Professor Ihab Ilyas is a leading figure in data management and machine learning at the Cheriton School of Computer Science , University of Waterloo , where he holds the Thomson Reuters Research Chair in Data Quality . He is currently on leave from the university, serving as a Distinguished Engineer, Proactive Intelligence at Apple Inc . His research focuses on data cleaning , large-scale data integration , knowledge graphs , and machine learning applications in data quality . He has pioneered systems like HoloClean and Saga , with commercial impacts through co-founded startups Inductiv (acquired by Apple) and Tamr . PhD in Computer Science from Purdue University Co-founder of Inductiv (acquired by Apple) Co-founder of Tamr Research Interests include: Probabilistic and uncertain data management Machine learning for data quality and enrichment Big data systems and information extraction Knowledge graph construction and optimization Scientific Awards and Recognitions include: Fellow of the Royal Society of Canada (2024) C.C. Gotlieb Computer Award (2024) IEEE Fellow (2021) ACM Fellow (2020) Cheriton Faculty Fellowship (2013-2016) Ontario Early Researcher Award
Philip S. Yu is a Distinguished Professor in the Department of Computer Science at the University of Illinois at Chicago and holds the Wexler Chair in Information Technology. Previously, he led the Software Tools and Techniques department at IBM Thomas J. Watson Research Center. Education: B.S. in Electrical Engineering, National Taiwan University M.S. and Ph.D. in Electrical Engineering, Stanford University M.B.A., New York University His research spans data mining , big data , social networks , privacy-preserving data publishing , graph/network mining , recommender systems , and deep learning . He has authored over 970 papers with 74,500+ citations and an H-index of 127. Recent work focuses on heterogeneous graph representation, quantum walks in network analysis, and federated unlearning. Scientific Honors: ACM SIGKDD 2016 Innovation Award IEEE Computer Society 2013 Technical Achievement Award IEEE ICDM 2003 Research Contributions Award IEEE Region 1 Award (1999) UIC Research of the Year (2013) IBM Master Inventor with 300+ patents AI 2000 Most Influential Scholar Honorable Mentions (2024-2025) He served as Editor-in-Chief for ACM Transactions on Knowledge Discovery from Data and IEEE Transactions on Knowledge and Data Engineering , and on steering committees for ACM KDD and IEEE Data Mining. His work bridges theoretical advances in graph neural networks , deep learning , and privacy-preserving systems with applications in healthcare, social media, and enterprise analytics.
Dr. Stan Ahalt serves as the inaugural Dean of the UNC School of Data Science and Society (SDSS) and holds a professorship in the Department of Computer Science at UNC-Chapel Hill. He previously directed the Renaissance Computing Institute (RENCI) and currently acts as its executive advisor. Additionally, he is the associate director of informatics and data science at NC TraCS, the translational research institute at UNC. His academic journey includes a 22-year tenure as professor of electrical and computer engineering at Ohio State University and leadership roles at the Ohio Supercomputer Center. Ahalt’s research focuses on applying data science to societal challenges such as healthcare, climate, and judicial reform. Key initiatives include the National Consortium for Data Science and the iRODS project, which advanced enterprise data management systems. Ahalt has secured over $34.5M in grants to lead high-impact projects like the NHLBI BioData Catalyst (unifying biomedical data), the NCATS Translator (accelerating clinical discovery), and the NIH HEAL Initiative (ensuring FAIR data standards). He mentors students across doctoral and master’s programs, teaching data science fundamentals in courses like COMP 116: Introduction to Scientific Programming. His work emphasizes interdisciplinary collaboration, evidenced by roles in RENCI, NC TraCS, and the SDSS. Ahalt’s contributions span cyberinfrastructure development, educational innovation, and translational research, positioning UNC as a national leader in data science.
Dr. Muhammad Umar Farooq is a Lecturer and Module Director at York St John University's London Campus , specializing in Business, Marketing, and Project Management education for postgraduate students. He joined the university in 2022 and previously held roles as an Associate Lecturer at the University of West London, while also contributing to teaching and supervision at the University of East London and Regent’s University London. He holds a Doctorate in Business Administration (DBA), an MBA, and a Postgraduate Diploma in Leadership and Strategy, coupled with the prestigious Fellow of the Higher Education Academy (FHEA) distinction. His research focuses on digital marketing, SME innovation, AI applications in content creation, and project management strategies. Notable areas include generative AI for SME competitiveness, sustainable lean practices in construction, and agile methodologies in software development. He actively contributes to academic governance as an external examiner at Northumbria University and the University of Huddersfield. Teaching modules include Marketing Communication , Digital Marketing Strategy , Strategic Project Management , and Applied Research Project . His work bridges academic rigor with industry insights, emphasizing practical applications for organizational success. Research Awards: Recognized as FHEA. Professional Contributions: External examiner roles, LinkedIn engagement, and RaY Postgraduate Research supervision.
