Faezeh Ensan is an Assistant Professor at Toronto Metropolitan University, specializing in Information Retrieval, knowledge engineering, and data science applications in software engineering. She holds a B.Sc. from the University of Tehran (2004), M.Sc. from Ferdowsi University of Mashhad (2006), and Ph.D. from the University of New Brunswick (2011). Her research focuses on semantic technologies, ad hoc retrieval systems, and ontology evaluation. B.Sc., University of Tehran, 2004 M.Sc., Ferdowsi University of Mashhad, 2006 Ph.D., University of New Brunswick, 2011 Her work bridges semantic web, machine learning, and information systems, with notable contributions to entity-based retrieval and modular ontology evaluation. She has been funded by NSERC, Mitacs, and ACOA, and has held prestigious fellowships including the NSERC Industrial Research Fellowship (2014-2016). Recipient of NeOn Student Prize for Best Paper at EKAW 2008 Editor of Canadian Semantic Web: Technologies and Applications (2010) Her advising and grants include collaborations with industrial partners through NSERC and Mitacs projects. She teaches courses like COE528 and COE848, emphasizing object-oriented engineering and data engineering fundamentals.
Darshika G. Perera is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Colorado Colorado Springs (UCCS). Her research focuses on FPGA-based hardware acceleration, neuromorphic computing, and embedded systems optimization with applications in machine learning, cryptography, and battery management systems. She holds a PhD and has extensive experience in designing reconfigurable architectures for compute-intensive tasks. Her work bridges theoretical algorithms with practical hardware implementations, emphasizing efficiency and real-time performance. Key research areas include FPGA design methodologies, neuromorphic hardware for AI applications, and embedded systems security. She has published widely on topics such as hardware-software co-design for edge computing, optimization algorithms for genomics, and blockchain applications in healthcare IoT. Her contributions also span data mining hardware accelerators and dynamic reconfiguration techniques for cryptographic systems. Dr. Perera’s work is characterized by interdisciplinary collaborations, combining principles from electrical engineering, computer science, and applied mathematics. She is committed to advancing next-generation edge-computing platforms through innovative architectures and methodologies.
Emmanuel Giguet is a Researcher at the French National Centre for Scientific Research (CNRS), affiliated with the GREYC Laboratory (Computer Science Department) at the University of Caen, Normandy, France. He holds an HDR (Accreditation to Supervise Research) from the University of Caen (2011) and a PhD in Computer Science (1998), both focusing on multilingual natural language processing and document analysis. Roles: Cybersecurity Researcher, Communication and Scientific Mediation Adviser (GREYC Lab), Former Computer Forensics Legal Expert (2005–2015). Expertise: Digital Forensics, Natural Language Processing, Document Structure Analysis, Open Source Intelligence, Competitive Intelligence. His research spans cybersecurity, digital forensics, and NLP applications in document analysis. He co-founded Semiotime (2012), a Competitive Intelligence startup, and has contributed to tools like the GREYC Digital Investigation Platform (G'DIP). He teaches cybersecurity modules at the University of Caen, emphasizing digital forensics and information retrieval. Key Projects: Development of open-source digital investigation tools (e.g., G'DIP). Analysis of deepfake videos and forensic video forgery detection. PDF document structure extraction for financial narrative processing (FinTOC). Affiliations: GREYC Lab (CNRS UMR 6072), University of Caen. Institute for Information Sciences, University of Caen. Communication: Advises GREYC on branding and media presence, including logo guidelines, virtual backgrounds, and scientific mediation resources.
Yang Lei is an academic affiliated with the University of Melbourne's Department of Computing and Information Systems. Their research focuses on knowledge graphs, FAIR data principles, large language models (LLMs), and ontology engineering. They contribute to initiatives like the Open Research Knowledge Graph (ORKG) and NFDI4DataScience, emphasizing reproducibility, scholarly metadata, and systematic literature reviews. Recent work includes applications of LLMs for abstract summarization, leaderboard extraction, and entity recognition in scholarly documents. Yang also explores challenges in FAIR Digital Objects, machine-actionable workflows, and interoperability in research data management.
