Research

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

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.

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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.

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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.

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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.

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