Dhruv Jain

Dhruv Jain

PhD Student, Computer Science

University of Washington

Twitter

I am a fourth year PhD student in Computer Science and Engineering at the University of Washington. My research focuses on advancing sound accessibility through deployable HCI+AI systems. My work has been published at top HCI venues such as CHI, ASSETS, and UIST and has received multiple best paper awards and honorable mentions. I am advised by Prof. Jon Froehlich and Prof. Leah Findlater. Before starting my PhD, I completed by masters from MIT Media Lab, bachelors from IIT Delhi, and took a gap year to backpack 21 countries. Through publishing a critical reflection of my travel experiences as a hard of hearing individual, I introduced the unique method of auto-ethnography to the field of accessible computing. My biggest pride is the indoor navigation system for visually impaired users which was installed in Indian National Science Museum for two years. Besides professional life, I provide scuba instruction and conduct DIY workshops—so far, 11 one-week workshops in six low-income countries, total 200+ students. Atleast two teams from these workshops have continued their projects and turned them into multinational companies.

Recent Projects

This is the thumbnail image for the project HomeSound

HomeSound

2018 – 2020

This is the thumbnail image for the project Deaf Travel Autoethnography

Deaf Travel Autoethnography

2018 – 2019

This is the thumbnail image for the project SoundWatch

SoundWatch

2018 – 2022

This is the thumbnail image for the project HoloSound

HoloSound

2020

Recent Papers

Sound Sensing and Feedback Techniques for Deaf and Hard of Hearing People

UW CS PhD Dissertation 2022

PDF | doi | Citation | AR Captioning • HoloSound • Personalizing Sound Recognition • ProtoSound • HomeSound • SoundWatch • GlassEar

SoundWatch: deep learning for sound accessibility on smartwatches

CACM 2022

Dhruv Jain, Hung Ngo, Pratyush Patel, Steven Goodman, Khoa Nguyen, Rachel Grossman-Kahn, Leah Findlater, Jon E. Froehlich

PDF | doi | Citation | Code | SoundWatch

ProtoSound: A Personalized and Scalable Sound Recognition System for Deaf and Hard-of-Hearing Users

CHI 2022

Dhruv Jain, Khoa Nguyen, Steven Goodman, Rachel Grossman-Kahn, Hung Ngo, Aditya Kusupati, Ruofei Du, Alex Olwal, Leah Findlater, Jon E. Froehlich

PDF | doi | Citation | ProtoSound • Personalizing Sound Recognition

Recent Videos

ProtoSound: A Personalized and Scalable Sound Recognition System for Deaf and Hard-of-Hearing Users

YouTube | Paper

Toward Sound Recognizer Personalization with d/Deaf and Hard of Hearing Users

YouTube | Paper

Sound Sensing and Feedback Techniques for d/Deaf and Hard of Hearing Users

Recent Talks

Sound Sensing and Feedback Techniques for d/Deaf and Hard of Hearing Users

March 12, 2021 | Carnegie Mellon University, HCII Lecture

Virtual

PDF | PPTX | HoloSound • HomeSound • SoundWatch

Sound Sensing and Feedback Techniques for d/Deaf and Hard of Hearing Users

Feb. 18, 2021 | UW Speech and Hearing Center

Virtual

PDF | PPTX | HoloSound • HomeSound • SoundWatch

Sound Sensing and Feedback Techniques for d/Deaf and Hard of Hearing Users

Dec. 11, 2020 | UW General exam

Virtual

PDF | PPTX | Video | HoloSound • HomeSound • SoundWatch

SoundWatch: Exploring Smartwatch-based Deep Learning Approaches to Support Sound Awareness for Deaf and Hard of Hearing Users

Oct. 28, 2020 | ASSETS 2020

Virtual

PDF | PPTX | SoundWatch

We design, build, and evaluate new interactive tools and techniques to address pressing societal challenges. Makeability refers both to how our technological innovations make new abilities possible for humans as well as our educational mission to help students gain new abilities as they learn and grow through research, invention, and human-centered design.