My projects spanning Ubiquitous Computing, Human-Computer Interaction, and Neural Decoding.

HydroSense Mini

Developing a high-adherence smart water bottle to study personal hydration. Two main aims: 1) Integrate kinetic energy harvesting and other design considerations to make everyday use practical. 2) Track personal hydration habits alongside physiological signals to find markers of dehyrdation. Check out my poster I presented at the Paul G. Allen School 2022 Annual Research Showcase.



Augmenting smartwatch straps with pressure sensing to measure fit. Using fit to address: 1) PPG based heart rate sensing: exploring changing LED intensity. 2) IMU-based gesture recognition: exploring adjutsable smoothing and preprocessing based on fit. 3) Presenting error-bars or more accurate representations of the signal to improve transparency.


AutoStim: Optimized Encoding of Touch in Brain Machine Interfaces

Developed an efficient algorithm to find stimulation parameters that evoke discriminable sensations of touch in sensory brain machine interfaces. Implemented unsupervised clustering of neural response and active learning-like prioritization to make stimulation experiments efficient. Check out my poster I presented at the 2022 University of Pennsylvania Singh Center REU Symposium.



Developed a low-cost DIY cardboard button detectable by microphones. This provides a quick and sustainable option for short-term smart-home and interaction use cases. The entire button can be fabricated with cardboard, scissors, a staple, and tape. Testing the longevity, the button withstood over 3 million presses.