Dr. Jun Zhuang didn’t just grow up alongside the evolution of the Department of Homeland Security’s Centers of Excellence — he lived it.
“I was a Ph.D. student when the DHS COEs started,” said Zhuang, now the Associate Dean for Research in the School of Engineering and Applied Sciences at the University at Buffalo. “It’s been fulfilling to try to understand these complex problems and help solve them.”
That early inspiration led Zhuang into a career dedicated to tackling some of the most pressing challenges in homeland security — from border operations to disaster response — through rigorous, systems-driven research. His latest project, the Real-Time Optimal Resource Allocation for Border Patrol Strategy (RTRIPS), exemplifies that vision.
Where Theory Meets Reality: A Toolkit with Stakeholder Roots
At the heart of RTRIPS is a rare synergy of advanced game theory, AI, and operations research applied directly to real-world border operations.
“Real problems need real tools,” Zhuang said. “And real tools need to be integrated across disciplines.”
RTRIPS is designed to support U.S. Border Patrol in making better decisions in complex, constrained, and adaptive environments. With ever-changing operational goals — from maximizing coverage and encounters to minimizing overtime and risk — Zhuang’s team models the trade-offs Border Patrol faces in real time.
“We’re not just building models in a lab,” he said. “We’re building them based on what’s actually happening in the field.”
Zhuang has worked on more than 40 funded research projects, but he sees RTRIPS as a milestone thanks to the strength of its stakeholder collaboration.
“This is my third COE project, and what’s unique here is the level of involvement from U.S. Border Patrol,” he said. “We’re solving real problems that they’re facing right now.”
From site visits to the Tucson and Buffalo sectors to monthly meetings with operators, Zhuang’s team builds with users — not just for them.
“Being on the ground completely changed our perspective,” he said. “We learned about commute times, constraints, and logistical realities that you wouldn’t know unless you were there.”
Those visits inspired the team to prototype their own scaled-down command-and-control systems in the lab — antennas, sensors, and all — mimicking the information flow of real operations.
Balancing Priorities in a Shifting Landscape
Zhuang’s approach acknowledges a core truth of border security: priorities shift, and strategies must adapt.
“Border Patrol has to balance many objectives: coverage, encounters, costs, personnel constraints,” he explained. “And those priorities can change depending on politics, policy, and resources.”
To account for that, the RTRIPS toolkit lets users assign weights to different objectives or explore a Pareto frontier — a visual map of trade-offs that shows how emphasizing one goal affects the others.
“Our role is not to decide the priorities,” he said. “We provide the tools so decision-makers can make informed trade-offs.”
Smarter Strategies for Adaptive Adversaries: Data-Driven and Ready to Deploy
Much of RTRIPS is about more than logistics — it’s about strategic foresight. Zhuang’s team uses game theory to model how adversaries, including smugglers and organized crime, might respond to enforcement patterns.
“We assume adversaries are smart and strategic,” he said. “If they can predict patrol routes, they’ll adapt. So our models account for that — we don’t just plug holes; we build system-level strategies.”
This systems approach helps ensure that enforcement efforts don’t just push activity elsewhere but instead result in optimized outcomes across the entire border environment.
RTRIPS is already making strides toward operational relevance. The team’s aim isn’t just to publish papers — it’s to transition the toolkit into the hands of those who need it most.
“Border Patrol is swimming in data but often doesn’t have the bandwidth to process it at the systems level,” Zhuang said. “That’s where we come in — helping them design better strategies using the latest optimization and AI tools.”
By building a toolkit that can be integrated into existing infrastructure, Zhuang hopes RTRIPS can be deployed without requiring a complete system overhaul.
“Ultimately, we want to provide science-based strategies that can upgrade how DHS allocates resources and responds to real-time challenges,” he said.
Purpose Beyond the Equations: A Researcher with Range and Resolve
For Zhuang, RTRIPS isn’t just another project — it’s personal. As an immigrant, a systems engineer, and a resident of a border town, he sees the work through multiple lenses.
“Buffalo is just 20 minutes from Canada, and border security is part of daily life,” he said. “At the same time, I’ve reflected deeply on the human experience — the people on both sides of this equation.”
Zhuang speaks of standing in a helicopter over the Arizona desert, seeing groups of migrants on the ground below.
“In that moment, I was thinking about their journey, their choices, and what happens next,” he said. “This work is not black and white. It’s about understanding the complexity of humanity.”
From observing real-time exercises on Grand Island to helping build models that balance competing priorities, Zhuang’s work is shaped by empathy, insight, and experience.
With RTRIPS, he hopes to give DHS and other security partners the tools they need to make more informed, ethical, and effective decisions — not just for today, but for a more adaptable future.
“I’m grateful to be in a position to help,” he said. “This project gives us a chance to study the complexity and offer something that has both technical value and human impact.”
