Dr. Moody Amakobe: Advancing Responsible AI for Public Good
Multidisciplinary technologist and educator with 15+ years of experience bridging artificial intelligence, distributed systems, and public policy. Specializing in responsible AI, distributed trust systems, and AI capacity-building in the public sector.
About
Bridging technical innovation with social and institutional challenges to ensure emerging technologies serve both operational excellence and public accountability.
My research vision centers on translating complex technical advances, especially in AI and distributed computing, into meaningful, real-world applications that promote trust, equity, and transparency.
Doctor of Computer Science - Colorado Technical University15+ years enterprise software architecture experienceAdjunct Professor at multiple universitiesAuthor of forthcoming textbook "Deep Learning: A Comprehensive Guide"
Research Areas
Advancing responsible AI through innovative research in distributed systems, governance frameworks, and public interest technology applications.
Federated Proof of Contribution (F-PoC)
Novel blockchain consensus mechanism integrating federated learning with PoC principles for privacy-critical environments like healthcare and decentralized identity systems.
Generative AI in Enterprise & Government
Research into AI coding assistants impact on development teams, LLM adoption in healthcare operations, and AI-powered cybersecurity in resource-constrained organizations.
AI Governance & Public Sector Innovation
Focused on AI governance, technical policy translation, and public sector readiness. Developing frameworks to help policymakers navigate ethical AI implementation.
Professional Journey
A comprehensive blend of academic research, industry leadership, and technological innovation spanning over 15 years.
Adjunct Professor
2021 – Present
George Mason University, Trine University, University of the Cumberlands
Teaching graduate courses in Deep Learning, NLP, Blockchain, and Big Data. Mentoring thesis and capstone students in applied AI, cybersecurity, and public interest technology.
Principal Engineer / Software Development Manager
2021 – 2023
T-Mobile
Led DevOps transformation across hybrid infrastructure, introduced scalable infrastructure strategies supporting future AI deployment readiness, and advocated for responsible automation practices.
Solution Architect Manager / Consultant
2013–2016, 2019–2021
Accenture
Designed enterprise architecture for large clients in healthcare and insurance. Advised cross-functional teams on systems alignment, compliance, and risk management.
Senior Architect / Technical Manager
2016 – 2019
Mindtree / Wipro
Built and deployed secure enterprise platforms with integrated data modeling and analytics pipelines. Collaborated with security, operations, and data governance teams.
Publications & Research
Advancing the field through academic publications, textbooks, and mentored research projects focused on responsible AI and public interest technology.
Deep Learning: A Comprehensive Guide
Cognella Academic Publishing, 2025
Blends foundational ML theory with practical implementation in PyTorch and Hugging Face, emphasizing explainability, cloud deployment, and AI ethics. Designed to introduce graduate students to core machine learning concepts while emphasizing real-world constraints.
Current Research Mentorship Areas
Generative AI in clinical and administrative healthcare workflows
AI coding assistants and their effect on team dynamics
AI barriers in cybersecurity adoption in SMBs
PQC integration into legacy IT systems
Ethical oversight of autonomous infrastructure monitoring
Let's Collaborate
Whether you're interested in research collaboration, speaking engagements, or academic partnerships, I'd love to connect with you.
Location:
Alexandria, VAUnited States
Areas of Expertise:
Response Time:
I typically respond to inquiries within 24-48 hours during business days. For urgent matters, please mention it in your message.