The R.A.I.S.E. Framework
Resilience • AI • Infrastructure • Systems • Education
Vision
The R.A.I.S.E. framework represents a holistic approach to strengthening water and civil infrastructure through the responsible integration of emerging technologies, systems thinking, and transformative education. As our infrastructure systems face unprecedented challenges—aging assets, climate change, resource constraints, and evolving demands—we need frameworks that bridge traditional engineering with cutting-edge innovation.
The R.A.I.S.E. framework has guided Dr. Lee’s research across water infrastructure domains. Current work emphasizes the application of R.A.I.S.E. principles to building water distribution systems, digital twins, and autonomous control for integrated water-energy-quality (WEQ) optimization.
The Five Pillars
R - Resilience
Building infrastructure that adapts, withstands, and recovers from disruptions
Modern infrastructure must go beyond reliability to achieve true resilience. This pillar focuses on:
- Predictive resilience: Using data analytics to anticipate failures before they occur
- Adaptive capacity: Designing systems that respond dynamically to changing conditions
- Recovery optimization: Minimizing downtime and cascading failures during disruptions
- Multi-hazard preparation: Addressing climate change, wildfires, earthquakes, and human-caused events
Key Research Areas:
- Water infrastructure performance measurement
- Disaster response and recovery (Camp Fire contamination study)
- Asset management under uncertainty
- Climate adaptation strategies
A - Artificial Intelligence
Leveraging AI and advanced analytics for smarter infrastructure decisions
AI and machine learning are transforming how we design, operate, and maintain infrastructure. This pillar explores:
- Predictive analytics: Forecasting failures, demand, and system behavior
- Prescriptive analytics: Optimizing operations for energy, cost, and water quality
- Real-time monitoring: Smart sensors and continuous data analysis
- Decision support systems: AI-assisted tools for complex infrastructure choices
Key Research Areas:
- Machine learning for water demand forecasting
- Neural networks for pipeline failure prediction
- Optimization algorithms for pump scheduling
- Data-driven asset management
I - Infrastructure
Advancing the physical systems that sustain our communities
Infrastructure is the backbone of modern society. This pillar addresses:
- Water distribution systems: Pipes, pumps, treatment, and storage
- Premise plumbing: Building-level water systems and water quality
- Smart infrastructure: Sensor networks and digital twins
- Asset management: Strategic repair, rehabilitation, and replacement
Key Research Areas:
- Water main failure analysis and management
- Premise plumbing hydraulic and water quality modeling
- Service line material performance
- Infrastructure integrity programs
S - Systems
Thinking holistically about interconnected challenges
Infrastructure doesn’t exist in isolation. This pillar emphasizes:
- Systems thinking: Understanding complex interactions and feedback loops
- Water-energy nexus: Recognizing the interdependence of water and energy systems
- Integrated planning: Coordinating across utilities, agencies, and stakeholders
- Sustainability: Balancing economic, environmental, and social objectives
Key Research Areas:
- Multi-objective optimization
- Life cycle assessment of infrastructure materials
- Decentralized and hybrid water systems
- Non-revenue water reduction
- Water equity and environmental justice
E - Education
Preparing the next generation of infrastructure leaders
The future of infrastructure depends on well-trained engineers who can navigate complexity. This pillar focuses on:
- Curriculum innovation: Integrating analytics, AI, and systems thinking into civil engineering education
- Experiential learning: Real-world projects and industry partnerships
- Interdisciplinary training: Bridging engineering with data science, policy, and economics
- Lifelong learning: Supporting continuous professional development
Key Activities:
- NSF-funded educational research on systems thinking and data analytics
- Development of new courses on water infrastructure analytics
- Mentoring graduate students and early-career professionals
- Industry-academic partnerships (California Water Service collaboration)
Research Impact Through R.A.I.S.E.
The R.A.I.S.E. framework has guided research that has:
- Advanced knowledge: 130+ publications, 7 books, 2,000+ citations
- Secured funding: $1.3M+ from NSF, EPA, and industry partners
- Influenced practice: AWWA manuals, ASCE technical reports, utility partnerships
- Earned recognition: Multiple Best Paper Awards, ASCE and EWRI Fellowships
- Trained leaders: Dozens of graduate students and practicing engineers
Recent R.A.I.S.E. Projects
NSF-Funded Education Initiative
Developing Students’ Systems Thinking and Data Analytics Skills in Civil and Environmental Engineering
- Integrating analytics across undergraduate curriculum
- Creating new pedagogical approaches
- Measuring learning outcomes
EPA Water Infrastructure Research
Right-Sizing Tomorrow’s Water Systems
- Integrated premise plumbing modeling
- Building water system optimization
- Public health and sustainability
Industry Collaboration
California Water Service Partnership
- Water main integrity management
- Multi-objective system optimization
- Well rehabilitation strategies
- Real-time monitoring and control
The R.A.I.S.E. Community
The framework extends beyond individual research to build a community of practice:
- Academic partners: Collaborations with University of Delaware, Rutgers University, and other leading institutions
- Industry partners: Water utilities, consulting firms, and technology companies
- Professional societies: Leadership in ASCE, AWWA, and EWRI
- Students and early-career engineers: Mentorship and career development
Future Directions
As infrastructure challenges evolve, so will R.A.I.S.E. Emerging focus areas include:
- Digital twins for real-time infrastructure management
- Explainable AI for transparent decision-making
- Equity-centered infrastructure serving underserved communities
- Circular economy approaches to water and materials
- Climate-adaptive design for uncertain futures
Join the R.A.I.S.E. Mission
For Prospective Graduate Students
I’m recruiting motivated graduate students passionate about using AI and analytics to solve real-world infrastructure challenges. Research assistantships available for qualified candidates interested in:
- Machine learning for water infrastructure
- Predictive analytics and optimization
- Premise plumbing and building water systems
- Climate resilience and adaptation
- Digital transformation in civil engineering
Interested? Email me at juneseok.lee@manhattan.edu with your CV and research interests.
For Researchers and Practitioners
Interested in collaboration on water infrastructure, AI applications, or systems thinking research? Let’s explore how the R.A.I.S.E. framework can advance your work.
Areas for collaboration:
- Joint research projects and publications
- Proposal development
- Industry-academic partnerships
- Visiting scholar opportunities
For Utilities and Agencies
Looking for research partnerships or technical expertise? I welcome opportunities to:
- Apply cutting-edge analytics to operational challenges
- Develop decision support tools
- Provide expert guidance on infrastructure resilience
- Collaborate on grant-funded research
Past partners include: California Water Service, EPA, NSF
Contact
Juneseok Lee, Ph.D.,P.E.
Professor of Civil and Environmental Engineering
Manhattan University
Riverdale, NY 10471
📧 juneseok.lee@manhattan.edu
📞 718-862-7318
🔗 Google Scholar | Faculty Profile | GitHub
“The R.A.I.S.E. framework is not just about technology—it’s about building a more resilient, equitable, and sustainable future through smarter infrastructure.”