Vuk Gajić is an Assistant Professor at the Faculty of Applied Ecology, Singidunum University, where he has held academic roles since 2016. His career progression includes positions as a teaching associate (2016), assistant (2019), and current role (2023). He earned a Ph.D. in Environment and Sustainable Development from Singidunum University (2019–2022), following prior studies in environmental protection and risk management at the same institution. Research interests span environmental science, sustainable development, GIS applications, and radiation technology for waste and food treatment. He has contributed to interdisciplinary studies, including soil contamination analysis in Libya, microbial decontamination via ionizing radiation, and machine learning applications for software defect prediction and agricultural weed detection. His work bridges environmental engineering with technological innovation, emphasizing sustainability and ecological conservation. Publications reflect a focus on environmental monitoring, pollution assessment, and eco-technologies. Key themes include GIS-based environmental databases, forest fire prevention through sensor networks, and agricultural waste reuse. His research often integrates quantitative methods with geospatial tools, addressing both local and global environmental challenges. Teaching responsibilities include courses on geodiversity, sustainable development, and natural hazards. He actively participates in academic conferences, contributing to peer-reviewed journals and presenting at events like Sinteza and SETI. Current projects likely explore emerging technologies in environmental management and sustainable practices.
Nataša Stanišić is an academic at Singidunum University affiliated with the Faculty of Business and Department of Management and Business. She holds a Doctorate in Management and Business (2021), Master's in Financial Management from Lincoln University (2006-2008), and a Bachelor's in English Language and Literature from Faculty of Philology (1999-2005). Her research focuses on hospitality industry dynamics, employee motivation frameworks, sustainable tourism development, and human resource management strategies. Key research interests include applying behavioral theories in workplace environments, analyzing labor market trends in Serbia, and exploring blended learning methodologies in tertiary education. She has contributed to studies on employer branding in IT sectors and the impact of pandemic disruptions on tourism industries. Her recent work highlights innovations in HR practices for agile cultures, competency modeling in hospitality sectors, and evaluating translation technologies. She has co-authored over 15 papers presented at international conferences like Sinteza and SITCON, addressing topics ranging from slow tourism concepts to collaborative web development pedagogy. No scientific awards are listed in the provided materials. Her academic contributions include curriculum development for business education and cross-disciplinary research bridging technology adoption with organizational behavior.
Maura R. Grossman is a Research Professor at the University of Waterloo, specializing in High-Recall Information Retrieval, AI ethics, and legal technology. Her work focuses on ensuring comprehensive information retrieval in high-stakes contexts like electronic discovery in law, healthcare data curation, and medical evidence synthesis. She explores the intersection of artificial intelligence and legal systems, particularly addressing challenges posed by AI-generated evidence and deepfakes in judicial processes. Education: J.D. (Georgetown University Law Center, 1999), Ph.D. (Adelphi University, 1984), M.A. (Adelphi University, 1982), A.B. (Brown University, 1980). Research interests include AI accountability in courts, responsible data science practices, and improving electronic discovery methodologies. Recent work analyzes AI’s role in legal proceedings, ethical AI frameworks, and healthcare data governance. Her publications emphasize validating technology-assisted review (TAR) systems and evaluating generative AI impacts on marginalized communities. Her articles highlight trends in AI’s legal implications, healthcare data sharing protocols, and the need for transparent algorithmic systems in justice contexts. She contributes to TREC tracks, advancing high-recall retrieval techniques for legal and medical document analysis. Notable projects include developing frameworks for unbiased health data sharing and analyzing AI’s effects on marginalized writers. Her work underscores interdisciplinary collaboration between law, computer science, and healthcare to address emerging technological challenges.
Stephan Schlögl is a Full Professor at MCI - The Entrepreneurial School in Austria, leading research and teaching in Human-Computer Interaction (HCI), Artificial Intelligence (AI), and Information Systems. He holds editorial roles at journals like the Springer Discover Artificial Intelligence Journal and MDPI Multimodal Technologies and Interaction Journal. His work spans over two decades, with key roles including Postdoctoral Research Fellow at Télécom ParisTech (2012–2013) and PhD Researcher at Trinity College Dublin (2008–2012). Schlögl’s research focuses on HCI, AI-driven conversational systems, and assistive technologies for aging populations. Education includes a PhD in Computer Science from Trinity College Dublin, an MSc in Human-Computer Interaction from University College London, and a Mag.(FH) in Applied Informatics & Management from MCI. His teaching spans Software Engineering, Business Intelligence, and Research Methods. Research interests emphasize natural language interfaces, AI ethics, and technology’s societal impact. Notable projects include the EU-funded EMPATHIC initiative (2017–2021), developing an empathic virtual coach for elderly care, and the CRYSTAL project (2024–present) on conversational systems for emotional support. Schlögl has supervised numerous theses on AI applications, chatbots, and UX design. He co-organized major conferences like CUI (Conversational User Interfaces) and received awards for best papers in AI-HCI and CHIRA. His work bridges academia and industry, addressing challenges in AI adoption, digital well-being, and ethical technology design.
