I work at the intersection of neuroscience, computing, and history. Three of my projects turn out to ask one question: when does a measurement confidently report something that isn't there? A hippocampal CA1 model where the spectral statistic found a rhythm that was an artifact of its own input. A brain-computer interface where the hard part was telling a decoder's failure apart from the signal's. A surrogate model that certifies firing rates a real neuron cannot produce, reporting zero error while the cell stays silent. The pattern showed up before any of them: the first open-source BCI I trusted owed its accuracy to data leakage, and the single-electrode headset I had bought could not physically reach motor cortex. I moved to public datasets and rebuilt the analysis on real EEG.
The question is not only a technical one. I spent a year on a paper arguing that McCarthyism damaged American universities less through congressional pressure than through administrative capitulation, institutions failing the value they claimed to exist for. In an essay on psychiatric diagnosis I argued that the threshold for clinically significant is a judgment, not a measurement, and that where it falls decides whose hard life becomes a condition. I build historical arguments in Civilization VI mods too, where a claim about what a leader optimized for has to be written as numbers and can then be proved wrong by play.
I also build things that simply have to work: a dining-hall ordering system for my school, and a rating engine that turned my dorm's foosball table into a social hub. What drives me is curiosity about the brain: how it computes, remembers, and might one day interface with machines, and I care about using what I build to help people, from a scholarship-funded housing project for rural families to reading with kids.