جست‌وجوی استاد و پژوهشگر

Ian Bayleyمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Secure Programming
• Exploits
• +۱۱ مورد دیگر

Dr. Ian Bayley is a Senior Lecturer in Computer Science at the School of Engineering, Computing and Mathematics, Oxford Brookes University. He serves as Subject Coordinator for MSc courses in Computing Science, Advanced Computer Science, and Computer Science for Cyber Security. His research focuses on cybersecurity, secure programming, software engineering, and design patterns, with collaborations on topics like LLM evaluation, exploratory testing for machine learning, and agent-oriented programming for microservices. He is affiliated with the Cloud Computing and Cybersecurity Group (CCC) and the Artificial Intelligence, Data Analysis and Systems (AIDAS) Institute. Teaching responsibilities include modules such as Secure Programming (undergraduate/postgraduate) and Professional Programming Practice for first-year undergraduates. He actively supervises cybersecurity projects and students, including Debalina Ghosh (LLM evaluation) and Kieren Stanton (authentication in vehicular networks). Research interests span cybersecurity patterns, software design composability, formal methods for web services, and agent-oriented approaches to microservices. Recent work explores LLM evaluation via scenario-based meta-information and testing challenges in machine learning applications. He co-leads research on design pattern composition and algebraic specifications. Publications span journals like Journal of Systems and Software and IEEE Transactions on Software Engineering , addressing topics from cybersecurity patterns to formal verification of web services. His teaching and research emphasize practical software engineering principles and cutting-edge cybersecurity practices.

Mohammad Kazemi Beydokhtiمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Natural Language Processing (NLP)
• Geospatial Domain
• +۵ مورد دیگر

Mohammad Kazemi Beydokhti is a Research Fellow (Level A) at RMIT University's Research & Innovation Capability department. He is also a PhD candidate with expertise in Machine Learning, NLP, and Geospatial Domain applications. His research focuses on qualitative spatial reasoning, GeoQA systems, knowledge graphs, and LLMs, with notable contributions to projects like Dynamic Vicmap (awarded the 'Innovation Award' by GCA) and the RMIT AWS Cloud Supercomputing Hub. He has collaborated with institutions like Utrecht University and has taught courses such as Advanced Imaging Technology (GEOM2112), Geospatial Programming with Python (GEOM2157), and Applied Geospatial Techniques (GEOM2450) as a tutor at RMIT from July 2021 to August 2024. His scientific contributions span geospatial question-answering systems, probabilistic spatial reasoning, and spatial-temporal modeling of seismic activity. Key projects include the DBSCAN-based seismic province analysis in Iran and ANP-OWA method applications in air quality monitoring station placement. Research Awards: Innovation Award (GCA) for Dynamic Vicmap project Labs/Teams: Involved in RMIT's AWS Cloud Supercomputing Hub and geospatial collaboration networks

Abebe Diroمشاهده پروفایل

مدرس

• Cybersecurity
• AI-Driven Security
• Cryptography
• +۳ مورد دیگر

Dr. Abebe Diro is a Lecturer in Cybersecurity at RMIT University's School of Accounting, Information Systems and Supply Chain. He holds roles such as Representative on the CoBL Early Career Academic in Business Research Committee (2023–2024) and Chair of the AISSC Workload Committee (2024–2025). His research focuses on AI-driven security, cryptography, space cybersecurity, and critical infrastructure protection, supported by grants from the Australian Defence and CSIRO Data61. He has received awards for research and teaching excellence. Dr. Diro's work addresses challenges in cybersecurity governance, policy development, and cross-sector collaboration, with a commitment to sustainable development goals related to infrastructure, education, and urban resilience. Research Highlights: Defence 2024 Strategic Policy Grants Program Enhancing Cyber Security across the Pacific University Sector CSIRO Data61 collaborations Teaching Expertise: Specializes in cybersecurity technical subjects and governance frameworks, maintaining ACS accreditation standards. Courses integrate innovative methodologies and machine learning applications. Grants & Projects: Australian mining sector cybersecurity initiatives Machine learning-based cyber threat attribution research Industry 5.0's impact on digital trust and compliance Awards: Early Career Research Excellence Award (2024) Early Career Teaching Excellence Award Labs/Teams: Engaged with interdisciplinary teams at RMIT's School of Accounting and Information Systems, collaborating with CSIRO and industry partners on applied cybersecurity solutions.

