Meet the Founder

Educator & Generative AI Scientist with 20+ Years of Higher-Ed and Research Experience


I’m Jonathan Wong, the founder of CloudPedagogy—an educator, generative AI scientist, and lifelong learner with over 20 years’ experience in higher education, research, and technology. In my career, I’ve developed hands-on data science and machine-learning courses, guiding learners through real-world research projects and workflows. I’ve also led generative AI–driven initiatives, ensuring each solution remained ethical and impactful. In May 2025, I launched CloudPedagogy to bridge the gap between generative AI’s potential and the everyday needs of academic and research professionals.

And coming soon: the CloudPedagogy Agentic Tool Lab — a hosted and downloadable suite of intelligent AI tools to apply what you learn directly to real academic workflows.

Our Mission

CloudPedagogy equips academic developers, learning designers, research managers, and senior leaders with deep, applied generative AI skills—so institutions can adopt these tools responsibly, ethically, and at scale. We believe:

Education Should Be Hands-On
 It’s not enough to discuss generative AI in theory—learners need practical exercises, real-world prompts, and structured activities to experiment, refine, and build genuine confidence.

Context Matters
 A one-size-fits-all MOOC won’t address complex workflows across universities, research centres, libraries, and museums. Our courses are crafted around relevant policies and tackle institutional challenges—governance, assessment integrity, research acceleration, and operational efficiency.

Efficiency & Competitive Advantage
 In an era of tightening budgets and heightened competition, CloudPedagogy helps institutions unlock efficiency gains—whether automating routine administrative tasks, accelerating literature reviews with generative models, or drafting policy documents. These savings free up faculty and staff time for strategic initiatives, making your institution leaner, more agile, and better positioned to compete.

Guided Pathways Foster Growth
 We’ve organised our content into progressive learning pathways so that everyone—from newcomers to seasoned professionals—can upskill at their own pace, layering knowledge from ethical foundations to executive-level strategy. New generative AI course bundles are continuously in development to deepen and broaden these pathways.

Who Benefits: A Wider Audience

  • Academic Faculty & Researchers: Professors, lecturers, postdoctoral fellows, and research associates who need to accelerate literature reviews, prototype generative AI–driven experiments, or generate data-driven insights for publications and grants.

  • Teaching & Learning Designers: Instructional designers, learning technologists, and educational developers building curricula augmented with generative AI, adaptive assessments, and inclusive pedagogies.

  • Departmental & Research Administrators: Research managers, programme coordinators, grant administrators, and project officers seeking to streamline workflows—such as automating grant proposal summaries, managing research data pipelines, or synthesising committee minutes using generative AI.

  • Library & Knowledge Services Teams: Librarians, archivists, and knowledge managers leveraging generative AI for catalogue curation, metadata enrichment, systematic reviews, and digital scholarship support.

  • Policy & Governance Committees: Ethics board members, data-protection officers, compliance teams, and governance committees drafting generative AI policies, risk-mitigation frameworks, and audit protocols.

  • IT & Educational Technology Teams: System administrators, cloud engineers, platform architects, and educational technologists deploying, securing, and scaling generative AI environments within institutional infrastructure.

  • Student Support & Success Services: Academic advisors, career counsellors, disability services coordinators, and mental-health professionals exploring AI-powered chatbots, personalised learning recommendations, and data-driven student retention strategies.

  • Curricular & Programme Directors: Heads of department, programme leaders, and curriculum committees designing degrees or certificate pathways that embed generative AI literacy and practical competencies.

  • Professional Development & CPD Teams: Staff developers, faculty-development specialists, and continuing-education coordinators creating scalable CPD offerings to upskill entire institutions in generative AI.

  • Library & Knowledge Services Professionals: Librarians and information specialists developing generative AI applications for digital collections, interactive learning resources, and public engagement initiatives.

  • Marketing & Recruitment Teams: Student-recruitment managers, communications officers, and marketers using generative AI for promotional materials, social-media content, and personalised outreach campaigns.

  • Executive Leadership & Strategy Groups: Deans, provosts, directors, and senior executives responsible for institutional strategy, resource allocation, and ensuring competitive advantage in research funding, rankings, and grants.

  • External Consultants & Partners: Educational consultants, grant-funding advisors, and technology partners seeking deeper expertise in generative AI applications within higher education and research contexts.

By addressing this broad spectrum of roles, CloudPedagogy ensures that every stakeholder—from frontline faculty member to senior leader—sees immediate relevance and practical value in our training.

Our Innovative Approach

Deep, Applied Generative AI Competencies
 Participants gain not only theoretical understanding but hands-on skills in areas like generative AI governance, prompt engineering for assessment and research, and data-driven research design. These capabilities translate directly into improved teaching practice, more efficient research workflows, and enhanced confidence in leading generative AI projects.

Career Acceleration
 Mastery of advanced generative AI methods positions faculty, researchers, and professional staff for promotion, secondments to institutional AI strategy teams, or external consultancy roles. Demonstrating real-world generative AI proficiency becomes a powerful differentiator on your CV.

Tangible Efficiency Gains
 By learning how to automate literature reviews with generative models, generate draft policy documents, curate digital archives, and prototype data pipelines, you’ll reclaim hours each week—time you can reinvest in mentoring students, writing grant proposals, or advancing your own research agenda.

Impact for Individual Learners

Deep, Applied Generative AI Competencies
 Participants gain not only theoretical understanding but hands-on skills in areas like generative AI governance, prompt engineering for assessment and research, and data-driven research design. These capabilities translate directly into improved teaching practice, more efficient research workflows, and enhanced confidence in leading generative AI projects.

