Book Context and Rationale: American research institutions face an unprecedented paradox: shrinking budgets, aging infrastructure, and grant success rates half what they were a generation ago, yet computational power that once cost millions now costs only a few dollars per hour. This convergence of scarcity and abundance demands a fundamental reimagining of how discovery happens. The Computational Research Revolution provides the strategic roadmap for this transformation. Drawing on extensive research and real-world implementation across universities, national laboratories, and industry R&D facilities, Dr. Jason A. Hubbart demonstrates how institutions can leverage computational approaches to accelerate discovery, reduce costs, and enhance competitiveness, even in the face of fiscal constraints. The book systematically addresses the computational imperative across ten comprehensive chapters, from economic drivers and disciplinary transformation to infrastructure building, workforce development, and sustainable funding models. Readers will learn how: Cloud computing and shared cyberinfrastructure reduce research costs by orders of magnitude while expanding capability - Computational methods compress research timelines from years to weeks across physical sciences, engineering, social sciences, and humanities. - Research Software Engineers and data stewards form the critical human infrastructure enabling reproducible, scalable research. - Community cluster models generate 5:1 returns on investment while accelerating publication output by 40% - Strategic partnerships with industry and philanthropy diversify revenue and create career pathways for students. Each chapter combines theoretical frameworks with practical implementation strategies, providing actionable guidance for various institutional types, including land-grant universities, community colleges, private research institutions, and national laboratories. Why This Book Matters Now: Federal agencies increasingly embed computational readiness into funding criteria. The National AI Research Institutes program directs multi-year investments of up to $20 million toward institutions that demonstrate cyberinfrastructure capabilities. Employers across sectors prioritize data fluency as a baseline hiring requirement. Students select institutions based on computational sophistication. The window for early-adoption advantages remains open, but won't stay open indefinitely. For Leaders Ready to Act: Institutional leaders will find strategic frameworks for transformation. Faculty researchers will discover pathways to enhance scholarly impact while reducing costs. Industry professionals will recognize opportunities to strengthen university partnerships. Policymakers will understand how targeted investments yield measurable economic returns and national competitiveness. The book concludes with a detailed implementation roadmap featuring assessment tools, phased timelines, performance metrics, and strategies for sustaining innovation amid emerging technologies, including artificial intelligence, quantum computing, and edge processing. Institutions that strategically embrace computational research will transform apparent constraints into competitive advantages. Those who delay risk obsolescence. The computational advantage awaits those with the vision to pursue it and the determination to implement it effectively.