Dr. Jeewanie Jayasinghe Arachchige is a Lecturer in the Department of Computer Science at Vrije Universiteit Amsterdam, Faculty of Science. She teaches undergraduate courses including Bachelor Project Computer Science, Professional Development, and Software Engineering Processes for the academic year 2024–2025. Her research focuses on process mining , healthcare informatics , and data security . She applies process mining to analyze healthcare pathways and subpopulation treatment variations, develops explainable AI frameworks for predictive analytics, and examines data governance in emerging architectures like Data Lakehouses. Her work intersects legal informatics, particularly formalizing Sri Lankan civil court processes using ontology engineering. Recent publications highlight trends in balancing simplicity and complexity in process modeling, Industry 4.0 healthcare applications, and cybersecurity in model-driven web development. She has contributed to over 20 peer-reviewed articles since 2006, spanning topics from service-oriented architectures to value network analysis. Her teaching and research emphasize practical applications of IT in healthcare, legal systems, and enterprise environments. No ancillary activities are currently recorded.
Dr. Sirui Li is a Lecturer at Murdoch University's School of Information Technology within the College of Science, Technology, Engineering and Mathematics. Her research focuses on Artificial Intelligence, Natural Language Processing (NLP), Machine Learning, Knowledge Graphs, Data Analysis, Temporal Data, and Multi-modal Models, with applications in medicine, agriculture, and mining. She collaborates with industry partners like BHP and has published in journals such as Food Chemistry and Knowledge and Information Systems , as well as conferences like ICSME and IJCNN. Education: Bachelor of Advanced Computing (Honours) in Computer Science at Australian National University Master of Computing (Specialising in AI) at ANU Ph.D. in Information Technology (AI) at Murdoch University Research interests include interdisciplinary applications of AI, such as clinical coding privacy solutions, disease spread modeling, and drug repurposing for pandemics. Her work emphasizes practical industry integration, demonstrated through awards like the 2024 EMNLP Best Demo Award and the 2023 Iron Ore Circuit Hackathon innovation prize. Professional roles include IEEE Western Australia Section committee membership, conference chair positions, and peer review for top journals. She actively mentors students pursuing Honours, Master's, or PhD projects in her areas of expertise.
Peter N. Belhumeur is a Professor in the Department of Computer Science at Columbia University and Director of the Laboratory for the Study of Visual Appearance (VAP LAB). He holds a Sc.B. from Brown University and a Ph.D. from Harvard University, followed by a postdoctoral fellowship at the University of Cambridge. His career includes roles at Yale University before joining Columbia in 2002. Education: Brown University (Sc.B., 1985), Harvard University (Ph.D., 1993) Postdoc: Isaac Newton Institute, University of Cambridge (1994) His research focuses on computer vision and machine learning, with applications in biodiversity and mobile technology. Notable projects include the Leafsnap, Birdsnap, and Dogsnap apps – pioneering species/breed identification tools using machine learning. He has received awards such as the PECASE, Helmholtz Prize, and EO Wilson Biodiversity Technology Pioneer Award. His work bridges academia and industry, demonstrated by collaborations with Dropbox and contributions to consumer-facing AI applications. The VAP LAB explores visual appearance modeling and computational photography.
