Greetings

I'm a 4th-year Ph.D. candidate in Computer Science at the University of Toronto, working with Prof. Khai Truong in the DGP lab.

My research lies at the intersection of human–AI interaction, accessibility, and creativity support, with a special focus on improving music accessibility for d/Deaf and hard-of-hearing (DHH) individuals. My projects include song signing (CHI ’23) to explore how music is experienced and expressed within Deaf culture, and ELMI (CHI ’25), an LLM-supported English lyrics to ASL gloss translation system.

I completed my B.Sc. in Computer Science and Engineering at Ewha Womans University, where I was advised by Prof. Uran Oh (Human-Computer Interaction Lab) and Prof. Hyokyung Bahn (Distributed Computing and Operating Systems Lab).

Additionally, I worked as a research intern at Samsung AI Center Toronto, where I was mentored by Iqbal Mohomed, and at NAVER AI LAB under the supervision of Young-Ho Kim. Most recently, I interned at Adobe Research in the STORIE Lab, supervised by Anh Truong and Justin Salamon .

💼 I am currently exploring academic (Assistant Professor) and industry (Research Scientist) positions starting in Summer/Fall 2026.

Google Scholar | LinkedIn | suhyeon.yoo[at]mail.utoronto.ca

IEEE RTCSA2020: Power-Saving Integrated Task Scheduling in Multicore and Hybrid Memory Environments

Abstract:
A new task scheduling algorithm that schedules a mixed task set consisting of real-time and interactive tasks is presented. Our algorithm aims at minimizing the power consumption of the system with the reasonable response time of interactive tasks as well as the deadline guarantees of real-time tasks. Experimental results show that the proposed algorithm improves the power consumption by 23% on average.
Date of Conference: 19-21 Aug. 2020
Date Added to IEEE Xplore22 September 2020
Publisher: IEEE
Conference Location: Gangnueng, Korea (South), Korea (South)

Proceedings: https://ieeexplore.ieee.org/abstract/document/9203632









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