I am a Computer Science PhD Candidate at Cornell University, based at the New York City campus, Cornell Tech. Before that, I completed a Bachelor's Degree in Computer Science and General & Departmental Honors curricula at Clemson University (during the pandemic, unfortunately). This summer, I was a research fellow at the Design Trust for Public Space. In 2024, I was a research fellow at Hayden AI Technologies. My research is supported by the Cornell Tech Urban Tech Hub, the Cornell Dean's Excellence Fellowship, the Siegel PiTech PhD Impact Fellowship, and the Digital Life Initiative Doctoral Fellowship.

I co-organize the EAAMO Urban Data Science Working Group, which meets biweekly during the academic year (if interested in joining, please sign up for our mailing list!)

My dissertation will span the emerging data stream of dense street imagery (DSI), presenting technical applications and approaches for insight extraction, modeling, and reconciliation; analyzing information flows and nascent norms in the DSI landscape with ethical frameworks like contextual integrity; and demonstrating DSI's potential for urban science and design, which includes juxtaposition and situation against existing urban sensing methods, human-centered design methods, design across scales, and urban planning. My research interests extend to vision language models, mapping, computational social science (particularly in issues of societal inequality, climate, or public health), statistical modeling, computer vision, and fashion & design. My research has been covered in the New York Times, The Economist, Gothamist, and other local NYC news outlets.

I play, compose, and record classical and neoclassical piano music, pendulate between fiction and non-fiction books, hike while on vacation, write (immediately below), and model once or twice per year.

Writing

• Springs's Best, '25

  Published:Dec 5, 2025 |  at 04:47 PM

  Musical miscellany from the flowering months of 2025.

• Sensing AI Incidents & Risks from Global News

  Published:Nov 10, 2025 |  at 12:00 PM

  An LLM-based Urban AI Risks (UAIR) assessment pipeline for extracting, verifying, and classifying risk information about AI use cases from large-scale news article collections. The pipeline processes articles through a five-stage workflow combining large language model inference, semantic verification, and regulatory classification.

• Winter's Best, '24

  Published:Mar 30, 2025 |  at 12:47 PM

  My favorites from the winter bridging 2024 and 2025, where music never modeled life better.

• Where I am from, in nots

  Published:Mar 15, 2025 |  at 03:30 AM

  A short piece in the first issue of Skills/Hobbies/Interests that attempts to answer the prompt, 'where are you from?'