Eila Erfaniمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence Ethics
• Cybersecurity Management
• Business Analytics
• +۴ مورد دیگر

Dr. Eila Erfani is a Senior Lecturer at the School of Information Systems and Technology Management (SISTM) within the UNSW Business School. She leads the Cybersecurity Management major and Business Analytics programs. Dr. Erfani holds a PhD in Information Systems from Macquarie University, alongside a Master of Systems Engineering and Bachelor of Engineering. Her research focuses on ethical AI integration, cybersecurity governance, and leveraging machine learning for sustainability challenges. Notable areas include: AI ethics in healthcare and finance IoT-driven safety systems Open innovation platforms Big data analytics for sustainable supply chains Publications span applications of machine learning in lithium markets, bioleaching optimization, and drowning detection technologies. She has also extensively studied social media's psychological impacts, including addiction risks and mental health consequences. Recent work includes developing mHealth applications for senior wellness and cancer patient support. Her teaching emphasizes bridging technical capabilities with ethical responsibility, preparing students for roles in cybersecurity management and data-driven decision-making. Current research explores AI's role in achieving UN Sustainable Development Goals through triple-bottom-line approaches.

• Information Retrieval
• Computational Linguistics
• Knowledge Graphs
• +۵ مورد دیگر

Pei-Chi Lo serves as Assistant Professor in the Department of Information Management at National Sun Yat-sen University (NSYSU), Taiwan, where she leads research at the intersection of information retrieval, computational linguistics, and user profiling. Her work leverages knowledge graphs and large language models to advance contextual understanding systems and social media analysis. Education: PhD in Computer Science, Singapore Management University (supervised by Prof. Ee-Peng Lim) Research Focus: Dr. Lo pioneers knowledge-based information retrieval systems including contextual path generation and knowledge graph reasoning. Her computational linguistics work spans task-specific language models, Singlish (English Creole) processing, and LLM-based knowledge extraction. User profiling research examines behavior-based modeling, adaptive crowdsourcing, and social media personality analysis through community-specific language features. Publication Trends: Her 14 publications (2017-2025) reveal evolving expertise from foundational knowledge graph embeddings to contemporary LLM integration. Recent work (2023-2025) emphasizes causal reasoning with LLMs, judicial document analysis, and temporal knowledge discovery, while maintaining core strengths in contextual retrieval and low-resource language processing. Academic Leadership: Dr. Lo advises 8 Master's students across 2024-2025 cohorts and supervises undergraduate research teams. She has secured multiple competitive grants including NSTC projects on LLM-based causal reasoning (2025-2027) and temporal knowledge discovery (2024-2026), plus institutional funding for sustainable e-commerce and elderly care technology initiatives. Laboratory: Her NSYSU research lab actively recruits students for projects spanning judicial reasoning analysis, personalized travel planning systems, and Singlish processing tools, maintaining strong industry and community engagement through practical NLP applications.

Cicero Eduardo De Sousa Walterمشاهده پروفایل

استادیار

• Innovation Management
• Business Management
• Organizational Behavior
• +۳ مورد دیگر

Cicero Eduardo De Sousa Walter is an Assistant Professor of business and management at the Federal Institute of Education, Science and Technology of Piauí (Brazil) , with affiliations to the University of Aveiro (Portugal) through the GOVCOPP research unit (Governance, Competitiveness, and Public Policy). He holds a Ph.D. in Business and Economics from the University of Aveiro and Master's and Specialization degrees in Management from the Polytechnic Institute of Bragança (Portugal). His research focuses on Innovation Management, Business Management , and Organizational Behavior , with a particular interest in innovation dynamics in small enterprises, consumer behavior, and education-related studies. He has received scientific awards for his research. His work spans institutions in Brazil and Portugal, emphasizing empirical analyses of innovation drivers, licensing models, and educational outcomes. Recent publications highlight trends in machine learning applications for patent licensing, Generation Z's privacy concerns , post-pandemic retail strategies , and innovation policy . Collaborations with researchers like Manuel Au-Yong-Oliveira and Cláudia Veloso reflect cross-institutional partnerships. His affiliations include the Competitiveness, Innovation, and Sustainability (CIS) research group and profiles in SCOPUS, Web of Science, and other academic indexers. Scientific awards include recognition for research contributions in business management and innovation. His work bridges quantitative and qualitative methodologies , with a focus on Portuguese and Brazilian contexts .

