research community through professional service including co-chairing ECIR 2017 short paper track and serving on program committees for CIKM, SIGIR, and Web Science conferences. He has secured multiple research grants from TÜBITAK (Scientific and Technological Research Council of Turkey) including projects on query result caching, semantic relationships for search scalability, and domain-specific search engines. His work connects academic research with practical applications through collaborations with industry partners like Yahoo! Research. He leads research within METU's Computer Engineering Department, contributing to projects like LivingKnowledge (focusing on fact, opinions and bias in time) and previously participating in European projects like MUSCLE (Multimedia Understanding through Semantics, Computation, and Learning). His laboratory work emphasizes experimental validation of search algorithms with real-world datasets and practical implementations.
Luca Vassio is a Fixed-term tenure-track Assistant Professor at the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino. He is also a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. His academic work spans multiple degree programs including Ingegneria Elettronica, delle Telecomunicazioni e Fisica, and Ingegneria Informatica, del Cinema e Meccatronica. Vassio serves as a PhD tutor for students in the Ingegneria Informatica E Dei Sistemi program. Dr. Vassio's research interests focus on Artificial Intelligence for Network Security, Machine Learning for Network measurement and management, and Performance of network protocols and services. His work bridges theoretical computer science with practical applications in cybersecurity and data analysis. He is particularly interested in applying machine learning techniques to network security challenges, social network analysis, and big data processing. His interdisciplinary approach combines elements of computer science, data science, and network engineering to address contemporary challenges in digital infrastructure. Vassio's recent publications demonstrate a strong focus on network security, social media analysis, and machine learning applications. His work spans from analyzing Telegram group dynamics and Facebook content to developing advanced techniques for network anomaly detection and darknet traffic analysis. A significant portion of his research applies graph neural networks and embedding techniques to cybersecurity problems, showing a consistent thread of using advanced machine learning methods to address network security challenges. His publications appear in reputable venues including ACM Transactions on the Web, IEEE conferences, and other high-impact computer science publications. As a research leader, Vassio serves as Scientific Responsible for multiple commercial research projects spanning from 2020 to 2025, including initiatives like Predictive Maintenance for on-road Vehicles, AISN – AI Secured Networks, and various projects focused on statistical models, data analytics, and machine learning. He actively supervises PhD students including Alberto Verna, Ali Yassine, and Giordano Paoletti, whose research covers privacy on the Internet, analyzing online social networks, and implications for cybersecurity and misinformation. Dr. Vassio is actively involved with the DBDM - Database and Data Mining Group and the TNG research group at DAUIN. His laboratory work focuses on practical applications of data science to real-world network problems, with particular emphasis on security applications and social network analysis. His research has practical implications for industry partners working on network security, traffic analysis, and social media monitoring systems.
Mark W. Patton is a Senior Lecturer in the Department of Management Information Systems at the University of Arizona and serves as Program Administrator for the AZSecure Cybersecurity Program. His expertise spans cybersecurity, security informatics, and decision support systems. PhD in Management Information Systems (University of Arizona, 2009) MBA (University of Michigan, 1999) BS in Mining Engineering and Computer Science (Montana Tech of the University of Montana, 1990) His research focuses on cybersecurity and security informatics, particularly in automated deception identification, SCADA vulnerabilities, and enterprise security management. He has contributed to studies on Tor networks, IoT vulnerabilities, and AI-driven cybersecurity frameworks. Mark's publications highlight his work in cybersecurity analytics, network reconnaissance, and AI-based deception detection systems. His recent work addresses SCADA vulnerabilities, honeypot technologies, and dark web marketplaces. He is affiliated with the Artificial Intelligence Laboratory at the University of Arizona and has developed kiosk-based systems for deception detection and network security analysis.
