Umer Farooq is a Professor at Dhofar University's College of Engineering, specializing in Electrical and Computer Engineering. His research spans interdisciplinary areas including artificial intelligence, nanotechnology, educational technology, and cybersecurity. He has contributed to over 90 publications since 2002, focusing on topics such as neural networks, federated learning, IoT security, and biomedical applications. His work bridges theoretical advancements with practical implementations in fields like medical imaging, renewable energy systems, and smart education platforms. Research interests emphasize innovative solutions at the intersection of engineering and computing. Notable contributions include federated learning frameworks for education, neural network-based medical diagnostics, and secure IoT systems. Recent trends in his publications highlight advancements in machine learning for healthcare, nonlinear dynamics in electronic systems, and sustainable energy solutions. No scientific awards or grants are explicitly listed in the provided texts. Collaborations span global institutions, reflecting his active role in international academic networks.
Simon Parkinson is a Professor at the University of Huddersfield specializing in cybersecurity and machine learning applications in security systems. His research focuses on empirical analysis of access-control systems, threat prediction, and defensive AI strategies. Parkinson's work combines data mining, behavioral analysis, and computational methods to address real-world security challenges. Recent publications demonstrate strong emphasis on biometric security, IoT protection, and forensic investigation techniques. His 2023-2025 research explores LLM-based event log analysis, wearable biometric cryptosystems, and zero-day DDoS detection in IoT networks. Collaborative projects include international case studies in Bahrain and innovative applications of computer vision in security diagnostics. Parkinson contributes to cybersecurity education initiatives and stakeholder engagement for security standardization.
Dr. Jonathan Lazar is a Professor in the College of Information Studies (iSchool) at the University of Maryland, where he serves as Executive Director of the Maryland Initiative for Digital Accessibility (MIDA) and core faculty in the Human-Computer Interaction Lab (HCIL). He previously held a professorship at Towson University, where he founded the Universal Usability Lab and directed the information systems program. His work bridges human-computer interaction (HCI), disability rights, and legal policy to advance digital accessibility for marginalized populations, particularly blind users, individuals with cognitive impairments, and people with Down syndrome. Education: LL.M. (Disability Rights Law, University of Pennsylvania), Ph.D. (Information Systems, UMBC), M.S. (Information Systems, UMBC), B.B.A. (Management Information Systems, Loyola University Maryland). Research Focus: Dr. Lazar's work emphasizes ICT accessibility in developing countries, non-visual modalities for blind users, ballot accessibility for voters with disabilities, and legal frameworks to enforce accessibility standards. He has authored/co-authored 17 books and over 200 peer-reviewed articles, with notable contributions on accessible data visualization, automated accessibility testing, and the intersection of law and technology. Awards: Includes the ACM SIGACCESS Outstanding Contribution Award (2020), ACM SIGCHI Social Impact Award (2016), and multiple University System of Maryland Board of Regents Awards. His research has influenced U.S. federal regulations, including airline website accessibility mandates following his work on discriminatory pricing for blind travelers. Professional Service: Serves on the executive board of the Friends of the Maryland Library for the Blind, co-chairs the Cambridge Workshop on Universal Access and Assistive Technology (CWUAAT), and advises government agencies on accessibility policy. He advocates for inclusive design in public libraries, voting systems, and educational technologies. Labs & Projects: Leads the Trace R&D Center's legacy work on accessibility, co-designs health IT tools with individuals with Down syndrome, and develops tools like FormA11y for PDF accessibility remediation. His research emphasizes translating academic findings into actionable policies and practices.
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.
Barbara Carminati is a Professor at the Department of Theoretical and Applied Science, University of Insubria, Italy. Her work focuses on security, privacy, and trust management in decentralized systems, particularly online social networks, IoT, and emerging technologies like blockchain and digital twins. She has contributed extensively to access control, risk assessment, and collaborative frameworks. Her research spans trust modeling , privacy-preserving mechanisms , and malware detection , with a strong emphasis on decentralized social networks and UAV security . She actively explores the application of blockchain for secure workflows and information sharing. Recent publications highlight her engagement with large language models for security optimization, IoT botnet detection , and metadata leakage analysis . Her work bridges theoretical foundations with practical implementations in cybersecurity, social network management, and edge computing. Contact: barbara.carminati@uninsubria.it
Katherine Flanigan is an Assistant Professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in the Department of Electrical and Computer Engineering. She holds a Ph.D. in Civil Engineering from the University of Michigan (2020) and earlier degrees from the same institution (M.S.E. in Electrical and Computer Engineering, 2018, and M.S.E. in Civil Engineering, 2016) and a B.S.E. in Civil and Environmental Engineering from Princeton University (2014). Her research focuses on transforming civil infrastructure and urban systems into intelligent cyber-physical systems (CPS) by integrating sensing, computing, and actuation technologies. Key areas include developing wireless sensor networks for smart cities, modeling infrastructure resilience, and leveraging digital twins for data-driven decision-making. She extends this work to cyber-physical-social systems (CPSS), emphasizing human-infrastructure interactions and equity in policy-making through community-driven data. Flanigan is particularly noted for projects combining technical and social dimensions, such as human-in-the-loop control solutions and privacy-preserving urban sensing technologies. Flanigan has received prestigious awards including the NSF Graduate Research Fellowship, the Towner Prize for Outstanding PhD Research, and the Wimmer Faculty Fellow award for teaching innovation. She advises PhD student Lindsay Graff, whose work addresses transportation equity and multimodal networks. Her research also involves collaborations with industry leaders via the Manufacturing Futures Institute, and she leads the Autonomous Infrastructure Systems Lab at CMU. Her teaching contributions include course redesigns focused on hands-on projects, such as constructing habitats for pollinators and Little Free Libraries to blend engineering with community impact. She emphasizes preparing students for real-world challenges through project courses that teach sensing, data analysis, and infrastructure system design under constraints like risk and resource limitations.