Karl Michael Göschka is an Associate Professor at Vienna University of Technology (TU Wien) in the Department of Distributed Systems (E194-02) within the Faculty of Computer Science. His academic title of Privatdozent indicates he has completed habilitation, the highest academic qualification in the German/Austrian system. He maintains an active research and teaching profile with courses scheduled through 2026S, including Bachelor Thesis supervision, Computer Science Projects, and PhD Seminars. His research spans over two decades with consistent publications from 2004 to 2022. Göschka's primary research interests focus on Dependable Distributed Systems, Web Engineering, and the convergence of voice and data technologies. His work demonstrates particular expertise in middleware, service-oriented architecture, wireless sensor networks, and fault tolerance mechanisms. He has supervised numerous master's and diploma theses since 2006, with his most recent doctoral supervision completed in 2022. Göschka's publication record shows a clear evolution from foundational work in distributed systems and replication (2004-2013) to more recent contributions in wireless sensor networks and dependable computing (2020-2022). His research consistently addresses the challenge of balancing dependability, performance, and security in distributed environments, with notable contributions in temporal decoupling techniques and adaptive systems. GIT-Preis des Österreichischen Vereins für Elektrotechnik (1999) Würdigungspreis des Ministeriums für Wissenschaft und Forschung (1998) GIT-Förderpreis des Österreichischen Vereins für Elektrotechnik (1994) Göschka has led and participated in multiple significant research projects including TRADE (2008-2011) on adaptive performance optimization, COMPASS (2005-2007) for automotive software systems, S-Cube (2008-2012), ALL-TIMES (2007-2010), and DeDiSys (2004-2007) on dependable distributed systems. His research has strong practical applications in automotive systems, online auctions, and critical infrastructure monitoring.
Tan Chuan Hoo is an Associate Professor (tenured) and Deputy Head of the Department of Information Systems and Analytics at the National University of Singapore's School of Computing. With a distinguished academic career spanning multiple continents, he brings expertise in digital transformation, healthcare informatics, and enterprise systems to his teaching and research. His educational background includes: B.Sc. (1st Class Honours, National University of Singapore) M.Sc. (Accelerated, National University of Singapore) Ph.D. (National University of Singapore) Professor Tan's research focuses on digital transformation, particularly designing, deploying, and evaluating technological innovations. His work centers on two critical areas: digital commerce (provision of digital services such as online shopping aids) and digital organization (ensuring operational efficiency and performance). His research has significant implications for healthcare institutions, corporations, and crisis preparedness and response organizations. He conducts comprehensive analyses using various scientific methodologies including field experiments and mixed methods to understand how digital technologies reshape business operations and enhance societal well-being. His publication record shows a consistent focus on information systems, with recent articles (2020-2025) emphasizing healthcare informatics, digital transformation, and open innovation. His work demonstrates a clear trajectory toward understanding how technology intersects with organizational effectiveness and societal implications, with increasing attention to healthcare applications and digital crisis management. Professor Tan has received numerous prestigious awards for his contributions to the field: Faculty Teaching Excellence Award, NUS (2024, 2017) Information Management Research Award, China Information Economics Society (2023) Reviewer Hall of Fame, Journal of AIS (2020) Outstanding Associate Editor Award, MIS Quarterly (2016) Best Reviewer Award, Journal of AIS (2016) INFORMS ISS Design Science Award (2013) Honorable Mention, Journal of AIS (2015) He has successfully advised PhD students and collaborated with public and private entities on research projects. His editorial service as Associate Editor for Information Systems Research and MIS Quarterly, along with board memberships at other leading journals, demonstrates his significant influence in the field. Professor Tan has secured research grants supporting projects on digital crisis preparedness, disaster response technology, and healthcare digitalization. His research group focuses on understanding how technology can be designed and implemented to support organizations in crisis situations, enhance healthcare services, and improve digital commerce. Current projects include examining digital crisis management, technology for disaster response, and the digital transformation of healthcare services.
