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Anton DidenkoView profile

Associate Professor

• Banking and Finance Law
• FinTech Regulation
• Central Bank Digital Currencies (CBDC)
• +5 more

Associate Professor Anton Didenko is a leading academic at UNSW Sydney's School of Private & Commercial Law, specializing in FinTech regulation, banking law, and central bank digital currencies (CBDC). He holds law degrees from Russia and the UK, including an MJur and DPhil from the University of Oxford. His research focuses on CBDC design, regulatory sandboxes, open banking frameworks, and cybersecurity in finance. University Affiliation: UNSW Sydney Key Academic Roles: Author of Banking Law in Australia (11th ed, 2024) and lead author of Customer Data Sharing Frameworks (2024) Global Engagement: Adviser to G20, Asian Development Bank, and UN agencies Research Interests: - CBDC policy and design implications - Regulatory frameworks for FinTech innovation - Cybersecurity in financial systems - Transnational commercial law and secured transactions - Open data and customer consent mechanisms Recent Articles: Focus on CBDC adoption in Pacific economies, weaponization of digital currencies in geopolitical conflicts, and comparative analysis of blockchain liabilities. His work bridges legal, technological, and policy dimensions of financial innovation. Awards : Australian Academic of the Year in Digital Finance (2023) Advising & Grants: - No listed advisees - Collaborations include Asian Development Bank-funded Pacific CBDC studies - Co-authored policy reports for UN Capital Development Fund and CPA Australia Labs/Teams: - Editor-in-Chief of the Cape Town Convention Journal - Co-leader of UNSW's FinTech regulation research initiatives

Pradip SharmaView profile

Associate Professor

• Cybersecurity
• Artificial Intelligence
• Blockchain
• +5 more

Dr. Pradip Sharma is an Associate Professor of Cybersecurity & AI at the University of Aberdeen, UK, within the School of Natural and Computing Sciences, Department of Computing Science. He is a globally recognized academic and researcher with expertise in Cybersecurity, Artificial Intelligence, Blockchain, and Edge Computing. His research interests span multiple domains including Cybersecurity, Blockchain, Edge Computing, Software-defined Networking, and IoT Security. Dr. Sharma's work focuses on developing innovative solutions for security challenges in emerging technologies, with particular emphasis on privacy-aware AI systems, secure data sharing frameworks, and intelligent network security mechanisms. His interdisciplinary approach bridges theoretical foundations with practical implementations across healthcare, smart mobility, and consumer electronics domains. Senior Fellowship Advance HE (SFHEA) IEEE Senior Member (SMIEEE) Dr. Sharma actively supervises doctoral researchers and is accepting new PhD students in Computing Science. His funded research portfolio exceeds £1M from sources including EPSRC, Innovate UK, and international agencies. Current projects include 'Secure, Privacy-aware, and Trusted Data Share in Smart Mobility' (EPSRC, £200K), 'ZECURE Data Exchange Platform' (Innovate UK, £236K), and 'Quantum-resistant Cybersecurity' (Royal Embassy of Saudi Arabia, £73K). He also serves as an editor for leading journals and is a regular keynote speaker at international conferences.

Simon YangView profile

Professor

• Artificial Intelligence
• Robotics
• Control Systems
• +7 more

Simon Yang is a Professor in the School of Engineering at the University of Guelph, part of the College of Engineering and Physical Sciences. His research focuses on artificial intelligence, robotics, sensors, control systems, and bio-inspired intelligence. He has contributed to advanced robotics applications, including mobile robot navigation, underwater vehicle control, and agricultural automation. Dr. Yang holds editorial roles for journals such as the International Journal of Robotics and Automation and IEEE Transactions on Cybernetics . His work bridges theoretical advancements with practical implementations in areas like sensor networks, machine learning, and multi-agent systems. Recent projects include developing robust control frameworks for autonomous systems, digital twin applications, and bio-inspired neural network algorithms. His research emphasizes real-world challenges in robotics, environmental monitoring, and precision agriculture, with a focus on integrating AI-driven solutions for enhanced decision-making and system reliability. Professional contributions include advisory roles in multiple journals and conference committees, reflecting his leadership in the field.