Marco Mulas is an Associate Professor at the Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia. He teaches courses including Landslide Risk Assessment and Mitigation , Geothematic Surveying and Cartography , and Applied Geology for Civil and Environmental Engineering, focusing on landslide dynamics, geomorphological mapping, and hazard modeling. His research spans landslide monitoring using UAV-RTK/LiDAR, GNSS arrays, InSAR, and Digital Image Correlation. Key projects include the SoLoMon framework for regional landslide monitoring and development of unconventional Micropiles Tripods Shields for earthflow control. He specializes in rainfall-landslide thresholds, groundwater contamination modeling, and multi-temporal displacement analysis. Recent publications (2025-2016) cover topics like high-frequency UAV surveys (Baldiola landslide), effective rainfall impact on flysch landslides, debris flow hazard zonation, and structural analysis of rockfall precursors via sinusoidal wave fitting. His work emphasizes integrating field surveys with advanced geospatial datasets for hazard assessment. Contact: marco.mulas@unimore.it | Office: via G. Campi, 103 - Modena
Dr. Harry Agius is a Senior Lecturer in Computing at Brunel University, affiliated with the Creative Computing Research Group and Institute of Digital Futures under the College of Engineering, Design and Physical Sciences. His expertise spans digital media, games, and creative computing, with a focus on AI-driven personalization and immersive experiences. Research interests include user-centered artificial intelligence , graphical asset generation , MPEG-7 metadata , and collaborative gaming . His work bridges AI, digital media, and human-computer interaction, with recent articles examining intelligent game asset frameworks and evaluation metrics for AI-generated content. Teaching areas encompass digital experiences , emerging technologies , and responsive web development . He serves as Section Editor for Track 4 (Digital Games, VR/AR) in Multimedia Tools and Applications and co-edited the Handbook of Digital Games (IEEE/Wiley, 2014). His lab affiliations include the Creative Computing Research Group and Institute of Digital Futures , and he collaborates with researchers like Dr. Damon Daylamani-Zad and Prof. Marios Angelides.
Iván Martínez Ortiz is an academic at Complutense University of Madrid's Faculty of Computing, part of the Software Engineering and Artificial Intelligence Department. His work focuses on serious games, learning analytics, and educational technology. He has contributed to projects like Conectado , a serious game addressing bullying and cyberbullying, validated through extensive learning analytics research. His research emphasizes standards-based systems, such as IMS and xAPI-SG, to streamline serious game deployment and assessment. Notable contributions include integrating game analytics with data science to improve educational outcomes and designing infrastructure for web applications and cybersecurity training environments. He collaborates widely, publishing in journals like Journal of Learning Analytics and IEEE Transactions on Learning Technologies . His research interests span serious games , game-based learning , and data-driven educational assessment . Projects like UAdventure and Simva demonstrate his technical focus on game development tools and validation frameworks. Recent work explores automation in academic tracking systems and narrative-driven educational interventions. Key collaborations include projects on cyberbullying prevention, first aid training simulations, and cloud-based laboratory environments for web development education. His interdisciplinary approach bridges computer science with pedagogical innovation, aiming to enhance both teaching methodologies and student engagement through technology.
Tess Prendergast is a Lecturer at the UBC School of Information (iSchool) since 2019, where she teaches courses in librarianship and children’s literature. With over two decades of experience as a children’s librarian in urban public libraries, her work focused on early literacy support for diverse families, particularly newcomers to Canada. PhD research: Inclusion of children with disabilities in early learning through bioecological systems perspective Teaching expertise: Picture book evaluation as cultural barometers Key research areas: Inclusive library services, Indigenous and refugee children’s representation in literature Her publications and conference presentations emphasize anti-bias and anti-ableist approaches to library services, with a focus on early learning in multicultural contexts and the role of librarians in addressing systemic barriers.
