Dr. Jolanta Tańcula is an expert in computer science and mathematics, specializing in technical sciences and cybersecurity. She earned a PhD in Computer Science from the Polish Academy of Sciences in 2014, following master’s degrees in both Mathematics and Computer Science. Since 2018, she has served on the Scientific Committee for the International Conference on Applied Informatics (ICDD). Her international experience includes lecturing on distributed systems at Hochschule Ostwestfalen-Lippe in Germany and advanced security training at Graz University of Technology in Austria. Most recently, she contributed to the CyberEva project, where she developed a proprietary evaluation system for IoE/IoT cybersecurity.

Laijun Lu, Professor and Doctoral Supervisor at Jilin University, Chief Scientist of the Digital Earth Research Center. His research focuses on mathematical geosciences, mathematics and systems science. He has published nearly one‑hundred papers, six monographs, and holds six patents and software copyrights. He has received multiple national and provincial‑level academic awards and was honored as “Science Chinese Person of the Year 2012”. He holds several part‑time academic positions across Chinese universities and research institutions. His current research centers on complex‑system chaotic‑spectrum theory and pan‑quantum theory, developing novel algorithms for spatial‑data intelligent computing, natural‑event simulation, biomedical analysis and socio‑economic system early‑warning.

Cong Wang received the B.S. degree in automation and the M.S. degree in mathematics from Hohai University, Nanjing, China, in2014 and 2017, respectively, and the Ph.D. degree in mechatronic engineering from Xidian University, Xi’an, China, in 2021. He is currently an associate professor with the School of Mathematics and Statistics, Northwestern Polytechnical University, Xi’an, China. He was a visiting Ph.D. student with the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada, and the Department of Electrical and Computer Engineering, National University of Singapore, Singapore.
He was also a research assistant with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. His current research interests include intelligent machine vision, high-dimensional image analysis, as well as fuzzy theory and its applications. He currently has a textbook, a monograph, 10+ patents and more than 60papers (30+ in IEEE Transactions) and hosts over 10 research projects. He is funded by the China National Postdoctoral Program for Innovative Talents and the Excellent Chinese and Foreign Youth Exchange Program of the China Association for Science and Technology.
He is an editorial board member of 10+ international journals, including IEEE Transactions on Fuzzy Systems and a program committee chair, track chair, publication chair, publicity chair, program committee member, and technical committee member of 60+ international conferences. He also serves as a frequent reviewer of 70+international journals, including a number of the IEEE Transactions and many international conferences.

Fabrizio Degni is a distinguished AI Ethics and Governance researcher, technology evangelist, and President of the Italy Chapter for the Global Council for Responsible AI. Guided by his philosophy "Ask not if it can be done, nor how, but only if it should be done," he is deeply committed to exploring technological frontiers while ensuring AI serves humanity's common benefit through ethical, transparent, and accountable innovation.
Recent Recognition & Leadership: Degni was honored with the "Premio per l'Impegno Etico nella Cultura Algoritmica" (Award for Ethical Commitment in Algorithmic Culture) at the inaugural AI Awards Italy 2025, hosted by ENTE NAZIONALE per l'INTELLIGENZA ARTIFICIALE - E.N.I.A.® in Milano. This prestigious recognition celebrates his commitment to education and critical reflection on algorithms, ethics, and AI governance. As President of the Italy Chapter for the Global Council for Responsible AI, he leads a growing community of 500+ members across 71 nations dedicated to shaping responsible AI through ethics, transparency, and accountability principles.
Professional Expertise: As Chief of Artificial Intelligence, Degni's research focuses on sociotechnical risks introduced by emerging AI technologies, particularly AI agents and autonomous systems. His analysis of AI agent systems in IBM's 2025 AI Ethics Report highlighted critical challenges of opacity, complexity, and non-reversibility in autonomous systems, contributing to frameworks for evolved governance models and ethical oversight. Degni is the author of the book “Tecnologia senza paura” and the founder of the online policy watcher portal PolicyWatcher.online also.
Certifications & Credentials: Degni holds the Chief AI Officer certification from World X University (scored 100 / 100), AI CERTs™: AI+ Executive Certification (scored 90/100, May 2025) and specialized certifications from Stanford University ("AI Awakening: Economic and Society Implications"), edX ("AI Ethics for Professionals"), Copenhagen Business School, Microsoft, and Politecnico di Milano. His advanced credentials include ISO 42001:2023 AI System Management / ISO 9001 certifications and designation as a Certified AI Ethics & Governance Professional (CAEGP).
Thought Leadership: A frequent speaker and panel participant, Degni recently contributed to the "Alfabetizzazione e Innovazione" (Digital Literacy and Innovation) panel, discussing human and digital memory alongside leading experts. His work encompasses value alignment, bias mitigation, transparency, and actionable governance frameworks for AI implementation across multiple sectors.

