Scott Askinosie specializes in intent-driven context engineering for autonomous AI systems at scale. With a Ph.D. in Quantitative Biology and 7+ years of applied ML experience, Scott bridges the gap between cutting-edge research and production-grade agentic systems.

He has delivered 20+ technical workshops to Fortune 500 enterprises including NATO and Fannie Mae, architecting multimodal RAG systems and agentic orchestration frameworks that power real-world deployments. His work focuses on transforming complex AI concepts into actionable implementations for mission-critical systems.

Francisco Vidal is a Principal Data Scientist and AI Strategist currently leading innovation at Puerto San Antonio. He is the Founder & CEO of xSingular, where he develops xStryk, a Decision Intelligence platform integrating knowledge graphs and autonomous agents.

With a strong focus on Deep Tech, Francisco specializes in transforming complex industrial data into actionable strategic simulations. His work enables organizations to make smarter, data-driven decisions in highly complex environments.

Olger Huamani Jordan is a RENACYT-certified researcher and professor specializing in education, language, and digital transformation in learning systems.

He has published in leading journals such as BMC Psychology, Computers & Education: Artificial Intelligence, and Social Sciences & Humanities Open, focusing on AI in education, digital inclusion, and academic innovation.

His work explores how machine learning and emerging technologies can enhance teaching methodologies, improve curriculum design, and support adaptive, intelligent learning environments for the future.

Jacob Yates, Ph.D. is a Teaching Assistant Professor and Walton AI Fellow at the Sam M. Walton College of Business, University of Arkansas.

His teaching focuses on business analytics, information systems, data visualization, and the practical application of AI in business education.

As a Walton AI Fellow, he leads initiatives in AI integration across teaching, curriculum development, and faculty support, creating scalable and responsible AI-enabled learning experiences.

He has developed innovative programs including an AI in Business honors course, AI-enhanced analytics projects, and hands-on learning models that help students effectively apply AI in real-world business contexts.

Mina G. G. Helkany is the Head of Data Science at Trolley, leading data and AI initiatives across Kuwait and KSA. With over 20 years of experience in data engineering, analytics, and machine learning, he specializes in building end-to-end data ecosystems and deploying AI solutions into real business operations. Mina has led large-scale digital transformation projects across retail and oil & gas, focusing on turning data into actionable decision systems that drive revenue and operational efficiency.

Tiago Albineli Motta is a Software Engineer and AI/Data Scientist with over two decades of experience building scalable, production-ready systems. Currently a Principal Software Engineer at Will Bank, he focuses on combining deep technical execution with advanced data intelligence to deliver measurable business outcomes. His work centers on transforming complex data challenges into real-world solutions that drive user growth, improve conversion rates, and create tangible business impact.

Olena Kasian is a PhD researcher in Management at Sumy State University (Ukraine) and the founder of OKTOWN, a digital marketplace for tourism services. Her work focuses on the integration of AI technologies, digital transformation, and sustainable development in tourism. She specializes in developing innovative models for small and medium-sized tourism businesses, with a strong emphasis on accessibility and the silver economy across Ukrainian and European contexts.

Daniela Schulz is a Senior Editor at Deutsche Welle, working at the intersection of journalism, culture, and responsible AI. She focuses on human‑centered AI adoption in editorial environments, with a particular interest in ethics, cultural context,and global perspectives. Her work bridges newsroom practice and strategic thinking, exploring how AI can support human judgement in storytelling.

Okechukwu Nicholas is a Solutions Architect and AI Researcher focused on building scalable, responsible AI systems. He is passionate about bridging AI research and practical, ethical applications.

Jessica Montgomery is a Cloud Computing Engineer Lead at SAIC with experience in cloud modernization, AI governance, and the responsible adoption of AI in regulated environments.

Her work focuses on translating AI strategy into practical controls, operational risk management, and implementation pathways that technical and business teams can actually use.

She is currently pursuing a Doctor of Computer Science in AI and Big Data Analytics, with research interests in AI governance, secure data environments, and enterprise AI adoption.

Katherine Zhao is an AI strategist working at the intersection of business, governance, and emerging technology. She combines experience from Boston Consulting Group, Harvard Kennedy School, and AI startups to help organizations translate cutting-edge AI into practical, responsible business solutions.

Her work spans AI governance, digital transformation, and media strategy. Most recently, she developed an enterprise AI governance framework for DoorDash, while also leading growth and strategy for a Y Combinator-backed AI filmmaking startup focused on the future of creative AI.

At Harvard Kennedy School, Katherine specializes in AI policy and data-driven decision making, with research in AI governance, digital platforms, and public trust. She is particularly interested in how organizations can build AI systems that are both scalable and accountable while balancing innovation with human impact.

InChan Hwang is an Assistant Professor of Data Science and Cybersecurity at Montreat College. His research focuses on applying deep learning and machine learning across medical imaging and financial data analysis.

In medical imaging, his work explores how training data composition impacts model performance and fairness across demographic groups, with a strong focus on AI-driven breast cancer screening and mammography analysis.

He also develops predictive machine learning models for loan default detection and credit risk analysis using complex financial datasets. Prior to Montreat College, he conducted research at Kennesaw State University in collaboration with the Health Informatics and Technology Innovations (HITI) Lab at Emory University.

Deborah Osahor is a CISA-certified IT auditor and AI innovator building intelligent systems for financial oversight and fraud detection. She holds dual master's degrees in Information Technology and Accounting from Georgia Southern University, and is the founder of OversightAI, a platform powered by her patented hybrid machine learning and blockchain framework for real-time fraud detection and compliance monitoring

A Fellow of ACCSA Global and two-time Women in CyberSecurity (WiCyS) Scholar, her research has been published in peer-reviewed journals and presented at IEEE SoutheastCon 2026. She is an active member of NABA, IEEE, and the Blockchain Council.

Faith I. Nayebale is an accounting and tax compliance professional focused on the intersection of finance, taxation, artificial intelligence, blockchain, and digital transformation. She is a CPA Candidate, a Fellow of the Association of Chartered Certified System Accountants (ACCSA) Global, affiliated with the Certified Institute of Business Entrepreneurs (CIBE), and a member of the Blockchain Council.

Her work explores how emerging technologies can modernize tax administration, strengthen compliance, improve financial transparency, and support more efficient public and private sector systems. She brings a multidisciplinary perspective that combines accounting expertise with innovation, governance, and technology-enabled financial transformation.