Stephen Meisenbacher is a Research Associate at the Technical University of Munich (TUM) , affiliated with the School of Computation, Information and Technology and the Department of Computer Science, I19 . He has been part of the Software Engineering for Business Information Systems (SEBIS) chair since March 2022. His research focuses on Privacy-Preserving Natural Language Processing (NLP) , Differential Privacy , and Privacy-Enhancing Technologies (PETs) , with a particular interest in their integration into software development and business applications. His work also explores Hybrid, Expert-Driven Classification Systems and Usable Privacy solutions. Stephen’s recent publications address trends in AI Privacy Risks , Text Rewriting with DP , Legal AI Use Cases , and Data Protection Compliance . He has contributed to GDPR-related research and PETs adoption in small enterprises. His teaching includes Natural Language Processing seminars and Software Engineering lecture courses for Master’s and Bachelor’s students at TUM. He also organizes Entrepreneurship for Small Software-Oriented Enterprises seminars. Stephen holds a Master’s in Informatics from TUM (DAAD Graduate Scholarship) and a Bachelor’s in Computer Science from the University of Notre Dame, with additional studies in German Language and Literature. Contact: stephen.meisenbacher@tum.de | LinkedIn
Luisa Domingues is an Assistant Professor in the Department of Information Science and Technology at ISCTE - University Institute of Lisbon. She serves as an Integrated Researcher at ISTAR-Iscte - Research Center in Information Sciences, Technologies and Architecture, specializing in Information Systems research. Her academic qualifications include a PhD in Information Science and Technology from ISCTE-IUL (2013). Her primary research interests focus on: Project Management : Methodologies, risk assessment, and knowledge sharing Database Systems : Management, interoperability, and standardization e-Government Solutions : Public sector information systems and shared services Ontological Frameworks : Particularly for architectural heritage documentation Educational Technologies : Blended learning approaches in higher education Her recent publications (2016-2024) demonstrate a strong focus on project management methodologies, knowledge transfer, and information systems in public sector contexts. Key thematic trends include PMBOK framework applications, agile methodology adoption challenges, data science project risks, and technological solutions for cultural heritage preservation. Most works employ case study research and empirical validation methods. Dr. Domingues maintains an active advising portfolio with 1 doctoral candidate and 36 master's students, primarily focusing on topics in project management, information systems, and data science applications. She has held significant academic leadership positions including: 4th Year Coordinator for Bachelor's in Computer Science and Business Management (2020-2027) Program Director for the same degree (2017-2019) At ISTAR-Iscte research center, she contributes to projects involving information systems architecture, data standardization, and knowledge management frameworks.
Dr Maria Bada is a Lecturer in Cyberpsychology at the School of Biological and Behavioural Sciences, Queen Mary University of London. She is an active researcher in the field of cyberpsychology with a specific focus on the human element of cybersecurity. Dr Bada is also a member of the committee of the Artificial Intelligence, Ethics and Society Group at QMUL. Dr Bada's research spans multiple critical areas in cyberpsychology and cybersecurity. Her primary research interests include: The effectiveness of cybersecurity awareness campaigns and factors leading to their success or failure in changing information security behavior Development of prevention activities to enhance the resilience of Small and Medium Enterprises (SMEs) against cybercrime Cybersecurity awareness initiatives for school learners in South Africa and the UK Youth delinquency and interventions to prevent cybercrime, in collaboration with the National Crime Agency and Home Office Social and psychological impacts of cyber-attacks on vulnerable groups Exploration of the cybercrime ecosystem, including cybercriminal profiles, pathways, and risk perceptions Dr Bada's publication record demonstrates a consistent focus on the intersection of psychology and cybersecurity. Her recent work shows increasing specialization in SME cybersecurity challenges, ethical considerations in security behavior change, and the psychological impacts of cybercrime on individuals and organizations. She frequently collaborates with researchers from diverse disciplines including computer science, criminology, and healthcare, reflecting the interdisciplinary nature of her work. Dr Bada has secured significant research funding for her work, including: "Enhancing national cyber resilience via SME cyber security and digital responsibility" (£328,119 from EPSRC, 2023-2026) "REPHRAIN: Supporting organisations in making effective privacy related decisions" (£50,801 from EPSRC, 2022-2023) "Assessing Organisational DSbD Awareness and Readiness" (£15,554 from ESRC, 2022-2024) She works closely with research staff including Dr Matthew Rand and collaborates with various UK government agencies including the National Crime Agency and Home Office on cybercrime prevention initiatives.