• AI Security
• Cybersecurity
• Artificial Intelligence
• +۱۲ مورد دیگر

Petar Radanliev is a part-time academic and project supervisor at the Department of Computer Science, University of Oxford. He is actively involved in teaching and research, focusing on AI security, cybersecurity, and emerging technologies such as quantum computing and blockchain. His work bridges academic rigor with practical industry applications, and he supervises professional masters students. His research interests center on the security and ethical implications of artificial intelligence. Key areas include AI attack surfaces, agentic AI, quantum AI, malware analysis, and responsible AI practices. He explores vulnerabilities in machine learning systems and develops frameworks for secure and resilient AI deployment. His recent publications and courses reflect a strong trend toward interdisciplinary integration of AI with blockchain and quantum computing, emphasizing real-world threats, ethical considerations, and future-proofing digital systems. These works highlight a consistent focus on proactive defense, red teaming, and the societal impact of emerging technologies. Fulbright Fellowship Prince of Wales Innovation Scholarship Petar Radanliev has supervised numerous professional masters students and contributes to academic discourse through extensive publications, books, and public lectures. He is affiliated with major research platforms including ORCID, Google Scholar, and the Alan Turing Institute. His teaching includes advanced courses on AI security, quantum AI, and red teaming, often delivered through recorded events and online platforms. He is associated with research themes in Security, Artificial Intelligence, and Machine Learning at Oxford, and has contributed to projects such as SOCIAM. His work emphasizes practical, actionable insights for professionals and academics navigating the evolving landscape of AI and cybersecurity.

• Big data
• Data science
• Data analytics
• +۱۲ مورد دیگر

Paolo Garza is an Associate Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he also serves as Coordinator of the College of Computer, Film and Mechatronics Engineering. He is a member of the DBDM research group and the SmartData@PoliTO laboratory, and actively contributes to academic governance through roles in teaching coordination and PhD program committees. Education: Bachelor’s in Computer Engineering, Polytechnic University of Turin (2001) PhD in Computer and Systems Engineering, Polytechnic University of Turin (2005) His research centers on data science, big data analytics, data mining, and machine learning , with applications in emergency management, real-time communications, Earth observation, and cybersecurity. He has led and participated in numerous national and commercial research projects, including AI4CTI and NODES (PNRR), and has collaborated with industry partners like Cisco Systems. His work bridges theoretical algorithm development and practical deployment in critical systems. The recent publications reflect a strong trend toward multimodal AI, crisis informatics, and intelligent networking . Articles span computer vision for environmental monitoring (e.g., burned area detection, canopy estimation), ML for real-time communication quality, multimodal document understanding, and crisis response systems. His team leverages deep learning, transformers, and vision-language models across diverse domains. Scientific Service: Associate Editor, Knowledge and Information Systems (2024–) Associate Editor, Expert Systems with Applications (2022–) General Co-Chair, IEEE AICT Conferences (2022, 2023) He mentors several PhD students and leads funded research initiatives focused on AI for sustainable industry and cyber threat intelligence. His teaching includes graduate courses on big data processing, distributed architectures, and data science lab methods. He has also directed commercial training programs and research contracts in machine learning and cybersecurity. Research Labs & Teams: DBDM - Database and Data Mining Group (DAUIN) SmartData@PoliTO - Big Data and Data Science Laboratory LAB 5 - Research Laboratory (DAUIN)

Victor M. Montoriمشاهده پروفایل

استاد

• Evidence-Based Medicine
• Shared Decision-Making
• Minimally Disruptive Medicine
• +۱۲ مورد دیگر