Chris BryanView profile

Assistant Professor

• Data Visualization
• Human-Computer Interaction
• Data Storytelling
• +6 more

Chris Bryan is an Assistant Professor in the School of Computing and Augmented Intelligence (SCAI) at Arizona State University (ASU), part of the Ira A. Fulton Schools of Engineering. He leads the Sonoran Visualization Laboratory (SVL @ ASU), focusing on data visualization, human-computer interaction, and advanced interfaces for data science. His research includes explainable AI, augmented/virtual reality, and privacy-preserving visualization techniques. Educations: Ph.D. Computer Science, University of California, Davis (2018) B.S. Computer Science, University of Arkansas (2008) Research Interests: Bryan’s work spans data visualization, human-computer interaction, explainable AI, and immersive visualization. He develops tools for collaborative analysis, privacy-aware systems, and visual analytics for complex data. Current projects involve VR/AR interfaces, bias reduction in NLP tasks, and educational visualization tools. Recent Achievements: Recipient of the 2024 and 2023 Top Five Percent Faculty Award at ASU’s Ira A. Fulton Schools of Engineering. NSF grants for privacy-preserving visualization (SaTC #2224066) and visualization education (IUSE #2216452). Multiple publications in top venues like IEEE VIS, CHI, and EuroVis, including work on differential privacy, mind wandering in visualization, and LLM prompt exploration. Advising & Grants: Advises Ph.D., MS, and undergraduate students on visualization and HCI research. Collaborates with institutions like Los Alamos National Laboratory, Phoenix Children’s Hospital, and Nankai University. Lab focuses on mentoring and preparing students for academic and industry roles in visualization and AI. Labs & Teams: Leads the SVL @ ASU, which uses advanced hardware (HTC Vive, HoloLens 2) and tools like D3.js, React, and LaTeX. The lab emphasizes interdisciplinary projects with domain experts in medicine, engineering, and security.

Germain GauthierView profile

Assistant Professor

• Political Economy
• Public Economics
• Econometrics
• +7 more

Germain Gauthier is an Assistant Professor at the Department of Social and Political Sciences, Bocconi University. His work bridges economics and political science with a focus on political economy, public economics, and machine learning methods. He develops AI tools for social scientists, particularly for analyzing unstructured data like texts and images. Ph.D. in Economics, Ecole Polytechnique (2018–2023) Postdoctoral Researcher, ETH Zürich (2023) M.Sc. in Analysis and Policy in Economics, Paris School of Economics (2017–2018) M.Sc. in Quantitative Economics, HEC Paris (2013–2017) His research spans two main areas: applied studies on digital technologies' societal consequences (e.g., X's algorithms, #MeToo's impact) and methodological innovations in machine learning for social science data. Recent publications include work on protest dynamics, inequality, and narrative extraction from texts. Key trends in his publications include: Machine learning applications to political and economic analysis Text mining for social science narratives Empirical studies on protest movements and digital governance Algorithmic bias in labor markets Economic policy evaluation using big data He has received significant funding: Swiss National Sciences Foundation Grant (300K CHF, 2023–2026) Swiss National Sciences Foundation Grant (100K CHF, 2020) Laboratoire d’Excellence Ph.D. Grant (2018–2023) He teaches courses on Public Finance (Bocconi) and Text as Data for Social Sciences (LMU München), and has developed open-source software packages like relatio and DeepLatent for text analysis and latent variable modeling.

