Road to Innovation Expo 2026: AI Data Center Site Selection
The race to build the infrastructure behind artificial intelligence has created the new and urgent challenge of finding the right places to put it. Hyperscale data centers, the massive facilities that power AI, cloud computing, and the modern internet, require enormous amounts of land, energy and connectivity, and identifying viable locations means sorting through a tangle of geographic, regulatory and economic variables.
A team of Stevens School of Business seniors took on the problem for their senior design project, developing a structured, data-driven framework to evaluate potential sites for large-scale data centers across the United States. Working with an investment partner entering the space for the first time, the team combined geospatial mapping software, infrastructure research and financial analysis to produce a repeatable methodology to identify and rank locations that meet the demanding requirements of hyperscale development.
“Our framework helps identify which locations are most feasible for future AI and hyperscale data center development,” said Afonso Santos, a quantitative finance major from Kenilworth, New Jersey. “We started by looking at the factors that matter most to data center operators and investors, especially access to power, land availability, natural gas infrastructure, flood risk, water access and local regulatory or political conditions. Instead of looking at only one factor, the framework helps rank opportunities by balancing infrastructure readiness, development risk and long-term investment potential.”
The team built their analysis around ArcGIS, an industry-standard geospatial mapping platform that allowed them to overlay multiple infrastructure criteria, including power transmission lines, natural gas pipelines, fiber optic networks, flood zones and air quality designations, across a national map. The visual approach helped the team move efficiently from broad regional screening down to specific counties and sites.
“We start by looking at states that may offer tax benefits and have less political pushback toward data center development,” explained Anthony DiMayo, a business and technology major from East Rutherford, New Jersey, who brought prior work experience in the data center space to the project. “From there, we map major natural gas, water and power infrastructure across those states to find concentrated areas that could support a data center. This lets us narrow down suitable regions based on factors like infrastructure access, land availability and reduced flood risk before focusing more closely on specific providers and real estate opportunities.”
The project ultimately produced a structured site selection framework and a narrowed set of high-potential locations, each assessed with detailed ArcGIS maps and site-level breakdowns of key infrastructure factors, trade-offs and development risks.
The Team
Anthony DiMayo | East Rutherford, New Jersey | Business & Technology
Brock Dickson | Barrington, Illinois | Business & Technology
Christopher Lubas | Mendham, New Jersey | Business & Technology
Andrew Piro | Mahwah, New Jersey | Finance
Afonso Santos | Kenilworth, New Jersey | Quantitative Finance
Faculty Advisor: Dr. Richard Dool
Q&A with Data Center Site Selection Team
What drew your team to this topic, and why did it feel like the right fit for your senior design project?
Afonso Santos: “Our team was drawn to this project because it sits at the intersection of several fast-growing and highly relevant areas: artificial intelligence, real estate investment, energy infrastructure and strategic decision-making. Data centers are becoming one of the most important asset classes supporting the modern economy, and site selection has become much more complex than simply finding available land. We liked that the project gave us the chance to work on a real problem with real business consequences. It felt like the right fit for senior design because it challenged us to combine analytical thinking, market research and practical decision-making in a way that goes beyond the classroom.”
Andrew Piro: “Our team had a really strong blend of skills across finance, real estate and technology. Each of us brought something different — experience in underwriting, financial and investment analysis, commercial real estate, and technical problem-solving — which aligned well with what we were looking to explore in the AI data center space. It felt like a natural fit because the project sat right at the intersection of all those areas, and we were confident we could add real value.”
Was there a particular challenge or turning point that forced your team to rethink your approach?
Anthony DiMayo: “We originally started by researching county by county, but we quickly realized that our client was not focused on just one state. That meant we could spend a lot of time researching one county, only to find out it was not suitable and then have to start over somewhere else. Pretty soon, we realized that approach would take way too long. That pushed us toward using ArcGIS and working from a broader view first, starting with states, then major gas, water and power infrastructure, then regions, and finally individual counties.”
Christopher Lubas: “We had an idea to run a query in the ArcGIS software to essentially triangulate the requirements within a certain distance from one another, but that feature was part of a premium subscription that was too expensive for us to purchase. This forced us to do that part manually, roughly 10 times slower than our first proposed methodology. To combat this, we just spent more time together scanning the country for potential areas of interest.”
How has your coursework in the School of Business prepared you for the analytical and strategic thinking this project required?
Brock Dickson: “My coursework gave me a strong foundation across data analysis, finance and strategy. It taught me how to work through large amounts of information, identify patterns and think through decisions from both a technical and business perspective, which was really important throughout this project.”
Christopher Lubas: “Even though the actual work is a lot different than what we cover in the School of Business, the strategic approaches we took were learned from our time at Stevens. We had to translate a real-world problem into a repeatable framework, communicate assumptions and tradeoffs clearly, and deliver something a client could actually apply again. That experience has made me more ready for life after graduation because I’ve practiced how work happens in industry. There are tight timelines, ambiguity and the need to produce a clean deliverable that survives beyond the classroom.”
What is the value of a real-world consulting engagement as opposed to something more theoretical?
Andrew Piro: “Four years ago, I wasn’t initially anticipating a real estate path when I first arrived here as a freshman. But this changed my direction immensely, and the experience on my resume helped me land an analyst role at Newmark, a top commercial real estate firm. Do not discount senior design as just another class. I think when it is all said and done, this will be one of the most consequential projects I’ve ever been a part of in my life.”
Anthony DiMayo: “The main benefit was being put into an environment where we had to adapt. Things rarely go exactly according to plan in the real world, so working on a hands-on consulting project helped me get more comfortable with adjusting our approach when new challenges came up. It also showed me that theory can only take you so far. At first, I thought this project would be fairly straightforward, but once we got into the actual work, I quickly realized how much problem-solving and flexibility it required.”
What is the biggest lesson you’ve taken away from this project?
Afonso Santos: “The biggest lesson I will carry forward is that great analysis only matters if it is actionable. It is not enough to gather data or identify trends. The real value comes from knowing how to prioritize what matters most, communicate it clearly and turn it into a decision-making tool. This project taught me that strong work combines rigor with practicality, and that is a mindset I plan to bring into my professional career.”
Brock Dickson: “The biggest lesson I’ve taken away is that analysis is only valuable if you can turn it into something actionable. We worked with a lot of complex data, but the real challenge was turning that into clear recommendations. It also taught me how important it is to stay flexible when things change and keep working toward a solution.”