Beng Chin Ooi is a Lee Kong Chian Centennial Professor at the National University of Singapore (NUS), School of Computing. He has been with NUS since 1991, progressing through the ranks from Lecturer to his current distinguished position. He previously served as Dean of the School of Computing from 2007 to 2013 and as Director of the Smart Systems Institute from 2011 to 2021. His educational background includes: 1985: B.Sc. (1st Class Honors) from Monash University, Melbourne, Australia 1989: Ph.D. in Computer Science from Monash University, Melbourne, Australia Beng Chin Ooi's research focuses on database systems, large scale analytics, and distributed systems. His work has been instrumental in advancing the field of data management technology, particularly in the context of "big data" in large-scale parallel and distributed systems. He has made significant contributions to spatio-temporal and distributed data management, as well as pioneering research in distributed database management and peer-to-peer based enterprise quality management. His recent publications demonstrate a strong focus on blockchain technology, machine learning systems, and healthcare informatics. There's a clear progression from foundational database research to applications in emerging technologies like blockchain and AI. His work bridges theoretical advances with practical system implementations, as evidenced by multiple open-source projects associated with his publications. His notable awards include: 2021: NUS Research Recognition Award 2020: ACM SIGMOD E.F. Codd Innovations Award 2020: ACM SIGMOD Research Highlight Award 2019: VLDB Best Paper Award 2016: Fellow of Singapore National Academy of Science 2016: China Computer Federation Overseas Outstanding Contributions Award 2014: VLDB Best Paper Award 2014: IEEE TCDE CSEE Impact Award 2013: Singapore National Day's Public Administration Medal (Silver) 2013: NUS Outstanding Researcher Award 2012: IEEE Computer Society Kanai Award 2011: ACM Fellow 2011: Singapore President's Science Award 2009: IEEE Fellow 2009: ACM SIGMOD Contributions Award Throughout his career, Professor Ooi has demonstrated exceptional leadership in the database community, promoting high standards of database research at both international and regional levels. His BLOCKBENCH framework became the world's first benchmarking tool for private blockchains, and his work on data provenance on blockchain systems earned both the VLDB Best Paper Award and the ACM Research Highlight Award. He has led several major research initiatives, including the Smart Systems Institute at NUS. Professor Ooi has established multiple open-source projects including FabricSharp for blockchain data provenance and Cool for cohort online analytical processing. His research group has consistently produced high-impact work that bridges theoretical advances with practical system implementations.
Hooman Samani is a Reader and Course Leader of Creative Robotics at the University of the Arts London's Creative Computing Institute, and a Visiting Lecturer at the University of Hertfordshire. He holds a PhD in Robotics from the National University of Singapore and is a Fellow of the Higher Education Academy (FHEA). His research spans AI-driven social robotics, creative robotics, and robotics for healthcare, with notable contributions to ethical AI, human-robot interaction, and pandemic response systems. He has led projects at institutions like Philips, Fraunhofer, and the Keio-NUS CUTE Centre. Education: PhD in Robotics (National University of Singapore), prior roles at National Taipei University (founding AIART Lab), and industry experience at Posco and Philips. Research Interests: Focus on interdisciplinary applications of robotics, including cognitive robotics, cultural robotics, and AI in mental health. He advocates for ethical design, emphasizing trustworthiness and societal impact. Publications: Over 98 articles, books like Creative Robotics and Robotics for Pandemics . Recent trends include memory-driven AI, agentic systems, and ethical multi-robot collaboration. Awards: FHEA, multiple RoboCup competition wins. Active in media, featured on BBC, CNN, and Discovery Channel. Labs/Teams: Founded AIART Lab, involved in collaborative projects with Keio-NUS CUTE Centre. Current focus on creative robotics in theater and education.