Victor M. Montori is a Professor of Medicine at Mayo Clinic, Rochester, MN, with primary appointments in the Division of Endocrinology, Diabetes, Metabolism, and Nutrition, and a joint appointment in the Division of Health Care Policy & Research, Department of Quantitative Health Sciences. He conducts research in the Knowledge and Evaluation Research (KER) Unit, focusing on evidence-based medicine, shared decision-making, and minimally disruptive medicine. MD: Universidad Peruana Cayetano Heredia MS in Biomedical Research: Mayo Clinic Graduate School of Biomedical Sciences Fellowship in Clinical Epidemiology: McMaster University Fellowship in Human Rights and Technology: Harvard Kennedy School Dr. Montori's research centers on improving healthcare delivery for patients with chronic conditions by aligning treatment with patient values and reducing treatment burden. His work emphasizes knowledge synthesis through systematic reviews and meta-analyses, and the development of patient-centered care models. He advocates for shared decision-making as a method to enhance patient autonomy and care quality. The recent articles highlight a strong trend in patient-centered methodologies, including shared decision-making tools, treatment burden measurement, and the Core GRADE approach for evidence evaluation. His research spans diabetes, heart failure, and broader chronic disease management, with increasing focus on mental health integration and healthcare worker burnout. Member, Editorial Advisory Board, The BMJ (2012–present) Member, National Advisory Council, AHRQ (2012–2015) Chair, International Shared Decision Making Conference (2013) Robert H. and Susan M. Rewoldt Professor of Endocrinology, Mayo Clinic (2023) Most Cited Researcher in Clinical Medicine, Thomson Reuters (2014) Outstanding Mentor Award, Mayo Clinic (2013) Dr. Montori has served as Co-PI on NIH-funded projects such as QBSafe, which aimed to improve care for older adults with type 2 diabetes. He has advised numerous trainees and led initiatives in medical education, including clinical teaching and mentorship. His leadership extends to national and international advisory boards, including the Patient-Centered Outcomes Research Institute (PCORI) and the International Society for Evidence-based Health Care. He is actively involved in the Minnesota Shared Decision Making Collaborative and has contributed to guideline development through The Endocrine Society. His research is conducted within the Knowledge and Evaluation Research Unit, a multidisciplinary team focused on generating and implementing evidence in clinical practice. The unit collaborates across Mayo Clinic’s Centers for Clinical and Translational Science (CCaTS), Biomedical Ethics Research Program, and the Kogod Center on Aging. Dr. Montori also contributes to global efforts in evidence-based medicine through advisory roles with institutions like McMaster University and the Polish Evidence-based Medicine Center.

• Data Science
• Mobility Data Management and Mining
• Knowledge Discovery in Data (KDD)
• +۴ مورد دیگر

Professor Nikolaos Pelekis is a faculty member at the University of Piraeus, Greece, holding the position of Professor in the Department of Statistics and Insurance Science within the School of Finance and Statistics. His academic career focuses on Data Science, with a specialized emphasis on Mobility Data Management and Mining, a field he has contributed to for over two decades. He has authored two monographs and over 100 peer-reviewed articles, earning five Best Paper Awards and over 5,000 citations. Research Interests: Mobility Data Management and Mining Big Data Analytics Machine Learning Geographical Information Systems His work spans trajectory analysis, maritime and vessel traffic forecasting, and spatiotemporal data management. Notable projects include leading roles in EU-funded initiatives like GREEN.DAT.AI and EMERALDS, focusing on energy-efficient AI and urban mobility analytics. Awards and Recognition : Five Best Paper Awards, including the Ralf H. Güting Best Research Paper Award (2021) and Best Demo Paper Awards at SIGSPATIAL (2021). He also ranked 1st in the SemEval-2017 Task 4 for sentiment analysis. Professional Contributions : Serves on editorial boards (e.g., ECML PKDD, DMKD) and organizes workshops like BMDA. His teaching spans undergraduate and graduate courses in Data Science, Big Data Management, and Statistical Data Mining. Labs and Teams : Co-founder of the Data Science Lab at the University of Piraeus, collaborating across 4 departments and multiple researchers. Current efforts include maritime digitalization (VesselAI) and real-time trajectory prediction frameworks like ARGO.

• Cloud Computing Economics
• Software Service Platforms
• IT Service Economics
• +۶ مورد دیگر

Jörn Altmann is a Professor in the Department of Computer Science and Engineering at Seoul National University's College of Engineering. With a publication history spanning over three decades from 1994 to 2025, he has established himself as a leading researcher in the economics of computing services, particularly focusing on cloud computing economics, software service platforms, and IT service ecosystems. He has served as editor for the GECON (Economics of Grids, Clouds, Systems, and Services) conference proceedings for multiple years, demonstrating his leadership in the field. Altmann's research interests center on the economic aspects of computing infrastructure, with particular expertise in cloud federation models, resource allocation mechanisms, and the business dynamics of software service ecosystems. His work bridges technical computing concepts with economic theory, examining how market mechanisms can be applied to computing resource allocation. Recent research has expanded into cybersecurity economics, AI adoption frameworks, and knowledge management in distributed systems environments. His publications consistently explore the intersection of technology adoption patterns and economic incentives within computing ecosystems. Analysis of his recent publications reveals a strong focus on cloud federation architectures, trust mechanisms in cybersecurity information sharing, and the economic modeling of value creation in distributed computing environments. His work demonstrates a methodological diversity, employing game theory, agent-based modeling, systematic literature reviews, and empirical analysis of industry dynamics, particularly in the Korean technology sector. Altmann has collaborated extensively with researchers worldwide, with notable long-term collaborations with José Ángel Bañares, Omer F. Rana, Kurt Vanmechelen, and Korean researchers including Kibae Kim. His work has appeared in prestigious venues including Future Generation Computer Systems, IEEE Transactions on Engineering Management, and the GECON conference series which he has helped shape through editorial leadership. His research has practical implications for cloud service providers, enterprise IT strategy, and policy development in digital infrastructure. The consistent publication record and editorial leadership suggest active supervision of graduate students and research teams, though specific students are not documented in the provided publication records.