Alaa Nehme is an Assistant Professor of Information Systems at Mississippi State University's College of Business. He holds a Ph.D. from Iowa State University and an MBA and B.S. in Computer Science from Lebanese American University. His research focuses on information security, IT threats, and IS/social issues, with publications in top journals like JMIS and Computers & Security. He teaches Data Analytics, Cybersecurity, and Management Information Systems at both graduate and doctoral levels. Dr. Nehme's scholarly contributions include work on password manager adoption, cybersecurity communication fatigue, and smart home security. He actively serves as an associate editor for ECIS 2025 and has chaired tracks at MENA and Mediterranean conferences. His teaching evaluations highlight his effectiveness in applying real-world examples and project-based learning. He has reviewed for major IS journals/conferences and contributed to NSF grant advisory boards. His service includes program committee roles for EuroUSEC, HICSS, and others. He maintains a personal website at https://www.alaanehme.com/.
Dr. Eng. Marcin Markowski is a researcher at the Department of Computer Systems and Networks, Faculty of Computer Science and Telecommunications, Wrocław University of Science and Technology. His work focuses on computer network design, optimization, and security, with an emphasis on cloud computing, elastic optical networks, and distributed systems. Faculty: Computer Science and Telecommunications Department: Computer Systems and Networks Email: marcin.markowski@pwr.edu.pl His research spans network optimization algorithms (ant colony, tabu search), industrial IoT applications, and security protocols. Articles demonstrate expertise in WAN-based resource allocation, SDN laboratory development, and sustainable logistics through WiFi-based monitoring systems. Key trends in his publications include heuristic methods for elastic optical networks, multi-criteria replica placement in wide area networks, and cloud computing efficiency analysis. He integrates algorithmic innovation with practical applications in industrial and telemedicine contexts. The Software Defined Networking Research Laboratory at WUST features prominently in his experimental work on network topologies and scenarios. No explicit information is available on teaching roles, awards, or grants.
Javier Pastor Galindo is a researcher at the University of Murcia's Department of Information and Communications Engineering, affiliated with the Faculty of Informatics. He holds B.Sc., M.Sc., and Ph.D. degrees in Computer Science from the same institution. His roles include FPU-MECD Predoctoral Researcher (2019–present) and later postdoctoral researcher, specializing in cybersecurity, cyberintelligence, and disinformation analysis. He leads projects like DEFENDER (cybersecurity in IoT/5G labs), CDL-TALENTUM (cybersecurity talent development), and EUCINF (EU cyber warfare tools). Education: PhD in Computer Science (in progress), University of Murcia MSc in New Technologies on Computer Science (2019), specialization in Networks and Telematics BSc in Computer Science Engineering (2018), specialization in Information Technologies Research Interests: Focus on OSINT, cyber defence, disinformation detection, and social media analysis. His work spans frameworks for bot detection (e.g., BOTTER), Tor network studies, and NLP-based threat analysis. He emphasizes practical applications, such as the INDRA Cyber Range training platform. Awards: Recipient of the prestigious FPU Predoctoral Grant (2019), Research Initiation Grant (2018), and academic distinctions for his thesis work on SDN and TLS security. His research aligns with EU and national defense initiatives, addressing critical cybersecurity challenges. Grants & Projects: Involved in high-budget projects (e.g., EUCINF: €41M, EU-GUARDIAN: €13.5M), focusing on AI-driven cyber defence automation and European cyber resilience. Collaborates with entities like INCIBE and the European Defence Fund. Labs & Teams: Part of the CyberDataLab UMU, a hub for cybersecurity and data science R&D. Engages in interdisciplinary efforts, such as the COnVIDa pandemic data dashboard.
