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 .

๐Ÿ’ผ 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

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IIBC 2020 : Real-Time Power-Saving Scheduling Based on Genetic Algorithms in Multi-core Hybrid Memory Environments

 [1] S. Yoo, Y. Jo, K. Cho, and H. Bahn, “Real-Time Power-Saving Scheduling Based on Genetic Algorithms in Multi-core Hybrid Memory Environments,” The Journal of The Institute of Internet, Broadcasting and Communication (IIBC) , vol. 20, no. 1, pp. 135–140, Feb. 2020.

[pdf] [journal]


์ดˆ๋ก

์˜์–ด
Recently, due to the rapid diffusion of intelligent systems and IoT technologies, power saving techniques in real-time embedded systems has become important. In this paper, we propose P-GA (Parallel Genetic Algorithm), a scheduling algorithm aims at reducing the power consumption of real-time systems in multi-core hybrid memory environments. P-GA improves the Proportional-Fairness (PF) algorithm devised for multi-core environments by combining the dynamic voltage/frequency scaling of the processor with the nonvolatile memory technologies. Specifically, P-GA applies genetic algorithms for optimizing the voltage and frequency modes of processors and the memory types, thereby minimizing the power consumptions of the task set. Simulation experiments show that the power consumption of P-GA is reduced by 2.85 times compared to the conventional schemes.

ํ•œ๊ตญ์–ด
์ตœ๊ทผ ์‚ฌ๋ฌผ์ธํ„ฐ๋„ท, ์ง€๋Šฅํ˜• ์‹œ์Šคํ…œ ๋“ฑ์˜ ํ™œ์„ฑํ™”๋กœ ์‹ค์‹œ๊ฐ„ ์ž„๋ฒ ๋””๋“œ ์‹œ์Šคํ…œ์˜ ์ „๋ ฅ ์ ˆ๊ฐ ๊ธฐ์ˆ ์ด ์ค‘์š”ํ•ด์ง€๊ณ  ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ๋ฉ€ํ‹ฐ์ฝ”์–ด ์ด๊ธฐ์ข…๋ฉ”๋ชจ๋ฆฌ ํ™˜๊ฒฝ์—์„œ ์‹ค์‹œ๊ฐ„ ์‹œ์Šคํ…œ์˜ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์„ ์ ˆ๊ฐํ•˜๋Š” P-GA (parallel genetic algorithm) ์Šค์ผ€์ค„๋ง ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. P-GA๋Š” ๋ฉ€ํ‹ฐ์ฝ”์–ด๋ฅผ ์œ„ํ•œ PF (proportional fairness) ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๊ธฐ๋ฐ˜ํ•œ ํ”„๋กœ์„ธ์„œ์˜ ์ „์•• ๋ฐ ์ฃผํŒŒ์ˆ˜ ๋™์  ์กฐ์ ˆ ๊ธฐ๋ฒ•์— ์ฐจ์„ธ๋Œ€ ๋น„ํœ˜๋ฐœ์„ฑ๋ฉ”๋ชจ๋ฆฌ ๊ธฐ์ˆ ์„ ๊ฒฐํ•ฉํ•˜์—ฌ ์‹œ์Šคํ…œ์˜ ์ „๋ ฅ ์†Œ๋ชจ๋ฅผ ๋”์šฑ ์ค„์ธ ๋‹ค. ํŠนํžˆ, ์œ ์ „ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์‚ฌ์šฉํ•˜์—ฌ ํƒœ์Šคํฌ๋ณ„ ์ˆ˜ํ–‰ ํ”„๋กœ์„ธ์„œ์˜ ์ „์•• ๋ฐ ์ฃผํŒŒ์ˆ˜ ๋ชจ๋“œ์™€ ๋ฉ”๋ชจ๋ฆฌ์˜ ์ข…๋ฅ˜๋ฅผ ์ตœ์ ํ™”ํ•˜์—ฌ ํƒœ์Šค ํฌ ์ง‘ํ•ฉ์˜ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์„ ์ตœ์†Œํ™”ํ•œ๋‹ค. ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์‹คํ—˜์„ ํ†ตํ•ด P-GA๊ฐ€ ๊ธฐ์กด ๋ฐฉ์‹ ๋Œ€๋น„ ์ตœ๋Œ€ 2.85๋ฐฐ์˜ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์„ ๊ฐ์†Œํ•  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์ธ๋‹ค.

๋ชฉ์ฐจ

์š”์•ฝ
Abstract
Ⅰ. ์„œ๋ก 
Ⅱ. ๋ณธ๋ก 
1. ํ”„๋กœ์„ธ์„œ์˜ ์ „์•• ๋ฐ ์ฃผํŒŒ์ˆ˜ ์กฐ์ ˆ ๋ฐฉ๋ฒ•
2. ๋น„ํœ˜๋ฐœ์„ฑ ์ฐจ์„ธ๋Œ€ ๋ฉ”๋ชจ๋ฆฌ๋ฅผ ์ด์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•
3. ์œ ์ „ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•
4. ์‹œ์Šคํ…œ ๋ชจ๋ธ
Ⅲ. ์„ฑ๋Šฅ ํ‰๊ฐ€
Ⅳ. ๊ฒฐ๋ก 
References

ํ‚ค์›Œ๋“œ

DVFS Genetic Algorithm Hybrid Memory Multi core Real Time Scheduling.

์ €์ž

  • ๋ฅ˜์ˆ˜ํ˜„ [ Suhyeon Yoo | ๋น„ํšŒ์›, ์ดํ™”์—ฌ์ž๋Œ€ํ•™๊ต ์ปดํ“จํ„ฐ๊ณตํ•™๊ณผ ]
  • ์กฐ์˜ˆ์› [ Yewon Jo | ๋น„ํšŒ์›, ์ดํ™”์—ฌ์ž๋Œ€ํ•™๊ต ์ปดํ“จํ„ฐ๊ณตํ•™๊ณผ ]
  • ์กฐ๊ฒฝ์šด [ Kyung-Woon Cho | ์ค€ํšŒ์›, ์ดํ™”์—ฌ์ž๋Œ€ํ•™๊ต ์ž„๋ฒ ๋””๋“œ์†Œํ”„ํŠธ์›จ์–ด์—ฐ๊ตฌ์„ผํ„ฐ ]
  • ๋ฐ˜ํšจ๊ฒฝ [ Hyokyung Bahn | ์ •ํšŒ์›, ์ดํ™”์—ฌ์ž๋Œ€ํ•™๊ต ์ปดํ“จํ„ฐ๊ณตํ•™๊ณผ ] ๊ต์‹ ์ €์ž





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    ํ•œ๊ตญ์ธํ„ฐ๋„ท๋ฐฉ์†กํ†ต์‹ ํ•™ํšŒ ๋…ผ๋ฌธ์ง€ [The Journal of the Institute of Internet, Broadcasting and Communication]
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    ๊ฒฉ์›”๊ฐ„
  • pISSN
    2289-0238
  • eISSN
    2289-0246
  • ์ˆ˜๋ก๊ธฐ๊ฐ„
    2001~2020
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    KCI ๋“ฑ์žฌ
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    KDC 566.57 DDC 629
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