Projects

2022

Tongue Gestures in Head Worn Displays

Tongue Gestures in Head Worn Displays

Published:

Pioneered a new, accessible method of hands-free interaction with head-worn displays using tongue gestures, detected using multimodal sensing capabilities in current VR headsets. Collected a multi-location, multi-sensor dataset of 50,000 gestures across 16 participants.

Perceived Credibility of Public Health Messages

Perceived Credibility of Public Health Messages

Published:

Examined how credibility of public health messages regarding COVID-19 varies across different platforms (Twitter, original website) and source (CDC, Georgia Department of Health, independent academics) in a controlled experiment.

Assistive Smart Stove for Safer Kitchens

Assistive Smart Stove for Safer Kitchens

Published:

Prototyped an intelligent stovetop appliance and mobile app interface to reduce risks of burns and falling objects while assisting with memory lapses in finding ingredients within the kitchen. Conducted Wizard of Oz study on prototype with student participants and collected usability information from interviews, performance, and the NASA-TLX.

Horizon Worlds: A Community of Practice for Social VR Design

Horizon Worlds: A Community of Practice for Social VR Design

Published:

Using ethnographic methods, studied the online VR community in Horizon Worlds. Based on observational reports and interviews, we found the creative community of world designers to be a prototypical community of practice for designing social VR experiences.

2021

Localization of Working Memory using tfMRI

Localization of Working Memory using tfMRI

Published:

Investigated working memory activity through N-back tasks with different sequence lengths and stimuli based on the Human Connectome Project’s task-based fMRI data. Collaborated with international community of students in Neuromatch academy to localize and characterize prominent regions of activation.

Passive Haptic Learning for Accelerated Learning of Piano

Passive Haptic Learning for Accelerated Learning of Piano

Published:

Designing a custom vibrotactile haptic glove for enabling faster learning of piano skills. Leading a group of undergraduates in manufacturing glove hardware and organizing user studies to evaluate performance. Earned 2nd place Oral Presentation Award at Georgia Tech’s 2022 Undergraduate Research Symposium, to be presented at Intelligent Music Interfaces Workshop at CHI 2022.

BrainBraille: A Passively Learnable Brain Computer Interface using fNIRS

BrainBraille: A Passively Learnable Brain Computer Interface using fNIRS

Published:

Developing a new brain-computer interface using fNIRS to detect attempted motor movement in different regions of the body. Converting attempted motions to language to enable more versatile communication options for people with movement disabilities. Earned the President’s Undergraduate Research Award for project.

2020

SilentSpeller: Silent Speech Text Entry using Electropalatography

SilentSpeller: Silent Speech Text Entry using Electropalatography

Published:

Created the first-ever silent speech system capable of being used with a large vocabulary while in motion. Made a novel text entry system with capacitive tongue sensing from an oral wearable device to enable a privacy-preserving alternative to speech recognition. Earned the 1st Place Oral Presentation Award at Georgia Tech’s 2021 Undergraduate Symposium, demo presented at CHI 2021 and full paper accepted to CHI 2022. Featured by BuzzFeed and other news outlets in the media.

2019

Autonomous Navigation for Mobile Robots in Open Terrain

Autonomous Navigation for Mobile Robots in Open Terrain

Published:

Prepared a complete replica of competition in simulation to enable RoboJackets’ Intelligent Ground Vehicle Competition robots to be tested realistically. Coded motor control firmware and path planning algorithms to enable more accurate robot motion.

2018

2017

Mobile Robotics for Autonomous Humanitarian Demining

Mobile Robotics for Autonomous Humanitarian Demining

Published:

Competed in the IEEE Robotics and Automation Society’s Humanitarian Robotics and Technologies Challenge by applying machine learning for autonomous mine detection with a metal detector on a low-cost robot platform. Earned 3rd place in the competition and demonstrated robot at ICRA 2017 as a finalist.