Michael J. Freedman is the Robert E. Kahn Professor of Computer Science at Princeton University and co-founder/CTO of Timescale. He received his Ph.D. from NYU’s Courant Institute and degrees from MIT. Current roles: Professor, Co-founder & CTO Affiliations: Princeton University, SNS Group, CITP Associate Education: Ph.D. (NYU), S.B./M.Eng. (MIT) His research spans distributed systems, networking, and security, with innovations like CoralCDN, DONAR, and Ethane. His work impacts decentralized content delivery, software-defined networking, and privacy-enhancing technologies. His recent publications address scalable fusion algorithms, GPU acceleration for data systems, and distributed GPU resource management. These works intersect with cloud infrastructure, network optimization, and security. Scientific honors include: Presidential Early Career Award for Scientists and Engineers (PECASE) Sloan Fellowship NSF CAREER Award Office of Naval Research Young Investigator Award Test of Time Award (Theory of Crypto Conference) ACM SIGOPS Mark Weiser Award He advises graduate students like Sam Ginzburg and Ashwini Raina, who joined Meta AI and Timescale post-PhD. His projects have secured substantial grants, including $110M Series C funding for Timescale. Key labs/teams: Princeton SNS Group Co-founder, Timescale (enterprise data platform) Co-founder, iobeam (IoT analytics, acquired by Timescale) Collaboration with FCC on Consumer Broadband Test Contributions to OpenFlow/SDN standardization
Zohreh Pourzolfaghar is an Assistant Professor in Management Information Systems (MIS) at the School of Business, Maynooth University (MU). She serves as Director of the IT-Enable Innovation Programme and cluster lead for the Digital Construction cluster at the Innovation Value Institute (IVI). She is also a member of Lero, the SFI Research Centre for Software. Education: PhD in Project Management (University Putra Malaysia, 2011); MSc in Management Systems and Productivity; BSc in Software Engineering. Research Interests : Focuses on digital transformation for SMEs, information management in construction, and smart city architectures. Leads EU-funded projects like EnTrust (agri-data governance), DIGI+ (sustainable digital transformation), and DigiFABs (food & beverage SMEs). Co-PI for projects such as GDI-IE (genomic data infrastructure) and PERFORM (digital retail innovation). Grants & Awards : Secured funding from SFI, Enterprise Ireland, and EU. Notable awards include the BIM Hero Award (2022) and Research Engaged Award (2022). Teaching : Courses include Digital Business, Digital Technology Governance, and Enterprise Architecture. Advises PhD students in MIS and digital transformation. Industry Collaboration : Works with firms like ArcDox and Corballis Technologies on BIM standards and data governance. Active in national and EU policy networks, including NSAI committees.
Elena Simperl is a Professor of Computer Science and Deputy Head of Department for Enterprise and Engagement at King's College London's Department of Informatics. She co-directs the King's Institute for Artificial Intelligence and serves as Director of Research for the Open Data Institute. As a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study, she leads the Trustworthy Knowledge Graphs focus group and contributes to advancing human-centric AI research across European institutions. Professor Simperl obtained her doctoral degree in Computer Science from the Free University of Berlin and her diploma from the Technical University of Munich. Prior to joining King's, she held academic positions in Germany, Austria, and at the University of Southampton, and was a Turing Fellow. Her career trajectory demonstrates consistent leadership in bridging academic research with practical applications in data ecosystems. Her research sits at the critical intersection of AI and social computing, focusing on human-centric approaches to building sociotechnical systems that integrate data, algorithms, and human capabilities. She investigates how to make knowledge engineering more accessible, how to leverage collective intelligence for data quality improvement, and how to design participatory AI systems that address societal challenges like misinformation. Her work spans knowledge graphs, semantic technologies, crowdsourcing, and open data, with particular emphasis on the social dimensions of data-intensive systems and the governance frameworks needed for trustworthy AI deployment. Analysis of her recent publications reveals a strong evolution toward integrating large language models with traditional knowledge engineering practices while maintaining human oversight. There's a clear trajectory from foundational work on knowledge representation toward increasingly applied research addressing real-world challenges in media ecosystems, citizen science, and data governance, with growing attention to policy implications of AI technologies. Fellow of the British Computer Society Fellow of the Royal Society of Arts Hans Fischer Senior Fellow at TUM-IAS (2023) Ranked among top 100 most influential scholars in knowledge engineering of the last decade Included in Women in AI 2000 ranking Professor Simperl has led 14 major European and national research projects totaling millions in funding, including MediaFutures (a Horizon 2020 program tackling online misinformation), QROWD, ODINE, Data Pitch, and ACTION. She currently co-chairs the Croissant working group in ML Commons developing data standards for AI, and serves as president of the Semantic Web Science Association. Her research has directly influenced the development of data ecosystems supporting startups and citizen science initiatives across Europe, demonstrating exceptional ability to translate theoretical advances into practical impact. As Director of Research at the Open Data Institute, she oversees initiatives connecting data entrepreneurs with artists and civic organizations. Her leadership in the MediaFutures project established a data-driven innovation hub that supported 51 startups/SMEs and 43 artists through three open calls, creating a sustainable model for arts-technology collaborations addressing media challenges. Her work with the ODINE project helped create a European ecosystem for data-driven startups, demonstrating her commitment to building practical applications of open data principles.
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