Much of my professional and academic work starts from a basic but broad curiosity. I’m interested in how complex systems work, how minds and artificial intelligence process information, and how technological change reshapes our world. More than anything, I’m interested in how understanding the relationships between these questions can help us build more useful, responsible, and interesting things.
Professionally, I’ve spent much of my career translating messy real-world business problems into practical technical systems. That work has included product development, platform architecture, data integrations, analytics, security, and governance. I’m especially interested in the places where technology runs into organizational complexity. Those are often the places where solution architecture matters most, and where the trade-offs are real enough that they need to be carefully evaluated rather than hand-waved away.
I currently work at Newmark, where I help lead the development of Newlitic, an enterprise platform for data integration, analytics, and data management in the corporate real estate space. As part of that work, I’ve developed a deeper focus on security and compliance, including serving as lead implementor and security manager for our ISO27001 program. I had always been interested in security, but working with it professionally made the topic much more real and immediate. That perspective now strongly shapes how I think about AI and LLMs, especially as these tools move from isolated chat interfaces into connected systems with access to data and agentic capabilities.
Outside of work, I’m pursuing a Master’s in Computer Science at Georgia Tech with a focus on artificial intelligence. My academic interests center around generative AI (especially LLMs), cognitive science, and the question of how intelligent systems generate, evaluate, and revise ideas. My interest in cognitive science includes both human and artificial minds. This is a very broad area of interest that crosses several disciplines, but lately I’ve found myself narrowing in on questions of accuracy, reliability, and how modern LLM architectures can better regulate their outputs.
This site is a place for me to collect notes, questions, and reflections from those areas of interest. I write about AI and LLMs, data and business systems, cognitive science, markets and investing, books, research papers, and the occasional project or experiment. Some posts are professional reflections, some are research notes, and some are simply attempts to understand something interesting a little more clearly.
Note: This is a personal website, so I generally avoid writing too specifically or directly about what’s going on at work. Instead, I use this space to explore the broader ideas, patterns, and questions that connect to the kinds of problems I care about.