Dr. Yilun Shang received his B.S. and Ph.D. degrees in Mathematics from Shanghai Jiao Tong University, China, in 2005 and 2010, respectively. He is an Associate Professor at Northumbria University, UK. His research interests include complex networks and systems, probability and analysis, algebra and combinatorics, optimization and control, data science and artificial intelligence.

TianXiang Yue has completed his PhD from Chinese Academy of Sciences, China and postdoctoral studies from Helmholtz Centre for Environmental Research – UFZ, Germany. His research interests include quantum machine learning on eco-environmental surfaces and eco-environmental informatics. Since 2001, he, as a Professor, has been working at Institute of Geographical Sciences and Natural Resources Research and since 2018, chairing Eco-Environmental Informatics at University of Chinese Academy of Sciences.

Dr Jixin Ma is a Full Professor of Computer Science (Artificial Intelligence) and the Director of PhD/Postgraduate Research Programme in the School of Computing and Mathematical Sciences at University of Greenwich, U.K. He has been the Director of the Centre for Computer and Computational Science and the Lead of Artificial Intelligence Research Group. Professor Ma is also a Visiting Professor of Beijing Normal University, Hainan University, Anhui University, Zhengzhou Light Industrial University and Macau City University.

Professor Ma obtained his BSc and MSc of Mathematics in 1982 and 1988, respectively, and PhD of Computer Sciences in 1994. His main research areas include Artificial Intelligence, Data Science, and Information Systems, with special interests in Temporal Logic, Information Security, Machine Learning, Case-Based Reasoning and Pattern Recognition. Professor Ma has been a member British Computer Society, American Association of Artificial Intelligence, ACIS/IEEE, World Scientific and Engineering Society, and Special Group of Artificial Intelligence of BCS.

He has also been the Editor of several international journals and international conference proceedings, Conference/Program Chair, and Invited Keynote Speakers of many international conferences. Professor Ma has published more than 200 research papers in peer-reviewed international journals and conferences.

Dr. Bradley Fowler earned a Master of Public Policy in Cybersecurity Policy from American Public University System-Summa Cum Laude; Master of Science in Cybersecurity and Master of Science in Managing Information Systems in Information Security Management both from Bellevue University-Summa Cum Laude. He also earned a Master of Arts in Teaching and Learning with Technology-Summa Cum Laude, Bachelor of Arts in eMarketing-Cum Laude, and Master of Science in Technology Management-Magna Cum Laude, all from University of Arizona Global Campus, a Master of Science in Cloud Computing Architecture from University of Maryland Global Campus-Magnum Cum Laude and a Graduate Certificate in Information Assurance from University of Maryland Global Campus. Dr. Bradley is currently is completing his dissertation research for a Doctor of Education Administration at California Coast University.

In December 2024, Dr. Bradley conferred with a Ph.D. in Cybersecurity Leadership at Capitol Technology University. And is now writing his dissertation for a Doctor of Management in Information Systems and Technology at University of Phoenix.

In December 2023, Dr. Bradley completed a Graduate Certificate in Human Resource Management from Wilmington University.

Dr. Bradley is a member of Golden Key International Honour Society, National Society of Leadership and Success, National Cybersecurity Alliance, and the National Cybersecurity Student Association. He was a contributing writer for the National Security Policy Analysis Organization until April 2023, and general member of the American Public University System Alumni Council.

Dr. Bradley is co-author of Cybersecurity Public Policy SWOT Analysis for 43 Countries-Routledge Taylor & Francis & CRC Press, author of AWS for Public and Private Sector Cloud Computing Architecture for Government and Business-Apress, Information Assurance Risk Management Strategies for Managing Information Systems and Tools in the Cloud-Apress, Cybersecurity Leadership for Healthcare Organizations and Institutions of Higher Education-River Publishers, and Technology Management, Artificial Intelligence, and Machine Learning Strategies to Improve Technology Integration and Usage in the Workplace Strategies to Increase Leverage Over Competitors and Control Internal and External Risk Factors-River Publishers.

Kaustav Saha is a Senior Staff AI Engineer/Architect at Zscaler, where he builds production-scale multilingual ML detectors deployed across 28+ languages for the Eclipse AI Guard cybersecurity platform. He has filed 5 US AI patents and authored 5 technical white papers from his work at Zscaler, with two publications already available on the Technical Disclosure Commons.
He is the co-author of Advanced LLM Engineering for Non-Latin Languages (2026) and serves on the editorial boards of the IEEE Conference on Engineering Informatics and the International Computer Sciences and Informatics Conference. With 15+ years of experience spanning Cisco, eBay, Cowbell Cyber, and Credit Acceptance, Kaustav holds a B.Tech/M.Tech in Computer Science from IIT Kharagpur, an MS in Data Science (4.0 GPA) from the University of Virginia, and an MBA from UC Berkeley's Haas School of Business. He also serves on the Board of Directors of aifashionweek.ai, a Bay Area AI startup.

