Master's Thesis: A Journey of Growth and Innovation

Today, 2 May 2025, marked a defining moment in my life—I successfully defended my master's thesis and graduated from the University at Buffalo (UB) with a Master of Science in Industrial & Systems Engineering. 💯 This journey, full of challenges, insights, and transformations, has been one of the most rewarding experiences of my life. 🌟 I decided this thesis topic with a mission: to contribute meaningfully to society using my computer systems, data science and problem solving skills. And I leave with not just a diploma, but a body of work that reflects real-world application, innovation, and commitment to public safety. My research project, Patrolling Optimization for Enhanced Security in Schools (POESS), was inspired by a growing need to protect educational institutions against security threats in an unpredictable world. In this work, I leveraged ’Bayesian Stackelberg Games’, a branch of game theory, to model the interaction between security officers and potential adversaries. The idea was simple but powerful: design patrol routes that are strategically randomized, hard to predict, yet highly effective. Drawing inspiration from the PROTECT system used by the U.S. Coast Guard, I adapted these frameworks to school environments—factoring in real-time student movement data, campus layouts, and potential threat zones. This wasn't just a theoretical endeavor. It involved deep dives into simulation modeling, hours of algorithm optimization, and even developing a simulation web application to visualize the patrolling strategies. Seeing it all come together during my defense was nothing short of exhilarating. I would not be here without the incredible people who walked this path with me. My heartfelt thanks to my advisor, Dr. Jun Zhuang and mentors at UB, to the officers at the University Police who provided valuable perspectives, and to the brilliant minds at SENTRY (Soft Target Engineering to Neutralize the Threat Reality) and the Department of Homeland Security who offered critical support. A special shout-out to my family and friends who supported me through sleepless nights, endless debugging, and constant thesis edits. Your belief in me kept me going. I hope to continue working at the intersection of data, AI, machine learning, and public good. If my thesis taught me anything, it's that well-crafted strategies—when backed by data and purpose—can save lives. I'm excited to share more about my journey, the challenges I faced, and the lessons I learned along the way. Stay tuned for updates on my portfolio website, where I'll be posting more about my research, projects, and future endeavors in the field of data science and engineering.