I am a PhD candidate in Computer Science Department at University of Maryland, College Park, working with Professor Hernisa Kacorri. I am a member of Intelligent Assistive Machines lab, HCIL, and TRACE center at UMD. My research interest is about addressing the real-world problems using human-computer interaction and machine learning techniques. I build machine learning applications and investigate interactions between a user and the application using quantitative and qualitative analysis. In my recent projects, I explored the challenges of identifying errors from speech recognizer and conducted user studies to facilitate machine teaching with a teachable object recognizer for non-experts.
I am planning to graduate by February 2021 and I am looking for research positions in academia and industry.
The overarching theme of my research is designing and evaluating accessible interactions with emerging technologies such as wearables and AI-infused applications.
Advisor: Leah Findlater
Reviewing Speech Input with Audio: Differences between Blind and Sighted Users
Jonggi Hong, Christine Vaing, Hernisa Kacorri, Leah Findlater. TACCESS 2020.
Crowdsourcing the Perception of Machine Teaching
Jonggi Hong, Kyungjun Lee, June Xu, Hernisa Kacorri. CHI 2020.
Revisiting Blind Photography in the Context of Teachable Object Recognizers
Kyungjun Lee, Jonggi Hong, Ebrima Jarjue, Simone Pimento, Hernisa Kacorri. ASSETS 2019
Identifying Speech Input Errors Through Audio-Only Interaction
Jonggi Hong, Leah Findlater. CHI 2018.