Dilum Bandaraمشاهده پروفایل

عضو هیئت علمی

• Distributed Systems
• Blockchain
• Cloud Computing
• +۱۳ مورد دیگر

Dilum Bandara is a Principal Research Scientist at CSIRO's Data61 in Australia and an Adjunct Senior Lecturer at the School of Computer Science and Engineering, Faculty of Engineering, University of New South Wales (UNSW). He has previously served as a Senior Lecturer at the University of Moratuwa, Sri Lanka, and has over two decades of experience in research, teaching, and consultancy in distributed systems, security, and software engineering. His academic qualifications include: PhD in Computer Science, Colorado State University, USA (2012) MS in Computer Science, Colorado State University, USA (2008) BSc Eng. (Hons) in Computer Science and Engineering, University of Moratuwa, Sri Lanka (2004) Dilum's research interests are centered on Distributed Systems (Blockchain, Cloud, P2P), Computer Security , Software Architecture , Data Engineering , Performance Engineering , and the Internet of Things (IoT) . He applies these technologies in multidisciplinary domains such as Supply Chains , Digital Finance , Environmental, Social, and Governance (ESG) , Fleet Management , and Weather Monitoring . His work emphasizes real-world impact through trusted data management in multi-party ecosystems. The analysis of his recent publications reveals a strong focus on blockchain for transparency and security, cloud-native performance engineering, IoT integration with edge and cloud, and data-driven solutions for smart cities and sustainability. His work consistently bridges theoretical innovation with practical deployment, particularly in national and international infrastructure projects. His scientific awards include: Best Paper Award at BPM 2024 Multiple CSIRO internal awards (Customer First, Engineering and Technology, Collaboration) from 2021–2023 Student Paper Award (Merit) at IEEE SOLI 2018 Award of Excellence for Outstanding Research at University of Moratuwa (2015–2018) Dilum has led and contributed to several research grants, particularly during his time at the University of Moratuwa, including projects on smart city integration, real-time data forecasting, and cloud platforms for scientific computing. He has also held leadership roles such as Director of the Engineering Research Unit and co-founder of VaticHub. He is actively involved in professional communities as a Senior Member of IEEE and a Chartered Engineer with IESL. At CSIRO, he serves as a Health and Safety Representative, reflecting his commitment to corporate citizenship. He has advised students and early-career researchers, though specific names are not listed in the provided text. His labs and research teams include the Architecture and Analytics Platforms (AAP) team at CSIRO Data61 and collaborations with academic institutions like UNSW and University of Moratuwa.

• Machine Learning
• Case-Based Reasoning
• Natural Language Processing
• +۳ مورد دیگر

Nirmalie Wiratunga is a Professor in Intelligent Systems at the School of Computing , Robert Gordon University, and serves as the Associate Dean for Research . She is also an Adjunct Professor at the Norwegian University of Science and Technology (IDUN program). Her academic excellence spans over two decades in Artificial Intelligence and Machine Learning , with a focus on Explainable AI (XAI) , Case-Based Reasoning (CBR) , and Natural Language Processing (NLP) . Her research explores innovative methodologies for knowledge-rich representations to automate decision-making through CBR for Retrieval-Augmented Q&A systems and human-centered AI platforms . She co-founded Attendr.app , a spinout for student and conference attendance tracking, and leads the Artificial Intelligence & Reasoning Research Group at RGU. Recent publications (2024–2025) highlight her work on LLM hallucination detection , counterfactual explanations in finance , cross-lingual biomedical review automation , and multi-query resolution in legal domains . Themes span AI explainability , NLP , CBR , and domain-specific knowledge integration across healthcare, law, and education. Her leadership extends to organizing international workshops on XAI , digital health , and Deep Learning , and co-chairing the ICCBR 2021 and 2022 conferences. She actively contributes to program committees for ECCBR , ECML/PKDD , and IJCAI .

