cv
Basics
Name | Jeonghoon Park |
Label | Undergraduate Student |
hoonably@unist.ac.kr | |
Summary | Undergraduate student at UNIST, researching On-device AI in constrained environments at UAI Lab. |
Work
-
2025.01 - Present Undergraduate Research Intern
Ubiquitous AI Lab (UAI Lab)
Research on On-Device AI, Human-Centered AI, and Adaptive & Personalized AI.
- Supervisor: Prof. Taesik Gong
- Presented academic papers in English
- Experimented with on-device generation models
-
2021.07 - 2024.07 Math Instructor
Topmath
Taught math to students aged 14-19 with personalized instruction.
- Primary (non-part-time) instructor
- Taught 30+ students with personalized instruction
- Tracked and improved student outcomes
Education
-
2020.03 - Present Ulsan, Korea
Awards
- 2025.02.18
Academic Excellence Award
UNIST
Awarded for outstanding academic performance during the Fall semester of 2024.
Skills
Artificial Intelligence |
Computer Science |
Languages
Korean | |
Native speaker |
English | |
Intermediate |
Volunteer
-
2022.11 - 2024.08 Incheon, Korea
Public Service Agent & Volunteer Tutor
Community Children's Center
Served as a public service agent and volunteer at a community children's center, supporting administrative tasks and providing educational support to students.
- Assisted with center management and child engagement activities
- Tutored elementary to high school students across various subjects
Interests
Computer Science | |
Computer Architecture |
Artificial Intelligence | |
On-device AI | |
Personalized AI |
Hobby | |
Piano | |
Soccer | |
Cycle |
References
Professor Taesik Gong | |
Jeonghoon is ... |
Student Jaemin Kim | |
Jeonghoon is funny. |
Projects
- 2025.03 - 2025.06
Pintos Project
Implemented core OS components based on Stanford’s Pintos project: thread scheduling, system calls, user programs, virtual memory (demand paging, swapping, mmap), and extensible file system with indexed allocation. Gained deep insight into OS internals through hands-on implementation.
- Thread scheduling and priority donation
- Demand paging and mmap
- File system with indexed allocation
- 2025.04 - 2025.06
Traveling Salesman Problem (TSP) Solver
Implemented and analyzed classical TSP algorithms (Held-Karp, MST, Greedy, 2-opt) alongside a novel MCMF-based heuristic combining global flow and local refinement. Evaluated solution quality and runtime across diverse datasets.
- Held-Karp, MST, 2-opt, and MCMF heuristic
- Performance comparison and analysis
- 2025.03 - 2025.04
Sorting Algorithm Analysis
Implemented and benchmarked 12 sorting algorithms under various input types and data conditions, analyzing performance, stability, and memory usage.
- Benchmarking of 12 sorting algorithms
- Analysis on stability and memory usage
- 2025.01 - 2025.02
TinyLLM - UAI Lab
Investigated lightweight LLMs for on-device use. Evaluated accuracy and inference time of each model through various evaluation sets, exploring the tradeoffs in size, latency, and performance.
- Evaluation of small LLMs in constrained environments
- Trade-off analysis for on-device use cases