Tony IngessonView profile

Senior Lecturer

• Intelligence Analysis
• Counter-espionage
• Military Decision-Making
• +4 more

Tony Ingesson is a Senior Lecturer in the Department of Political Science at Lund University, specializing in intelligence analysis, counter-espionage, and military decision-making. With a background in the Swedish Armed Forces where he worked with technical data acquisition for airborne weapons systems and communications, he brings practical military experience to his academic work. His research interests span intelligence analysis methodologies, counterintelligence operations, deception and manipulation at tactical levels, clandestine communications, and industrial espionage. Ingesson has developed a particular expertise in how psychological mechanisms and biases influence intelligence analysis, as well as the historical connections between military conscription and democratization. His work bridges theoretical political science with practical security applications. Analysis of his recent publications reveals a strong focus on contemporary security challenges, particularly the intersection of traditional and emerging technologies in intelligence operations. His work examines how historical communication methods persist in modern conflicts, the evolving nature of espionage in high-trust societies like Sweden, and the application of intelligence analysis techniques to non-traditional fields such as precision oncology. Ingesson demonstrates consistent scholarly output across both academic journals and public-facing platforms like The Conversation, indicating his commitment to making complex security issues accessible to broader audiences. Ingesson actively participates in interdisciplinary research projects, including 'Clandestine Communications: Old Technologies, New Opportunities' and 'Greyzone genomics' at the Pufendorf IAS. His teaching portfolio encompasses political science methods, intelligence analysis techniques, counterterrorism, and deception studies, reflecting the breadth of his expertise. While specific details about student advising aren't provided in the available information, his role as Senior Lecturer indicates involvement in mentoring students through his teaching responsibilities. His research team involvement includes collaboration with researchers like Magnus Andersson on clandestine communications and David Gisselsson Nord on the intersection of genomics and security. These collaborations demonstrate his ability to bridge disciplinary boundaries while maintaining focus on core intelligence and security issues.

• Stochastic Processes
• Queueing Theory
• Probability Theory
• +7 more

Michel Mandjes is a Professor at the University of Amsterdam's Faculty of Science and holds a Visiting Professor position at the Faculty of Economics and Business (FEB). His research focuses on stochastic processes, queueing theory, and probability theory, with applications in risk modeling, network analysis, and operations research. Recent publications highlight his contributions to multivariate Hawkes processes , Lévy-driven systems , and dynamic random graphs , emphasizing large deviations, rare event simulation, and statistical inference. His work bridges theoretical probability with practical challenges in traffic flow, financial risk, and social network modeling. The trends in his research include the development of stochastic models for network stability, appointment scheduling optimization, and inference techniques for non-stationary processes. His methodological innovations often leverage advanced probability theory and queueing frameworks to address real-world problems in transportation, healthcare, and finance.

Istvan David McMasterView profile

Assistant Professor

• Digital Twins
• Model-Driven Engineering
• Sustainability
• +6 more

Istvan David is an Assistant Professor in the Department of Computing and Software at McMaster University , with research expertise spanning Digital Twins , Model-Driven Engineering , and Sustainability . His work bridges theoretical and applied domains, focusing on smart ecosystems , collaborative modeling , and AI-driven simulation . Key contributions include frameworks for digital twin evolution and interoperability in sustainable systems. Education : BSc, MSc, and PhD in Computer Engineering and Computer Science from Budapest University of Technology and Economics, and University of Antwerp. Research Areas : Digital Twins, Model-Driven Engineering, Reinforcement Learning, Smart Ecosystems, Sustainability, Collaborative Modeling, Cyber-Biophysical Systems, and Software Architecture. Recent Article Trends emphasize AI integration with digital twins, collaborative modeling in industrial contexts, and sustainable systems engineering . His work often combines machine learning with formal modeling to address challenges in technical sustainability and smart agriculture .