Gyunam Parkمشاهده پروفایل

پژوهشگر

• Process Mining
• Action-Oriented Process Mining
• Object-Centric Process Analysis
• +۱۲ مورد دیگر

Gyunam Park is a Research Group Lead and Process and Data Scientist at Fraunhofer FIT and a Scientific Assistant at the Chair of Process and Data Science at RWTH Aachen University, a leading institution in computer science and engineering. He is actively involved in both research and teaching, contributing to the advancement of process mining, data science, and artificial intelligence. His work bridges academic research and industrial applications, particularly in SAP ERP systems and digital twins of organizations. Research Interests: Gyunam Park’s research focuses on Action-Oriented Process Mining (AOPM) , Object-Centric Process Analysis , and Responsible Machine Learning . He aims to transform process mining insights into actionable management decisions, ensuring transparency, fairness, and compliance. His work enables organizations to monitor operational constraints, generate corrective actions, and assess their impact using data-driven methods. Publication Trends: His recent publications emphasize object-centric approaches to process mining, predictive monitoring, constraint checking, and integration with AI planning. There is a strong trend toward preserving structural information in event logs, improving machine learning performance, and applying these techniques to real-world systems like SAP ERP and after-sales service processes. Scientific Awards: No awards are explicitly mentioned in the provided text. Advising and Grants: While no formal students are listed, Gyunam Park leads research projects and collaborates with industry partners such as Samsung Electronics and SAP. His projects involve root cause analysis, resource optimization, and educational data mining. He has developed open-source tools like ProAct and OCPA , indicating active grant or institutional support for software development and research dissemination. Labs and Teams: He is a core member of the Process and Data Science (PADS) group led by Prof. Wil van der Aalst at RWTH Aachen University and leads a research group at Fraunhofer FIT. These teams focus on cutting-edge research in process mining, data science, and AI, with strong industry collaborations and regular contributions to top conferences and journals.

Tingting Liمشاهده پروفایل

مدرس

• AI for Cyber Security
• Automated Cyber Defence
• Diversification and Deception Strategies
• +۸ مورد دیگر

Dr. Tingting Li is a Lecturer (Assistant Professor) in Cyber Security at Cardiff University's School of Computing and Informatics and a member of the Centre for Cyber Security Research. She also holds an Honorary Research Fellow position at Imperial College London, reflecting her ongoing research collaboration. Her work bridges artificial intelligence and cybersecurity, with a focus on protecting critical systems such as cyber-physical systems (CPS), industrial control systems (ICS/SCADA), and autonomous vehicles. BEng (Hons) in Information Security, Xidian University, China MSc in Computing, Imperial College London PhD in Artificial Intelligence, University of Bath Dr. Li’s research interests lie at the intersection of AI and cybersecurity, particularly in automated cyber defense , diversification/deception strategies , and symbolic AI for knowledge representation . She investigates how AI can enhance the resilience of critical infrastructures through intelligent, adaptive defense mechanisms. Her recent work explores quantum-inspired reinforcement learning and machine learning models for proactive threat mitigation in complex systems. Her recent publications demonstrate a strong trend in applying advanced AI techniques—especially deep reinforcement learning, LSTM networks, and Bayesian models—to cybersecurity challenges in industrial and autonomous systems. These works span domains like IoT malware suppression, network diversity for ICS resilience, and automated compliance checking, reflecting a multidisciplinary approach combining security, AI, and systems engineering. Dr. Li has secured significant research funding, including a grant from the Alan Turing Institute (2024–2025) on AI safety in autonomous cyber defense, a RITICS/NCSC-funded project on diversity-based cybersecurity (2021–2022), and an EPSRC-funded project on metric-driven cybersecurity frameworks for critical national infrastructure (2021–2023). She actively supervises PhD students in areas including cybersecurity for autonomous vehicles, moving target defense, and cyber-physical system security. Her team includes Iryna Bernyk, Sanyam Vyas, Victoria Marcinkiewicz, Ellis Doran, Stephen Morris, and Sam Braithwaite. She also leads teaching modules on databases (CM6125/CM6625) and cybersecurity (CM6224/CM6724). Dr. Li’s research is conducted within the Centre for Cyber Security Research at Cardiff University, where she collaborates with experts in AI, security, and critical infrastructure protection. Her work is highly interdisciplinary, involving partnerships with institutions like Imperial College London and funding bodies such as EPSRC, NCSC, and the Alan Turing Institute.