A graduate-level fellowship for emerging leaders — bridging the major ESG and Sustainability disclosure frameworks with Systems Thinking, MBSE (with SysML), and advanced multi-agent AI design.
Most all sustainability programs teach you what to know. The Fellowship trains you how to see — developing the mental models that let you perceive what others overlook.
Cognitive and strategic foundation
You'll develop the mental architecture to see across disciplines — identifying feedback loops, causal dynamics, and leverage points that linear analysis misses entirely.
Technical proficiency, data, and quantitative analysis
From GHG scopes to MBSE modeling labs — you'll speak every language sustainability demands and build agentic AI research systems that hold up to professional scrutiny.
Accelerated professional application
You'll leave with a portfolio-ready capstone, immediate employer readiness, and the practiced ability to move from systems analysis to concrete, communicable action.
Below are the two Fellowship finalists’ sustainability analysis capstone projects.
A $20 billion semiconductor Mega-Fab location decision. Two sites. One board memo.
“Which site gives Aether Chips the strategic advantage — and can you prove it with systems analysis?”
Arizona vs. Vietnam — water scarcity against a coal-dependent grid. The right answer transcends the binary.
Two publicly traded companies. One regime change. Who survives the shift from ratings to verification?
“Which disclosure architecture holds up when procurement stops rewarding what you report and starts demanding what you can prove?”
Ratings measure what companies choose to disclose. Verification measures what they actually do.
The Fellowship is an intensive, hands-on program. Here’s what you need to know before you apply.
A 12-week cohort running fall semester, designed to fit alongside graduate coursework or early-career schedules.
A single, all-inclusive enrollment fee covering all coursework, materials, and capstone participation.
Weekly coursework plus an intensive sustainability research and analysis project that runs the full duration of the fellowship, culminating in a live presentation in front of industry professionals.
The ability to move fluidly between the granular — materiality, frameworks, forensics — and the structural — dynamics, feedback loops, emergent risk. Expert problem solvers don’t just know more than novices. They perceive differently.
The Fellowship curriculum rests on four pillars. Rather than treating them as independent modules, they are bound together by a single pedagogical concept that defines the fellowship’s intellectual identity: Hybrid Lateral Thinking.
The curriculum is built on a prescient observation of the emerging AI economy: as AI systems scale up their capacity for specialist analysis — reading disclosures, computing emissions intensities, and scoring ESG metrics — the human edge shifts decisively. AI will always go deeper into specialization. Therefore, the non-automatable human advantage lies in broad integration:
Every element of the curriculum is explicitly engineered to operationalize this lateral mindset. Rather than teaching these tools in isolation, fellows deploy them as an interconnected stack:
The curriculum culminates in a Sustainability Recommendation Presentation. This final deliverable requires fellows to trace a flawless arc from raw GRI forensic findings, through sophisticated system modeling, to multi-agent system design. By delivering defensible, innovative recommendations, fellows prove they can fuse all four pillars into a single, coherent, and transformative argument.
“All models are wrong, but some are useful.”— George Box, 1976