Benedikt AumeierView profile

Research Fellow

• Water Treatment
• Adsorption/Sorption
• Membrane Filtration
• +5 more

Dr. Benedikt Aumeier is a Research Fellow and head of the working group "Advanced Water Treatment" at the Chair of Urban Water Management, Department of Civil, Geo and Environmental Engineering, TUM School of Engineering and Design at the Technical University of Munich since 2023. Previously, he served as a Post-Doc and Working Group Leader at the Institute of Urban Water Management, RWTH Aachen University from 2020-2023. Dr. Aumeier holds a Dr.-Ing. from the Chair of Chemical Process Engineering at RWTH Aachen University (2020), an M.Sc. in Management and Technology of Water and Wastewater from the University of Duisburg-Essen (2011-2013), and a B.Sc. in Chemical Engineering from the Technical University of Munich (2007-2011). His research focuses on advanced water treatment processes for direct and indirect water reuse, drinking water treatment, and wastewater treatment. Key areas include adsorption/sorption, membrane filtration, advanced oxidation processes, and disinfection. He investigates competitive adsorption in aqueous media, novel sorbent regeneration methods, membrane fouling countermeasures, and process modeling. His work addresses removal of persistent and mobile organic contaminants including PFAS, as well as microorganism elimination. Dr. Aumeier's publications demonstrate a strong trend toward addressing emerging water quality challenges, particularly concerning persistent organic pollutants and advanced treatment technologies. His research spans fundamental studies on adsorption mechanisms to practical applications for water reuse and decentralized treatment systems, with increasing focus on PFAS removal and compliance with regulatory frameworks. Mitglied im Fachausschuss "Persistente-Mobile-Toxische (PMT) Stoffe" der Wasserchemischen Gesellschaft, Gesellschaft Deutscher Chemiker (GDCh) Mitarbeit an DWA M1200 Teil 2 "Wasserwiederverwendung für landwirtschaftliche und urbane Zwecke in Deutschland" At TUM, Dr. Aumeier teaches courses including "Natural processing methods," "Advanced Water Treatment Engineering and Reuse," and "Industrial wastewater treatment and reuse," demonstrating his commitment to educating the next generation of water professionals. He leads the "Advanced Water Treatment" working group, which focuses on developing and applying innovative water treatment technologies to address contemporary water quality challenges under changing climate conditions.

Zhi ChenView profile

Lecturer

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +3 more

Dr. Zhi Chen is a Lecturer in Computing at the School of Mathematics, Physics and Computing, University of Southern Queensland, specializing in Artificial Intelligence and Machine Learning with applications spanning digital agriculture and healthcare systems. Education: Master of Information Technology (MIT), University of Queensland, 2018 PhD, University of Queensland, 2023 Research Focus: His work centers on zero-shot learning, domain adaptation, and multimodal systems, addressing core challenges in computer vision and deep learning. Current projects integrate AI with agricultural risk modeling and medical diagnostics, emphasizing real-world deployment of robust algorithms under data-scarce conditions. Publication Trends: Recent output (2022-2025) shows concentrated expertise in source-free domain adaptation and generalized zero-shot learning, with significant contributions to plant disease recognition (via mobile multimodal systems) and diabetes subgroup analysis. His work consistently appears in premier venues including AAAI, CVPR, and ACM MM, demonstrating methodological innovation applied to critical domains like climate-resilient agriculture and precision medicine. Supervision: Currently serves as Associate Supervisor for a doctoral candidate developing parametric insurance models for oyster farms to mitigate climate-related risks from king tides and extreme weather events. Awards: No scientific awards were documented in the provided materials.