Chisom Elizabeth is a cybersecurity and AI/ML professional and researcher with extensive experience securing digital infrastructure and advancing intelligent threat-detection technologies. With more than 40 academic publications, her work explores the application of artificial intelligence, machine learning, and automation to strengthen cyber resilience and address evolving security challenges.
Her expertise includes developing and evaluating machine-learning models for cyber-threat detection, analyzing algorithmic performance, and optimizing AI/ML methodologies for real-world applications. Her research is driven by an interest in translating technical innovation into practical, scalable, and data-driven solutions while advancing the responsible application of AI and machine learning.

Wejeyan Nyerovwo Felix, an independent researcher, technology entrepreneur, and founder of HashTagPrograms whose work focuses on artificial intelligence, contextual reasoning, multi-agent systems, and computational knowledge representation. His research explores how AI systems can move beyond statistical pattern matching by incorporating structured contextual awareness, enabling more coherent reasoning, adaptive decision-making, and collaboration across complex environments.

He is currently developing Contextual Calculus, a proposed framework for modeling context as a dynamic computational state that evolves through semantic relationships and contextual transitions. His interests include explainable AI, agentic systems, contradiction-aware reasoning, contextual memory architectures, and adaptive multi-agent intelligence, with the long-term goal of contributing to the development of more transparent, resilient, and context-aware AI systems.

Lead enterprise AI portfolio strategy integrating machine learning and advanced analytics across insurance business functions. Direct large-scale AI and cloud transformation programs supporting risk assessment, fraud detection, and financial analytics platforms. Implement responsible AI governance frameworks aligned with regulatory standards, including NAIC and data privacy requirements. Manage cross-functional teams delivering enterprise AI platforms across multiple business units.

PROFESSIONAL SUMMARY

AI and machine learning leader with 20+ years of experience delivering enterprise-scale intelligent systems in the insurance and financial services sectors. Specializing in responsible AI, generative AI governance, and large-scale AI transformation programs across underwriting, claims, fraud detection, and risk analytics. Active researcher in generative AI safety with work focusing on the integration of Retrieval-Augmented Generation (RAG) architectures with guardrails frameworks to improve trustworthiness and reliability of large language models in enterprise environments.

KEY CONTRIBUTIONS

Led enterprise AI strategy initiatives integrating machine learning and generative AI across insurance operations, including underwriting, claims, and fraud detection. Conducted research on the integration of Retrieval-Augmented Generation (RAG) with guardrails frameworks to mitigate hallucinations in enterprise LLM systems. Developed evaluation approaches for LLM reliability, hallucination reduction, and responsible AI deployment in regulated industries. Led cross-functional AI initiatives involving data science, engineering, legal, and compliance teams to deploy responsible AI frameworks aligned with regulatory requirements.

Ravi Mandal is a Ph.D. Scholar at the Hindustan Institute of Technology & Science in Bangalore, India. His research focuses on the intersection of data integrity and automated governance. Specifically, his interests include the development of scalable frameworks for data quality assurance, the application of unsupervised machine learning for outlier analysis, and the optimization of data pipelines in enterprise environments. His current work aims to reduce manual intervention in data validation through advanced statistical profiling and anomaly detection engines.

Afolabi Abeeb is a Machine Learning Engineer, Language AI Specialist, and NLP Researcher with a passion for advancing artificial intelligence for low-resource African languages. He currently serves as the Head of Language AI at Plotweaver AI, where he leads the research and development, of multilingual AI solutions, including speech recognition, machine translation, text-to-speech systems, and real-time language technologies.

Abeeb is currently pursuing a Master's degree in Computer Engineering at Ladoke Akintola University of Technology (LAUTECH), Nigeria. His expertise spans Natural Language Processing (NLP), Automatic Speech Recognition (ASR), Text-to-Speech (TTS), Machine Translation, Large Language Models (LLMs), and deep learning, with a strong focus on building scalable AI systems for under-resourced languages.

His research contributions include pioneering work on Nigerian Pidgin speech recognition, African language machine translation evaluation, and multilingual text classification. His work has been presented at leading international venues, including NAACL, NeurIPS, ICLR, Deep Learning Indaba, and AfricaNLP. In addition to his research, he is an active AI educator, speaker, and community leader, having delivered talks and workshops on AI, language technologies, and GPU-accelerated computing at PyCon Africa, IndabaX, TensorFlow meetups, and other technology communities across Africa.

Through his research, leadership, and community engagement, Abeeb is committed to developing inclusive AI technologies that bridge language barriers and expand digital access for underserved communities worldwide.

Virginia Association of Criminal Justice Educators and Editorial Board Member Journal of Forensic Practice