Dr. Naeha Sharif is a Lecturer in Computer Science & Software Engineering at The University of Western Australia (UWA), specializing in Computer Vision (CV) and Natural Language Processing (NLP). She holds a PhD from UWA (2021) focused on AI-driven image captioning and received the prestigious ACS 1962 Medal for outstanding IT/CS research. Her work bridges AI with healthcare, including automated medical assessment via spine scans (DXA) for abdominal aortic calcification analysis and AI-driven medical report generation for fundus imaging. Education: PhD in Computer Science (UWA 2021), Master of Engineering in Biomedical Engineering (Kyung Hee University, 2013). Previous roles include Postdoctoral Fellow at Edith Cowan University (2021–2022). Research Interests: Vision-language models, medical image analysis, captioning metrics, multimodal learning, and AI applications in healthcare. Active in UN SDGs related to health and innovation. Teaching: Unit Coordinator for Computer Graphics & Animation (CITS3003, 2022–2023) Computational Thinking with Python (CITS1401, 2023) Grants: Lead investigator on the 'Generative AI for Screening of Depressive Disorders' project (2024). Awards: Recognized for student learning contributions (2025), best paper awards (2024/2020), and academic excellence honors (2021/2020). Labs/Teams: Member of UWA Natural & Technical Language Processing Group and IEEE Signal Processing Society.
Robert Dale is an Honorary Professor at the School of Computing, Macquarie University. His research focuses on Natural Language Processing (NLP), with significant contributions to automated writing assistance, legal technology applications, and NLP commercialization. He has led projects such as 'Beyond the Grammar Checker: Automated Copy-Editing Assistance' (2013–2019) and 'Natural Language Generation for Aboriginal Languages' (2010–2016). His work spans computational linguistics, text generation, and legal sector applications of NLP. Key research interests include NLP systems, legal tech integration, and industry adoption trends. Recent publications analyze the landscape of automated writing tools, NLP APIs, and commercialization strategies. His projects emphasize interdisciplinary collaboration, addressing challenges in language technology and real-world applications. Robert has advised on multiple research initiatives, including ARC-funded projects, and collaborates internationally on NLP applications. He has contributed to over 159 research outputs since 1990, with a focus on advancing NLP's practical utility across sectors.
Prof. Dr. Peter Buxmann is a full professor of business informatics at the Technical University of Darmstadt, holding the Chair in this field. He is an internationally renowned speaker, senior business advisor, and podcaster for the Frankfurter Allgemeine Zeitung. His roles include advisory board memberships for institutions like the Weizenbaum Institute for the Networked Society and Eckelmann AG. His research focuses on AI applications, digital transformation, and future work paradigms, with over 300 publications in top journals and conferences. Education: PhD and habilitation from University of Frankfurt, including a research stay at UC Berkeley's Haas School of Business. Previous positions: Professor at Technical University of Freiberg (2000-2004). Research Interests: Artificial Intelligence (applications in business, healthcare, and ethics), Digital Transformation (organizational and societal impacts), Data-Driven Business Models (platform economics, innovation ecosystems), and Future of Work (human-robot collaboration, agile principles). Keynote Topics: Generative AI and its industry applications Strategic digital transformation frameworks Ethical AI governance Labs/Teams: Leads the HIGHEST innovation center at TU Darmstadt and collaborates with TechQuartier Frankfurt. Founded multiple startups focusing on AI solutions.
Simon Foster is a Senior Lecturer in the Department of Computer Science at the University of York. His research focuses on formal methods, theorem proving (using tools like Isabelle/HOL and Agda), and the verification of cyber-physical systems. He holds a PhD and MComp from the University of Sheffield. Research Interests: Foster specializes in formal semantics, unifying theories of programming, and functional programming. His work addresses challenges in verifying complex systems, including robotic control software and safety-critical applications. He has contributed to projects like CyPhyAssure and RoboCalc, emphasizing assurance case generation and probabilistic modeling. Recent Work Trends: His recent publications (2022–2025) emphasize scalable verification techniques for cyber-physical systems, probabilistic modeling, and formal verification of robotic systems using Isabelle/HOL. Key themes include hybrid systems theorem proving, assurance case automation, and the integration of formal methods with robotic state machines. Grants & Projects: He led the CyPhyAssure project (2018–2021) and contributed to the H2020 INTO-CPS initiative. His roles include Research Fellowships in safety-critical systems and model-driven architectures. Labs & Teams: Active in the High Integrity Systems group at York, focusing on formal methods for safety-critical systems and collaborative tool development for systems engineering.