Adrian ALEXANDRESCU is an Associate Professor at the Department of Computer Science and Engineering within the Faculty of Automatic Control and Computer Engineering at “Gheorghe Asachi” Technical University of Iași. He is a member of the Open Infrastructure Research Center and specializes in interdisciplinary research areas such as blockchain technology, distributed systems, artificial intelligence (genetic algorithms, neural networks), and IoT applications. His work bridges theoretical computer science with practical implementations in education, healthcare, and smart technologies. His research interests focus on leveraging blockchain for secure transactions, optimizing distributed systems, and enhancing e-learning through gamification. He has contributed to projects involving sensor networks for health monitoring, real-time driver sobriety tracking, and decentralized identity management systems. His academic contributions span over 20 years, with notable work on genetic algorithms for task mapping in heterogeneous systems and cloud-based solutions for ambient assisted living. Dr. ALEXANDRESCU’s publications emphasize blockchain’s role in trustless systems, IoT-driven healthcare environments, and AI-driven solutions for education and logistics. His work on decentralized article retrieval systems and plagiarism detection frameworks underscores his commitment to ethical and efficient digital ecosystems. Despite no explicitly listed awards, his prolific publication record reflects sustained academic excellence. He advises on projects at the intersection of cloud computing, distributed architectures, and smart technologies. His labs and collaborations focus on developing scalable solutions for real-world challenges such as secure real estate transactions and community-driven academic publishing systems.
J. Scott Christianson is an Associate Teaching Professor in the Management Department and Director of the Center for Entrepreneurship and Innovation at the University of Missouri’s Robert J. Trulaske, Sr., College of Business. He specializes in emerging technologies, project management, and educational innovation, with a focus on integrating AI, blockchain, and IoT into curricula. Christianson has held faculty roles since 2014 and previously owned Kaleidoscope Consulting (1998–2019), a firm specializing in videoconferencing solutions. Education: MA in Education and Human Development from The George Washington University (1999) and BA in Biology from the University of Missouri (1991). Research & Teaching: Develops courses on management information systems, entrepreneurial ventures, and digital transformation. His work emphasizes critical thinking about technologies like blockchain and AI, and he has authored textbooks and numerous articles on these topics. Awards: Multiple teaching honors including the Raymond O’Brien Award (2017), Distance Learning Leadership Award (2009), and Top 20 Under 40 (2007). Recognized for contributions to edtech, including pioneering work in interactive television and videoconferencing. Grants & Leadership: Secured grants for integrating clinical simulations into courses and improving project management education. Served on boards such as the State Technical College of Missouri and Boone County Industrial Development Authority. Active in community initiatives like broadband planning and K–12 technology advocacy. Publications: Over 100 works, including books on certification, project management, and educational tech, plus peer-reviewed articles in vision science and computer security. Regular contributor to media discussions on AI, cryptocurrency, and digital ethics.
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.
Yuri Vershinin is an Assistant Professor in the CEES School of Engineering at Coventry University, UK. He joined in 2000 after industrial roles in digital/analog systems design and control systems. His research focuses on Intelligent Transport Systems (ITS), autonomous vehicles, smart cities, and adaptive control systems . He leads the ITS&T Applied Research Group , working on automotive communication protocols (e.g., CAN-Open), GNSS navigation, and autonomous vehicle testing. Teaching: He developed unique modules like Intelligent Transport Systems (2006) and Telematics (2009) , and taught courses in control engineering, avionics, and microprocessor systems. He designed practical labs using GPS, CAN-bus, and MIL-STD-1553 systems, tested on real vehicles like the Peugeot-206 at Bruntingthope racing track. Research & Professional Activities: He organized international conferences (e.g., IEEE ITSC 2014–2022) and contributed to EU-funded projects (e.g., DIONICOS). His work includes remote lab systems, emergency evacuation simulations, and automotive diagnostic tools. He is a Visiting Professor at MSRSAS, Bangalore, and a reviewer for EPSRC grants. Awards: Received the 2019 Prize for A Web-based Interactive Remote Laboratory . He holds Fellowships from the Higher Education Academy and British Computer Society, and is a Chartered Engineer (CEng). Advising: Supervised 10 PhD students, 80 MSc projects, and 180 undergraduate projects. Active in promoting sustainable development goals related to smart transport and energy systems.