Career Acceleration
 Mastery of advanced generative AI methods positions faculty, researchers, and professional staff for promotion, secondments to institutional AI strategy teams, or external consultancy roles. Demonstrating real-world generative AI proficiency becomes a powerful differentiator on your CV.

Tangible Efficiency Gains
 By learning how to automate literature reviews with generative models, generate draft policy documents, curate digital archives, and prototype data pipelines, you’ll reclaim hours each week—time you can reinvest in mentoring students, writing grant proposals, or advancing your own research agenda.

Impact for Departments & Institutions

Operational Efficiency & Cost Savings
 Training in generative AI empowers your teams to automate time-consuming processes—grading, literature synthesis, policy drafting, metadata enrichment—so you reduce overhead, reallocate resources to strategic initiatives, and respond more nimbly to budget constraints.

Culture of Responsible Innovation
 By upskilling cohorts of lecturers, researchers, librarians, administrators, and support staff together, you create a shared language around ethical generative AI use—accelerating institution-wide fluency and reducing fragmented, siloed pilot projects.

Policy & Compliance Readiness
 Graduates can draft robust policies, construct evaluation frameworks, and define risk-mitigation protocols—helping universities and research centres comply confidently with emerging generative AI–specific regulations. No more scrambling when external regulators knock.

Scalable Best Practices
 As participants share successful prompts, toolkits, and case studies, departments can rapidly repurpose proven models—compressing time to impact for new programmes, research initiatives, public engagement efforts, or administrative workflows from months to weeks.

Competitive Differentiation
 Institutions that master generative AI can offer more innovative curricula, attract top researchers, secure grants tied to digital transformation, and deliver stronger student experiences. By embedding generative AI literacy into your core strategy, you stand out in an increasingly competitive higher-education and research landscape.

Societal & Pedagogical Benefits

Equity & Inclusion
 Advanced training in bias detection and accessibility auditing equips staff to design generative AI–augmented learning experiences that close achievement gaps for under-represented groups—promoting digital inclusion, social justice, and broader knowledge equity.

Future-Ready Graduates & Researchers
 By embedding sophisticated generative AI tools into curricula, research training, and professional development, institutions prepare students, early-career researchers, and support staff for workplaces increasingly powered by generative models—enhancing both employability and broader societal digital literacy.

Together, these impacts create a virtuous cycle: well-trained staff drive more effective, ethical generative AI implementations, which in turn produce better student outcomes, stronger research outputs, enriched public engagement initiatives, improved institutional reputation, and evidence-based contributions to the wider education and research ecosystem.

Why CloudPedagogy Is Unique

Focused on Real-World Workflows:
 Large MOOC platforms offer generic “generative AI in education” courses but rarely address specific use cases—like systematic reviews with LLMs, grant proposal support, policy governance, or digital curation. We design every exercise around the actual tasks you face.

Not Just an Add-On:
 EdTech vendors and consultants may run occasional workshops on AI policy or digital-scholarship tools, but these are often siloed or tied to specific products. At CloudPedagogy, you get a cohesive curriculum that integrates ethics, technical skill, and institutional strategy—without expensive consulting fees.

Scalable & Flexible:
 Consultancy boutiques can deliver bespoke workshops at high price points, but they struggle to scale. Our modular, self-paced design lets institutions pick and choose exactly which generative AI competencies they need—achieving both depth and breadth in training at an affordable cost.

Context-Sensitive Pathways:
 From foundational generative AI literacy through advanced application to specialist leadership strategy, every module is tailored to real policies, regulations, and pain points across higher education, research, and allied cultural and support services—ensuring immediate relevance and impact.

Solving Real-World Pain Points

Pedagogical & Research Quality
 Ensuring generative AI enhances—not undermines—learning outcomes, assessment fairness, research rigor, and scholarly integrity.

Operational Resilience
 Equipping research offices, teaching support teams, library and archives staff, and administrative units with generative AI tools and protocols to boost efficiency while preserving equity, data privacy, and compliance.

Strategic Readiness
 Training leaders—deans, directors, policy-makers—to embed generative AI safely into institutional strategy—minimising reputational, regulatory, and financial risk.

With emerging generative AI regulations, national digital-skills mandates, and CPD budgets available, there’s never been a better time for universities, research centres, libraries, and museums to invest in high-quality generative AI upskilling.

What Learners Can Expect

Hands-On Exercises & Templates:
 Every module includes practical activities—prompt repositories, policy-drafting checklists, digital-curation frameworks, and step-by-step case studies—so you graduate with generative AI tools you can implement from day one.

Expert Guidance:
 Learn from instructors who combine academic rigor with real-world experience. You’ll be guided by someone who’s built machine-learning pipelines for research projects, aligned generative AI workflows, developed digital-scholarship initiatives, and designed multi-disciplinary AI curricula.

Continuous Growth:
 Our tiered pathways let you start with foundational topics and progress through advanced and specialist subjects—so whether you’re new to generative AI or ready for executive-level strategy, there’s a clear roadmap for your journey.

Join Us

Whether you’re an academic researcher exploring generative AI–driven literature reviews, a learning designer reimagining curriculum delivery, a librarian prototyping AI-powered discovery tools, a research manager streamlining data workflows, a curator developing digital exhibitions, or a department leader drafting your institution’s first generative AI policy—CloudPedagogy has a pathway for you. Browse our offerings, request a demo, or get in touch to discuss group pricing and pilot collaborations.

At CloudPedagogy, we believe responsible, well-informed generative AI is the future of higher education, research, and allied cultural services. Together, let’s build the skills, frameworks, and confidence you need to lead in this new era of generative AI.