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.

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.

Alireza Ghasempour has extensive experience in research, teaching, and leadership positions. His areas of interest include smart grids, Internet of Things, artificial intelligence, and optimization techniques. He has published a book chapter and several papers in peer-reviewed journals and at conferences.

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.

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.

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.