Barry Smith is a SUNY Distinguished Professor of Philosophy at the University at Buffalo, holding the Julian Park Chair in the Department of Philosophy. He also serves as Director of the National Center for Ontological Research (NCOR) and maintains affiliate appointments in Biomedical Informatics and Computer Science & Engineering. With joint appointments across multiple departments, Smith is a leading figure in the field of applied ontology and its applications across disciplines. Smith received his PhD in Philosophy from the University of Manchester in 1976, following MA and BA degrees in Mathematics and Philosophy from Oxford University. His educational background reflects his interdisciplinary approach that bridges philosophy, mathematics, and computer science. Smith's research focuses primarily on applied ontology, with significant contributions to biomedical informatics, artificial intelligence, and philosophy of science. His work has established foundational frameworks that enable data integration and knowledge representation across multiple domains. He has pioneered the development of Basic Formal Ontology (BFO), which has become the most widely adopted top-level ontology framework and was approved as an ISO standard (ISO/IEC:21838-2). His research has significantly influenced the Open Biomedical Ontologies (OBO) Foundry, a suite of interoperable ontology modules supporting biology and biomedicine research. Smith's publications over the past five years demonstrate a consistent focus on the applications of ontology to pressing scientific challenges, particularly in biomedical domains (including COVID-19 research), artificial intelligence limitations, and knowledge representation. His work spans theoretical developments in formal ontology while maintaining strong practical applications in real-world information systems. Wolfgang Paul Award of the Alexander von Humboldt Foundation (2002) Paolo Bozzi Prize in Ontology (2011) Fellow of the American College of Medical Informatics (FACMI) (2013) Smith has supervised numerous graduate students and postdoctoral researchers, contributing to the development of a new generation of ontologists. His research has been supported by major funding agencies including the National Institutes of Health, National Science Foundations of the US, Switzerland and Austria, the Volkswagen Foundation, the European Union, and the US Department of Defense. Since 2000, he has served as a consultant to Hernando de Soto on projects related to property and business rights among the poor in developing countries. As Director of the National Center for Ontological Research, Smith leads a team focused on advancing ontological methods and applying them to diverse domains including biomedical informatics, defense intelligence, and industrial engineering. His work continues to shape how we represent and integrate knowledge across disciplinary boundaries.
Bowen Xu is an Assistant Professor in the Department of Computer Science at North Carolina State University (NC State), College of Engineering. His research focuses on software engineering, machine learning, and program analysis, particularly in securing AI models and improving code quality. He holds a PhD from Singapore Management University (SMU), where he also conducted postdoctoral research. Education: PhD in Computer Science, Singapore Management University (SMU) Postdoctoral Researcher, SMU School of Computing and Information Systems Research Interests: AI for Code, Backdoor Attacks on Code Models, Vulnerability Detection Code Representation Learning, Model Compression, Safety of AI Systems Chatbot Development for Developers, Automatic Code Review Key Contributions: Developed PTM4Tag+, a Stack Overflow tag recommendation system using pre-trained models Explored stealthy backdoor attacks in code and reinforcement learning systems Pioneered work on automatic vulnerability repair using LLMs and broader input analysis Awards: 2022: Honorable Mention Award (ACSAC) 2018: Highly Commended Full Paper Award (ESEM) Service Roles: Editorial Board Member, Empirical Software Engineering Journal Program Committee Co-chair for ICSE/FSE Research Tracks Organized workshops like FORGE, MaLTeSQuE, and SEA4DQ Labs & Teams: Leads the Softmax Lab at NC State, advising 12+ students across PhD, Master's, and undergraduate levels. Alumni include industry professionals at Microsoft, Barclays, and Marvell Semiconductor.
Fred Popowich is a Professor in the School of Computing Science at Simon Fraser University (SFU), Canada. He holds adjunct positions at Dalhousie University's Faculty of Graduate Studies and is an Associate Member of SFU's Department of Linguistics and Cognitive Science Program. His academic career began post-PhD (Cognitive Science/Artificial Intelligence, University of Edinburgh, 1989) and has spanned over three decades at SFU. Education: PhD in Cognitive Science/Artificial Intelligence (University of Edinburgh, 1989); M.Sc. and B.Sc. in Computing Science (Simon Fraser University and University of Alberta, 1985/1982). Research focuses on natural language processing (NLP), machine translation, intelligent systems, and big data applications. He directs SFU’s Big Data Initiative and leads the Natural Language Laboratory, supervising MSc/PhD students in computing science. His work includes developing systems for smart homes, toxic language detection in social media, and energy grid analysis. Industry roles include co-founding Axonwave Software (as CTO/President) and contributing to technology commercialization. Current projects address EV charging impacts, personalized learning systems, and real-time load monitoring. Publications span machine translation, sentiment analysis, and NLP applications in education and energy systems. His work bridges theoretical computer science with practical applications in healthcare, smart cities, and education.