• Road Safety
• Connected and Automated Vehicles
• Driver Behaviour
• +5 more

Evita Papazikou serves as a Lecturer in Transport Engineering at the School of Engineering, University of the West of England (UWE Bristol), where she contributes to the Centre for Transport and Society and collaborates with the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre. Her academic qualifications include: Civil Engineering (BEng and MEng) from Aristotle University of Thessaloniki MSc in Planning, Organisation, and Management of Transport Systems, Aristotle University of Thessaloniki PhD in Automated Systems and Driver Behaviour (Road Safety) from Loughborough University, sponsored by the Insurance Institute for Highway Safety with access to SHRP2 NDS data Dr. Papazikou's research focuses on road safety, connected and automated vehicles, driver behaviour analysis, and smart infrastructure. She investigates accident causation through statistical modeling, develops driver monitoring systems, and explores human factors in transportation. Her work integrates traffic simulation with mobility data fusion from vehicles, sensors, and infrastructure to enhance safety in future mobility systems, particularly in cooperative, connected, and automated environments. Her recent publications (2023-2025) reveal a concentrated research trajectory examining safety impacts of dedicated lanes for autonomous vehicles, parking policy implications in automated eras, and driver fatigue management. She consistently employs naturalistic driving data and traffic microsimulation to analyze driver-vehicle-environment interactions, with increasing emphasis on real-world intervention effectiveness and environmental sustainability in mobility systems. Scientific Awards: No specific awards were mentioned in the provided information. Dr. Papazikou has secured significant research funding through competitive programs including Horizon 2020, Innovate UK, and the Department for Transport. Her project portfolio demonstrates substantial industry collaboration, particularly with Ford, and includes: LEVITATE: Assessing societal impacts of Connected and Automated Vehicles SafetyCube: Developing an innovative road safety decision support tool i-DREAMS: Creating a smart driver and road environment assessment system DDRST: Building a data-driven road safety tool for hotspot identification TRIP: Developing a driver culpability assignment tool for road injury prevention She actively contributes to interdisciplinary research through her affiliations with the Centre for Transport and Society and the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre, where she bridges engineering, human factors, and policy development for next-generation transportation systems.

George VasilakopoulosView profile

Professor

• Health Informatics
• Cloud Computing
• Emergency Healthcare Systems
• +4 more

George Vasilakopoulos is a Professor in the Department of Digital Systems at the University of Piraeus , where he also serves as Vice-Chancellor for Academic Affairs and Personnel. By law, he is President of the Quality Assurance Unit (MODIP) and the Employment and Career Structure (DASTA) of the university, overseeing the development of modern information systems. He earned his PhD from the University of London and has held leadership roles including Department President, Director of Postgraduate Programs, and Scientific Director of the Digital Health Services Laboratory. PhD: University of London Current Roles: Vice-Chancellor, Department of Digital Systems Professor Labs: Digital Health Services Laboratory His research focuses on Health Informatics , Cloud Computing , and Medical Data Security , with key contributions to: Emergency healthcare process automation Privacy-preserving personal health record systems Context-aware authorization models Cloud-based medical service frameworks Machine learning in clinical data analysis Interoperable health information systems The trends in his 15 most recent articles (2010-2015) reveal a consistent emphasis on integrating cloud infrastructure , semantic technologies , and mobile platforms to enhance emergency care, chronic disease management, and patient data security. His work bridges biomedical engineering , software architecture , and public health policy . He has held advisory roles for the Minister of Health on IT issues, served on hospital boards, and contributed to national committees for healthcare technology standards. His professional activities include project evaluation for Greek and European research programs and authoring three books on health informatics.

Nathaniel NucciView profile

Associate Professor

• Protein Biophysics
• Spectroscopy
• Drug Development
• +11 more

Nathaniel Nucci is an Associate Professor at Rowan University's College of Science & Mathematics, jointly appointed in the Department of Biological & Biomedical Sciences and Physics & Astronomy. His research bridges biophysics, structural biology, and nanotechnology to understand protein behavior in confined environments. Education Ph.D., Biochemistry and Molecular Biophysics, University of Pennsylvania M.S., Biochemistry and Molecular Biology, University of New Hampshire B.S., Biochemistry and Molecular Biology, University of New Hampshire Research Interests Dr. Nucci's lab focuses on: Protein biophysics in crowded/confining environments Reverse micelle technology for biomolecular studies Hydration dynamics of proteins (NMR-based methods) Structural biology of disease-related proteins (PHDs, p53) Drug delivery systems for protein therapeutics Nanoparticle synthesis with protein conjugation Research Trends His recent publications demonstrate expertise in using reverse micelles to study: Protein structural stability under confinement Hydration dynamics of therapeutic proteins Microenvironmental effects on phase-separating proteins Conformational changes in GPCRs Interfacial interactions in biomolecular systems Scientific Awards Gary J. Hunter Excellence in Mentoring Award (2024) College of Science and Mathematics Excellence in Academic Student Support (2022) Teaching Philosophy Emphasizes applied and experiential learning, integrating recent scientific discoveries into classroom practice and promoting hands-on scientific investigation.

