- Fluid Interfaces
I received my PhD in 2021, as part of the the Fluid Interfaces group. I work with machine learning and human-centered design for applications in adaptive technology and health, and am particularly interested in personalized technologies and real-world data collection. My PhD research focused on creating new augmentative technologies for communication by developing a better understanding of non-traditional communication styles. In my doctoral work, I developed personalized machine learning models to classify the meaning of nonverbal vocalizations from individuals who do not communicate using typical verbal speech, as well as designed novel research protocols, datasets, and applications with this population. I graduated from MIT in 2017 with a SM in mechanical engineering, and in 2015 with a SB in mechanical and ocean engineering. I have a strong background in computational and analytical modeling, design optimization, and product design.
I co-founded MIT's ATHack, an assistive technologies hackathon that aims to promote innovation and interest in assistive technologies while building connections between community members and student engineers. ATHack emphasizes collaborative development—teams of students are matched with a community co-designer who is living with a disability, and work with the co-designer from ideation through fabrication and testing. Since the hackathon began in 2014, we worked with over 500 student hackers and 100 community co-designers.
I also enjoy outreach and mentoring. I have mentored teams in design and toy development classes at MIT, and have been involved in a number of other outreach events on campus for K-12 students.