I am a Computer Science PhD Candidate at Cornell University, based at the New York City campus, Cornell Tech , and advised by Wendy Ju and Helen Nissenbaum. 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. During my PhD, I have held summer fellowships at Hayden AI and the Design Trust for Public Space. My scholarship has been covered in the New York Times, Gothamist, New York Post, The Economist, and other local NYC news outlets.

Since 2024, I co-organize the EAAMO Urban Data Working Group. View our scheduling here.

I care deeply about upholding the integrity of the norms our society has stewarded, through centuries of technological innovation, for public spaces. I am especially interested in informational norms (expectations around how information should flow between parties) and interaction norms (expectations around how people should interact & behave).

I use the Contextual Integrity framework as a litmus: if new practices in a context (e.g., public space) pose harms or benefits to affected parties, impact ethical and political (i.e., societal) values, or impact the attainment of contextual ends and values, then they warrant defense on ethical grounds.

I research, situate, analyze, model, and highlight the technologies that are being introduced into our cities; including networked dashboard cameras (FAccT '23 & '25, AutoUI '24, NYTimes Street Wars '24, NatComms '26), autonomous vehicles (FAccT '25), sidewalk delivery robots (CHI '25), and AI 'smart' glasses (to come). Complexity arises from the coupling of these sensing technologies with an artificial intelligence model, which produces diverse and perceptive inference-making capability. Interpretability hence becomes important.

My interests have become increasingly more 'meta' (my favorite word) as I scrutinize LLM architectures, deontic logic, and moral philosophy. And so, I now also research technical interventions at the *model* level (COLM '26), with a focus on training-time finetuning methods, transformations for training data, and analyzing model behavior.

I play , compose, and record neoclassical piano music, pendulate between fiction and non-fiction books, hike whilst on vacation, write, and model once or twice per year.