Niko Mäkitalo is an Assistant Professor at the University of Jyväskylä's Faculty of Information Technology and a member of the University Consortium Chydenius. His research focuses on advancing cyber-physical systems through innovative software architectures for AI, IoT, and the Cloud-Edge Continuum, with significant emphasis on hardware and network infrastructures. He teaches and mentors graduate students in these areas. Research Interests: Mäkitalo's work centers on creating intelligent environments via novel software frameworks, engineering methodologies for distributed AI/ML applications, and addressing ethical/privacy challenges in edge computing. He explores the intersection of agile development practices, third-party code management, and industry standards like IDSA/GAIA-X for AI integration. Key Contributions: His recent work includes studies on software ownership dynamics, regulatory-aware AI deployment, and liquid AI systems. He leads the Empirical Software Engineering Research group and collaborates on initiatives like 6GSoft for edge-cloud software solutions. Advising & Grants: Mäkitalo supervises Master's and Ph.D. candidates in software engineering and systems architecture. His projects often involve industry partnerships to address real-world challenges in smart manufacturing, autonomous systems, and networked environments. Labs/Teams: Active in the Empirical Software Engineering Research group, contributing to cross-disciplinary projects at the University of Jyväskylä's tech innovation ecosystem.
Jennifer Jie Zhang is the Daniel Himarios Endowed Chair Professor of Information Systems in the College of Business at the University of Texas at Arlington , within the Department of Information Systems and Operations Management . She earned her Ph.D. in Computer Information Systems from the University of Rochester in 2003, preceded by an M.S. in Management Science from the same university and a B.E. in Engineering Economics from Tianjin University . Her research interests lie at the intersection of information systems, digital marketing, and AI applications , focusing on: Social Media & Networks : Impact on business and consumer behavior. AI in Business & Healthcare : Analytical and empirical studies. Digital Marketing : Online channel strategies, pricing, and advertising. Crowdsourcing & Innovation : Tournament design and team dynamics. Privacy & Ethics : Consumer data protection and market mechanisms. Her recent publications (2021-2024) emphasize real-time analytics in meal delivery, AI-driven insights for fitness apps, and social media dynamics affecting box office performance. These works highlight her expertise in leveraging big data for operational and strategic decision-making. Awards & Honors: Daniel Himarios Endowed Chair Professorship (2021-present). Best Paper Awards/Runner-ups at ICIS, WITS, HICSS, and AMCIS. Distinguished Research Publication Awards from UTA and College of Business. NSF-funded grants including "Convergence Accelerator Pilot: Credible Open Knowledge Network" ($999,870). Advising & Grants: PhD Chair/Co-Chair for 6+ students (e.g., Siddhi Nair, Jiang Hu). Committee Member for 10+ doctoral candidates. Undergraduate/Master’s Advisor for capstone and thesis projects. Principal/Co-Investigator on federal grants (NSF, totaling ~$1M). Labs & Teams: Leads research initiatives in Web Analytics and Digital Enterprise Management , collaborating with interdisciplinary teams across UTA’s College of Business and external partners (e.g., industry sponsors, international workshops).
Associate Professor Ben Matthews is affiliated with The University of Queensland (UQ), holding positions in the School of Electrical Engineering and Computer Science (Faculty of Engineering, Architecture and Information Technology) and as an Affiliate of the Centre for Communication and Social Change (Faculty of Humanities, Arts and Social Sciences). He leads research in design processes focusing on collaborative and participatory methodologies, with expertise in healthcare technology, educational tools, and community resilience. Education: BEng (Hons) and PhD from UQ. His research spans three core domains: designing advocacy for marginalized groups, participatory design materials, and augmenting professional expertise through technology. Key projects include designing for mental health stakeholders, wearable displays in healthcare, and bushfire resilience frameworks. Research Interests: Interaction design, participatory design, technology ethics, and human-centered innovation. His work emphasizes inclusive design processes that amplify user agency in technology development. Recent studies include VR analytics for mental health, energy use transparency, and emergency medical AR systems. Grants: Current funding includes ARC projects on AI-driven recruitment and trauma patient pathways. Past grants involve wearable tech for high-tempo work and passport processing research. Over 100 publications span journals like International Journal of Human-Computer Studies and conferences such as OzChi. Advising: Supervises PhD candidates on topics ranging from augmented reality in education to language learning applications. Collaborates with interdisciplinary teams across healthcare, education, and urban planning.