• Immunology
• Molecular Immunology
• T-Cell Biology
• +7 more

Michael Dustin is the Kennedy Trust Professor of Molecular Immunology and Director of Research at the Kennedy Institute of Rheumatology , University of Oxford. His career spans leadership roles at Washington University School of Medicine (1993–2000) and Skirball Institute of Biomolecular Medicine at NYU School of Medicine (2001–2013). Education : B.A. in Biology, Boston University (1984) Ph.D. in Cell and Developmental Biology, Harvard University (1990) Prof. Dustin's research focuses on the immunological synapse , a specialized interface between T cells and antigen-presenting cells. His work has revealed supramolecular attack particles as autonomous killing entities, synaptic ectosomes for TCR cargo transfer, and mechanistic insights into T cell signaling pathways. His recent publications highlight advancements in vaccine adjuvant response , T cell receptor dynamics , and glycosphingolipid synthesis in immune cells. Collaborations span neuroscience, cancer immunology, and rheumatology. Scientific Awards : Wellcome Trust Principal Research Fellowship European Research Council Advanced Grant (SYNECT) As Director of the NIH-funded Nanomedicine Center for Mechanobiology (2009–2014), he pioneered mechanobiology applications in immunology. Current projects integrate intravital microscopy and clinical translation for human diseases. His laboratory at Oxford investigates T cell regulation in autoimmune and inflammatory diseases, supported by an international network of collaborators including Wenbiao Gan, Dan Littman, and Dorian McGavern.

• Artificial Intelligence in Accounting
• Machine Learning Applications
• Fraud Detection
• +3 more

Benjamin Lee is a Senior Lecturer of Accounting and Director of Student Matters at the School of Accountancy, Singapore Management University. He serves as an SMU-X Academic Champion, driving experiential learning initiatives and promoting AI integration in accounting education and practice across multiple institutional roles. His academic background includes: Doctor of Philosophy in Management (Strategy and Technology Management), University of Glasgow, 2025 Master of Science in Business Analytics with Distinction, University of Surrey, 2017 Bachelor of Accountancy, Singapore Management University He is a Chartered Accountant of Singapore with prior industry experience as a consulting data analyst at Singapore's Accountant-General’s Department. Dr. Lee's research centers on AI-driven analytics (AIDA) applications for accounting problem-solving, including fraud detection, financial forecasting, and credit risk analysis. His work explores organizational dynamic capabilities in digital transformation and AI governance frameworks within professional service firms. His publication portfolio (2017-2025) reveals consistent focus on digital transformation across accounting and SME contexts, with recent emphasis on machine learning applications in fraud detection and public transport optimization. The research bridges academic theory with practical industry implementation through numerous case studies. His teaching excellence has been recognized through multiple awards including: Dean’s List for Teaching Excellence (2023-2025) SMU-X Excellent Teacher Award (2023) Howard Teall Award for Innovation in Accounting Education (2023) Wharton-QS Reimagine Education Digital Readiness Award (2022) While specific doctoral advising isn't documented, Dr. Lee actively mentors students through SMU-X experiential projects and industry collaborations. His industry partnerships with ISCA and media contributions to The Business Times demonstrate practical knowledge transfer beyond academia. He holds leadership positions including Director of Student Matters, SMU-X Academic Champion, and member of ISCA's AI Taskforce Sub-Committee on Policy and Regulation, where he shapes professional standards for AI implementation in Singapore's accounting sector.