Current Work

I am joining Google as a Senior Quantitative UX Researcher, applying AI- and data-driven approaches to understand and enhance human-computer interactions at scale!

Previous Work

I was a Senior Research Scientist at Ruby Neurotech, an early-stage startup funded by Wellcome Leap to build AI-powered mental health solutions. Our work integrated AI and neurophysiology to deliver individualized interventions at scale. I designed human-AI conversations as well as large-scale evaluation of human-AI interactions, and identifying biomarkers that can predict the success of our interventions by integrating qualitative diaries, behavioral patterns, and physiological time-series signals of pupil size.

I also briefly consulted on a Stanford University project, funded by the Wu Tsai Human Performance Alliance, focused on enhancing memory retrieval through real-time eye tracking. In this role, I provided guidance on developing a closed-loop system that monitors attention in real time.

Past Research

Previously, I was a post-doctoral fellow at UChicago (supported by NIH K99 & F32 awards) and a Neuroscience PhD student at Princeton University (supported by an NSF GRFP). My research focused on developing real-time, closed-loop systems to enhance human attention and memory. I collaborated with Intel Labs’ Brain-Inspired Computing group, clinical researchers at UT Austin and UPenn, and neurologists and neurosurgeons at the UChicago Medical Center. Two key technologies that I developed were real-time fMRI neurofeedback and real-time triggering, which involved building machine learning models for personalized, adaptive interventions. I have extensive experience with a wide range of complementary cognitive neuroscience techniques, including EEG, fMRI, fNIRS, intracranial recordings, eye-tracking, pupillometry, face and pose tracking, PPG, heart rate variability, and both qualitative and quantitative asssessments of human behavior.

I hold a BS in Applied Mathematics from Columbia University, where I spent significant time as an undergraduate researcher in the Biomedical and Electrical Engineering departments building ML analysis and signal processing tools for EEG and fMRI.