Dr. Sharib Ali is a Lecturer (Assistant Professor) in the School of Computer Science at the University of Leeds, Faculty of Engineering and Physical Sciences. He is affiliated with the Leeds Cancer Research Centre and actively contributes to research in biomedical image analysis and computer vision. His work bridges cutting-edge AI with clinical applications, particularly in endoscopy and surgical technologies. PhD in Medical Image Analysis, University of Lorraine, France MSc in Computer Vision (by research), University of Burgundy, France Dr. Ali's research focuses on biomedical image analysis , computer vision , and machine learning , with applications in early cancer detection , computational endoscopy , and 3D reconstruction . He develops robust algorithms for segmentation, registration, depth estimation, and mosaicking, using both classical mathematical models and deep learning. His work emphasizes translational research and generalisability in real-world clinical settings. The recent publications highlight a strong trend in generalisability assessment , multi-modal data fusion , and AI benchmarking in endoscopy. His work spans from foundational algorithm development to clinical deployment, including federated learning , mixed reality in surgery , and multi-centre datasets , addressing key challenges like bias, data imbalance, and privacy. Dr. Ali has co-supervised multiple DPhil/PhD students and currently supervises several PhD candidates at the University of Leeds, University of Oxford, and Tec de Monterrey. He is actively involved in securing research funding and leading projects such as Leveraging multi-modality data for targeted biopsy and Federated learning in healthcare . He is a founding member of NAAMII, Nepal, where he volunteers to train students from LMICs. He also organizes international research initiatives including the EndoCV and P2ILF challenges at MICCAI, and serves on program committees and as a reviewer for journals like Nature Communications and Medical Image Analysis . His research is conducted within interdisciplinary teams, collaborating with clinicians from Oxford NHS University Hospitals, neuroscientists at Forschungszentrum Jülich, and engineers across Europe. He leads the development of open tools and datasets to advance the field of endoscopic computer vision.
Ashish Nanda is a Research Fellow at the Deakin Cyber Research and Innovation Centre (Deakin Cyber) at Deakin University, Australia, where he contributes expertise to pioneering cybersecurity research. Prior to his current role, he served as a Research Fellow at the Centre for Cyber Resilience and Trust (CREST), Centre for Cyber Security Research and Innovation (CSRI), and the Deakin Blockchain Innovation Lab (DBIL). He has also enriched the academic community as a Lecturer at the University of Technology Sydney. Dr. Nanda's educational background includes: PhD in Computer Science from the University of Technology Sydney Bachelor of Technology in Computer Science & Engineering from Amity University, India His research spans cybersecurity, authentication technologies, digital identity, and usable security. Nanda has contributed to national projects funded by the Cyber Security CRC, focusing on multi-factor authentication, privacy-preserving digital credential wallets, and ambient intelligence-based continuous authentication systems. His work bridges technical security measures with human factors, emphasizing that security solutions must be both robust and user-friendly to achieve widespread adoption. This human-centered approach to security has become increasingly prominent in his recent publications. Dr. Nanda's publication trajectory shows a clear evolution from foundational network security protocols toward increasingly human-centered security approaches. While his earlier research focused on technical aspects of secure routing for wireless mesh networks and IoT infrastructure, his recent work emphasizes usable security, authentication devices, and digital identity systems. This shift reflects the growing recognition in cybersecurity that technical solutions alone are insufficient without considering human factors and user experience. Dr. Nanda has received significant research funding through: Cyber Security Cooperative Research Centre (CRC) Australia's Economic Accelerator program He actively contributes to public discourse through articles in The Conversation and interviews with major media outlets including SBS News, The Guardian, and The Feed. His research collaborations extend across multiple institutions with emphasis on practical applications addressing real-world cybersecurity challenges. Nanda has also co-founded Adroit Explorer Innovation Chambers, a not-for-profit organization dedicated to fostering innovation and exploration in technology.
Dr. Adriane B. Randolph is a Professor and Executive Director of the BrainLab at Kennesaw State University’s Coles College of Business. Her work bridges neuroscience and information systems, focusing on brain-computer interfaces (BCIs) and their applications in assistive technologies, consumer behavior, and educational tools. Primary Affiliation: Kennesaw State University School: Coles College of Business Department: Information Systems Research interests include: Developing BCIs to assist individuals with locked-in syndrome (e.g., cerebral palsy, ALS) Neuromarketing studies on brand placement and consumer decision-making Exploring neural responses to workplace productivity and video games Designing systems to enhance cognitive engagement in educational settings Recent publications highlight interdisciplinary applications of BCIs in healthcare, education, and cybersecurity. Notably, her 2022 work in the Journal of Information Systems Education outlines a neuro-IS course, while 2020’s SAIS conference paper details IoT integration in BCI systems for locked-in patients. Scientific contributions include: 2020: Best Paper in Track, Southern Association for Information Systems (SAIS) Annual Conference Dr. Randolph mentors students in the BrainLab, fostering collaboration between undergraduate and graduate researchers. Her lab partners with institutions like Georgia Tech and the National ALS Association to advance BCI applications, with a mission to improve quality of life through non-invasive technologies.
